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Modern radiologic images comply with DICOM (digital imaging and communications in medicine) standard, which, upon conversion to other image format, would lose its image detail and information such as patient demographics or type of image modality that DICOM format carries. As there is a growing interest in using large amount of image data for research purpose and acquisition of large amount of medical image is now a standard practice in the clinical setting, efficient handling and storage of large amount of image data is important in both the clinical and research setting. In this study, four classes of images were created, namely, CT (computed tomography) of abdomen, CT of brain, MRI (magnetic resonance imaging) of brain and MRI of spine. After converting these images into JPEG (Joint Photographic Experts Group) format, our proposed CNN architecture could automatically classify these 4 groups of medical images by both their image modality and anatomic location. We achieved excellent overall classification accuracy in both validation and test sets (> 99.5%), specificity and F1 score (> 99%) in each category of this dataset which contained both diseased and normal images. Our study has shown that using CNN for medical image classification is a promising methodology and could work on non-DICOM images, which could potentially save image processing time and storage space.
Chen-Hua Chiang; Chi-Lun Weng; Hung-Wen Chiu. Automatic classification of medical image modality and anatomical location using convolutional neural network. PLOS ONE 2021, 16, e0253205 .
AMA StyleChen-Hua Chiang, Chi-Lun Weng, Hung-Wen Chiu. Automatic classification of medical image modality and anatomical location using convolutional neural network. PLOS ONE. 2021; 16 (6):e0253205.
Chicago/Turabian StyleChen-Hua Chiang; Chi-Lun Weng; Hung-Wen Chiu. 2021. "Automatic classification of medical image modality and anatomical location using convolutional neural network." PLOS ONE 16, no. 6: e0253205.
In recent years, many types of research have continued to improve the environment of human speech and emotion recognition. As facial emotion recognition has gradually matured through speech recognition, the result of this study provided more accurate recognition of complex human emotional performance, and speech emotion identification will be derived from human subjective interpretation into the use of computers to automatically interpret the speaker’s emotional expression. Focused on use in medical care, which can be used to understand the current feelings of physicians and patients during a visit, and improve the medical treatment through the relationship between illness and interaction. By transforming the voice data into a single observation segment per second, the first to the thirteenth dimensions of the frequency cestrum coefficients are used as speech emotion recognition eigenvalue vectors. Vectors for the eigenvalue vectors are maximum, minimum, average, median, and standard deviation, and there are 65 eigenvalues in total for the construction of an artificial neural network. The sentiment recognition system developed by the hospital is used as a comparison between the sentiment recognition results of the artificial neural network classification, and then use the foregoing results for a comprehensive analysis to understand the interaction between the doctor and the patient. Using this experimental module, the emotion recognition rate is 93.34%, and the accuracy rate of facial emotion recognition results can be 86.3%.
Huan-Chung Li; Telung Pan; Man-Hua Lee; Hung-Wen Chiu. Make Patient Consultation Warmer: A Clinical Application for Speech Emotion Recognition. Applied Sciences 2021, 11, 4782 .
AMA StyleHuan-Chung Li, Telung Pan, Man-Hua Lee, Hung-Wen Chiu. Make Patient Consultation Warmer: A Clinical Application for Speech Emotion Recognition. Applied Sciences. 2021; 11 (11):4782.
Chicago/Turabian StyleHuan-Chung Li; Telung Pan; Man-Hua Lee; Hung-Wen Chiu. 2021. "Make Patient Consultation Warmer: A Clinical Application for Speech Emotion Recognition." Applied Sciences 11, no. 11: 4782.
Background Accurate estimation of neurological outcomes after in-hospital cardiac arrest (IHCA) provides crucial information for clinical management. This study used artificial neural networks (ANNs) to determine the prognostic factors and develop prediction models for IHCA based on immediate preresuscitation parameters. Methods The derived cohort comprised 796 patients with IHCA between 2006 and 2014. We applied ANNs to develop prediction models and evaluated the significance of each parameter associated with favorable neurological outcomes. An independent dataset of 108 IHCA patients receiving targeted temperature management was used to validate the identified parameters. The generalizability of the models was assessed through fivefold cross-validation. The performance of the models was assessed using the area under the curve (AUC). Results ANN model 1, based on 19 baseline parameters, and model 2, based on 11 prearrest parameters, achieved validation AUCs of 0.978 and 0.947, respectively. ANN model 3 based on 30 baseline and prearrest parameters achieved an AUC of 0.997. The key factors associated with favorable outcomes were the duration of cardiopulmonary resuscitation; initial cardiac arrest rhythm; arrest location; and whether the patient had a malignant disease, pneumonia, and respiratory insufficiency. On the basis of these parameters, the validation performance of the ANN models achieved an AUC of 0.906 for IHCA patients who received targeted temperature management. Conclusion The ANN models achieved highly accurate and reliable performance for predicting the neurological outcomes of successfully resuscitated patients with IHCA. These models can be of significant clinical value in assisting with decision-making, especially regarding optimal postresuscitation strategies.
Chen-Chih Chung; Wei-Ting Chiu; Yao-Hsien Huang; Lung Chan; Chien-Tai Hong; Hung-Wen Chiu. Identifying prognostic factors and developing accurate outcome predictions for in-hospital cardiac arrest by using artificial neural networks. Journal of the Neurological Sciences 2021, 425, 117445 .
AMA StyleChen-Chih Chung, Wei-Ting Chiu, Yao-Hsien Huang, Lung Chan, Chien-Tai Hong, Hung-Wen Chiu. Identifying prognostic factors and developing accurate outcome predictions for in-hospital cardiac arrest by using artificial neural networks. Journal of the Neurological Sciences. 2021; 425 ():117445.
Chicago/Turabian StyleChen-Chih Chung; Wei-Ting Chiu; Yao-Hsien Huang; Lung Chan; Chien-Tai Hong; Hung-Wen Chiu. 2021. "Identifying prognostic factors and developing accurate outcome predictions for in-hospital cardiac arrest by using artificial neural networks." Journal of the Neurological Sciences 425, no. : 117445.
This study re-explored the predictive validity of Stroke Prognostication using Age and National Institutes of Health Stroke Scale (SPAN) index in patients who received different treatments for acute ischemic stroke (AIS) and developed machine learning-boosted outcome prediction models. We evaluated the prognostic relevance of SPAN index in patients with AIS who received intravenous tissue-type plasminogen activator (IV-tPA), intra-arterial thrombolysis (IAT) or non-thrombolytic treatments (non-tPA), and applied machine learning algorithms to develop SPAN-based outcome prediction models in a cohort of 2145 hospitalized AIS patients. The performance of the models was assessed and compared using the area under the receiver operating characteristic curves (AUCs). SPAN index ≥100 was associated with higher mortality rate and higher modified Rankin Scale at discharge in AIS patients who received the different treatments. Compared to the lower AUCs for the SPAN-alone model across all groups, the AUCs of the logistic regression-boosted model were 0.838, 0.857, 0.766 and 0.875 for the whole cohort, non-tPA, IV-tPA and IAT groups, respectively. Similarly, the AUCs of the generated artificial neural network were 0.846, 0.858, 0.785 and 0.859 for the whole cohort, non-tPA, IV-tPA and IAT groups, respectively, while for gradient boosting decision tree model, we computed 0.850, 0.863, 0.779 and 0.815. SPAN index has prognostic relevance in patients with AIS who received different treatments. The generated machine learning-based models exhibit good performance for predicting the functional recovery of AIS; thus, their proposed clinical application to aid outcome prediction and decision-making for the patients with AIS.
Chen-Chih Chung; Oluwaseun Adebayo Bamodu; Chien-Tai Hong; Lung Chan; Hung-Wen Chiu. Application of machine learning-based models to boost the predictive power of the SPAN index. International Journal of Neuroscience 2021, 1 -11.
AMA StyleChen-Chih Chung, Oluwaseun Adebayo Bamodu, Chien-Tai Hong, Lung Chan, Hung-Wen Chiu. Application of machine learning-based models to boost the predictive power of the SPAN index. International Journal of Neuroscience. 2021; ():1-11.
Chicago/Turabian StyleChen-Chih Chung; Oluwaseun Adebayo Bamodu; Chien-Tai Hong; Lung Chan; Hung-Wen Chiu. 2021. "Application of machine learning-based models to boost the predictive power of the SPAN index." International Journal of Neuroscience , no. : 1-11.
Personal health records (PHRs) have lots of benefits for things such as health surveillance, epidemiological surveillance, self-control, links to various services, public health and health management, and international surveillance. The implementation of an international standard for interoperability is essential to accessing personal health records. In Taiwan, the nationwide exchange platform for electronic medical records (EMRs) has been in use for many years. The Health Level Seven International (HL7) Clinical Document Architecture (CDA) was used as the standard of the EMRs. However, the complication of implementing CDA became a barrier for many hospitals to realize the standard EMRs. In this study, we implemented a Fast Healthcare Interoperability Resources (FHIR)-based PHR transformation process including a user interface module to review the contents of PHRs. We used “My Health Bank, MHB”, a PHR data book developed and issued to all people by the Taiwan National Health Insurance, as the PHRs contents in this study. Network Time Protocol (NTP)/Simple Network Time Protocol (SNTP) was used in the security and user authentication mechanism when processing and applying personal health information. Transport Layer Security (TLS) 1.2 (such as HyperText Transfer Protocol Secure (HTTPS) was used for protection in data communication. User authentication is important in the platform. OAuth (OAuth 2.0) was used as a user authentication mechanism to confirm legitimate user access to ensure data security. The contents of MHB were analyzed and mapped to the FHIR, and then converted to FHIR format according to the mapping logic template. The function of format conversion was carried out by using ASP.NET. XPath and JSPath technologies filtered out specific information tags. The converted data structure was verified through an HL7 Application Programming Interface (HAPI) server, and a new JSON file was finally created. This platform can not only capture any PHR based on the FHIR format but also publish FHIR-based MHB records to any other platform to bridge the interoperability gap between different PHR systems. Therefore, our implementation/application with the automatic transformation from MHB to FHIR format provides an innovative method for people to access their own PHRs (MHB). No one has published a similar application like us using a nationwide PHR standard, MHB, in Taiwan. The application we developed will be very useful for a single person to use or for other system developers to implement their own standard PHR software.
Yen-Liang Lee; Hsiu-An Lee; Chien-Yeh Hsu; Hsin-Hua Kung; Hung-Wen Chiu. Implement an International Interoperable PHR by FHIR—A Taiwan Innovative Application. Sustainability 2020, 13, 198 .
AMA StyleYen-Liang Lee, Hsiu-An Lee, Chien-Yeh Hsu, Hsin-Hua Kung, Hung-Wen Chiu. Implement an International Interoperable PHR by FHIR—A Taiwan Innovative Application. Sustainability. 2020; 13 (1):198.
Chicago/Turabian StyleYen-Liang Lee; Hsiu-An Lee; Chien-Yeh Hsu; Hsin-Hua Kung; Hung-Wen Chiu. 2020. "Implement an International Interoperable PHR by FHIR—A Taiwan Innovative Application." Sustainability 13, no. 1: 198.
Despite the salient benefits of the intravenous tissue plasminogen activator (tPA), symptomatic intracerebral hemorrhage (sICH) remains a frequent complication and constitutes a major concern when treating acute ischemic stroke (AIS). This study explored the use of artificial neural network (ANN)-based models to predict sICH and 3-month mortality for patients with AIS receiving tPA. We developed ANN models based on evaluation of the predictive value of pre-treatment parameters associated with sICH and mortality in a cohort of 331 patients between 2009 and 2018. The ANN models were generated using eight clinical inputs and two outputs. The generalizability of the model was validated using fivefold cross-validation. The performance of each model was assessed according to the accuracy, precision, sensitivity, specificity, and area under the receiver operating characteristic curve (AUC). After adequate training, the ANN predictive model AUC for sICH was 0.941, with accuracy, sensitivity, and specificity of 91.0%, 85.7%, and 92.5%, respectively. The predictive model AUC for 3-month mortality was 0.976, with accuracy, sensitivity, and specificity of 95.2%, 94.4%, and 95.5%, respectively. The generated ANN-based models exhibited high predictive performance and reliability for predicting sICH and 3-month mortality after thrombolysis; thus, its clinical application to assist decision-making when administering tPA is envisaged.
Chen-Chih Chung; Lung Chan; Oluwaseun Adebayo Bamodu; Chien-Tai Hong; Hung-Wen Chiu. Artificial neural network based prediction of postthrombolysis intracerebral hemorrhage and death. Scientific Reports 2020, 10, 1 -10.
AMA StyleChen-Chih Chung, Lung Chan, Oluwaseun Adebayo Bamodu, Chien-Tai Hong, Hung-Wen Chiu. Artificial neural network based prediction of postthrombolysis intracerebral hemorrhage and death. Scientific Reports. 2020; 10 (1):1-10.
Chicago/Turabian StyleChen-Chih Chung; Lung Chan; Oluwaseun Adebayo Bamodu; Chien-Tai Hong; Hung-Wen Chiu. 2020. "Artificial neural network based prediction of postthrombolysis intracerebral hemorrhage and death." Scientific Reports 10, no. 1: 1-10.
Objective: To investigate the prevalence and risk of subsequent dementia in subjects with sudden hearing loss during a 7-year follow-up period through comparisons with cohorts matched by sex, age group, and year of index date. Study Design: A retrospective matched-cohort study. Setting: The Longitudinal Health Insurance Database 2000 (LHID2000) in Taiwan. Patients: This study included a total of 11,148 subjects, including 1,858 in the study group and 9,290 in the comparison cohort group. Intervention(s): None. Main Outcome Measure(s): We analyzed the differences in sociodemographic characteristics and comorbidities between subjects with sudden hearing loss and the comparison cohort group. Then, we estimated the risk of dementia and also plotted the survival outcomes to evaluate differences in dementia-free survival rates between the two groups. Results: The dementia incidence rates per 1000 person-years were 20.45 and 8.15 for the subjects with sudden hearing loss and comparison cohorts, respectively. When we adjusted for the subjects’ characteristics, the hazard ratio for dementia was 1.69 (95% confidence interval [CI] = 1.06–2.68, p < 0.01) for subjects with sudden hearing loss compared with comparison cohorts during the follow-up period, and subjects with sudden hearing loss had lower 7-year dementia-free survival rates compared with comparison cohorts by using a log-rank test. Furthermore, male subjects with sudden hearing loss had a higher risk of dementia (adjusted hazard ratio [HR] = 2.11) than did the male comparison cohorts. Conclusions: This study revealed a relationship between sudden hearing loss and dementia in an Asian country. The risk of dementia was higher among patients with sudden hearing loss compared with matched cohorts during the 7-year follow-up period.
Ching-Chun Lin; Herng-Ching Lin; Hung-Wen Chiu. Increase Risk of Dementia in Patients With Sudden Hearing Loss. Otology & Neurotology 2020, 41, 1 .
AMA StyleChing-Chun Lin, Herng-Ching Lin, Hung-Wen Chiu. Increase Risk of Dementia in Patients With Sudden Hearing Loss. Otology & Neurotology. 2020; 41 (10):1.
Chicago/Turabian StyleChing-Chun Lin; Herng-Ching Lin; Hung-Wen Chiu. 2020. "Increase Risk of Dementia in Patients With Sudden Hearing Loss." Otology & Neurotology 41, no. 10: 1.
To develop artificial neural network (ANN)-based functional outcome prediction models for patients with acute ischemic stroke (AIS) receiving intravenous thrombolysis based on immediate pretreatment parameters. The derived cohort consisted of 196 patients with AIS treated with intravenous thrombolysis between 2009 and 2017 at Shuang Ho Hospital in Taiwan. We evaluated the predictive value of parameters associated with major neurologic improvement (MNI) at 24 h after thrombolysis as well as the 3-month outcome. ANN models were applied for outcome prediction. The generalizability of the model was assessed through 5-fold cross-validation. The performance of the models was assessed according to the accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUC), The parameters associated with MNI were blood pressure (BP), heart rate, glucose level, consciousness level, National Institutes of Health Stroke Scale (NIHSS) score, and history of diabetes mellitus (DM). The parameters associated with the 3-month outcome were age, consciousness level, BP, glucose level, hemoglobin A1c, history of DM, stroke subtype, and NIHSS score. After adequate training, ANN Model 1 to predict MNI achieved an AUC of 0.944. Accuracy, sensitivity, and specificity were 94.6%, 89.8%, and 95.9%, respectively. ANN Model 2 to predict the 3-month outcome achieved an AUC of 0.933, with accuracy, sensitivity, and specificity of 88.8%, 94.7%, and 86.5%, respectively. The ANN-based models achieved reliable performance to predict MNI and 3-month outcomes after thrombolysis for AIS. The models proposed have clinical value to assist in decision-making, especially when invasive adjuvant strategies are considered.
Chen-Chih Chung; Chien-Tai Hong; Yao-Hsien Huang; Emily Chia-Yu Su; Lung Chan; Chaur-Jong Hu; Hung-Wen Chiu. Predicting major neurologic improvement and long-term outcome after thrombolysis using artificial neural networks. Journal of the Neurological Sciences 2020, 410, 116667 .
AMA StyleChen-Chih Chung, Chien-Tai Hong, Yao-Hsien Huang, Emily Chia-Yu Su, Lung Chan, Chaur-Jong Hu, Hung-Wen Chiu. Predicting major neurologic improvement and long-term outcome after thrombolysis using artificial neural networks. Journal of the Neurological Sciences. 2020; 410 ():116667.
Chicago/Turabian StyleChen-Chih Chung; Chien-Tai Hong; Yao-Hsien Huang; Emily Chia-Yu Su; Lung Chan; Chaur-Jong Hu; Hung-Wen Chiu. 2020. "Predicting major neurologic improvement and long-term outcome after thrombolysis using artificial neural networks." Journal of the Neurological Sciences 410, no. : 116667.
Dementia is a syndrome that involves the deterioration of several higher mental functions in advanced age, and psoriasis is an autoimmune disease characterized by skin plaque. Epidemiological studies have indicated an association between dementia and psoriasis; however, to date, no studies in Asia have reported this association. This study used a population-based medical dataset to explore the association between previously diagnosed psoriasis and dementia in Taiwan. Using the Taiwan Longitudinal Health Insurance Database 2000, we identified 7118 individuals with a diagnosis of dementia; a further 21,354 sex- and aged-matched individuals were randomly extracted as controls. Patients with bullous pemphigoid, which is characterized by inflammatory phenomena similar to that evident in psoriasis, were chosen as a control group. Conditional logistic regression was performed to evaluate the association between dementia and prior psoriasis or bullous pemphigoid among the sampled patients. Of the 28,472 individuals, 2.2, 3.0, and 1.5% of the total, case, and control groups, respectively, had been diagnosed with psoriasis. After adjustments were made for patients’ monthly income, region, urbanization level, diabetes, hyperlipidemia, hypertension, and coronary heart disease, the odds ratio (OR) of diagnosed psoriasis for the case group was 1.46 (95% confidence interval [CI] 1.23–1.73; p < 0.001) compared with the control group. The ORs of a previous psoriasis diagnosis with arthritis and without arthritis in the case group were, respectively, 1.95 and 1.44 times (95% CI 1.03–3.89 and 1.21–1.72, respectively) those of the control group after adjustments for socioeconomic variables, diabetes, hyperlipidemia, hypertension, and coronary heart disease. However, no significant differences in prior bullous pemphigoid were observed between the dementia and control groups (0.5% and 0.4%, respectively). More patients with dementia had prior psoriasis than did patients in the control group. Additional research is required to confirm our results and clarify the relationship.
Ching-Chun Lin; Herng-Ching Lin; Hung-Wen Chiu. Association Between Psoriasis and Dementia: A Population-Based Case–Control Study. American Journal of Clinical Dermatology 2019, 20, 457 -463.
AMA StyleChing-Chun Lin, Herng-Ching Lin, Hung-Wen Chiu. Association Between Psoriasis and Dementia: A Population-Based Case–Control Study. American Journal of Clinical Dermatology. 2019; 20 (3):457-463.
Chicago/Turabian StyleChing-Chun Lin; Herng-Ching Lin; Hung-Wen Chiu. 2019. "Association Between Psoriasis and Dementia: A Population-Based Case–Control Study." American Journal of Clinical Dermatology 20, no. 3: 457-463.
Purpose: Artificial neural networks (ANNs) are one type of artificial intelligence. Here, we use an ANN-based machine learning algorithm to automatically predict visual outcomes after ranibizumab treatment in diabetic macular edema. Methods: Patient data were used to optimize ANNs for regression calculation. The target was established as the final visual acuity at 52, 78, or 104 weeks. The input baseline variables were sex, age, diabetes type or condition, systemic diseases, eye status and treatment time tables. Three groups were randomly devised to build, test and demonstrate the accuracy of the algorithms. Results: At 52, 78 and 104 weeks, 512, 483 and 464 eyes were included, respectively. For the training group, testing group and validation group, the respective correlation coefficients were 0.75, 0.77 and 0.70 (52 weeks); 0.79, 0.80 and 0.55 (78 weeks); and 0.83, 0.47 and 0.81 (104 weeks), while the mean standard errors of final visual acuity were 6.50, 6.11 and 6.40 (52 weeks); 5.91, 5.83 and 7.59; (78 weeks); and 5.39, 8.70 and 6.81 (104 weeks). Conclusions: Machine learning had good correlation coefficients for predicating prognosis with ranibizumab with just baseline characteristics. These models could be the useful clinical tools for prediction of success of the treatments.
Shao-Chun Chen; Hung-Wen Chiu; Chun-Chen Chen; Lin-Chung Woung; Chung-Ming Lo. A Novel Machine Learning Algorithm to Automatically Predict Visual Outcomes in Intravitreal Ranibizumab-Treated Patients with Diabetic Macular Edema. Journal of Clinical Medicine 2018, 7, 475 .
AMA StyleShao-Chun Chen, Hung-Wen Chiu, Chun-Chen Chen, Lin-Chung Woung, Chung-Ming Lo. A Novel Machine Learning Algorithm to Automatically Predict Visual Outcomes in Intravitreal Ranibizumab-Treated Patients with Diabetic Macular Edema. Journal of Clinical Medicine. 2018; 7 (12):475.
Chicago/Turabian StyleShao-Chun Chen; Hung-Wen Chiu; Chun-Chen Chen; Lin-Chung Woung; Chung-Ming Lo. 2018. "A Novel Machine Learning Algorithm to Automatically Predict Visual Outcomes in Intravitreal Ranibizumab-Treated Patients with Diabetic Macular Edema." Journal of Clinical Medicine 7, no. 12: 475.
Osteoporosis and atrial fibrillation (AF) are common in post-menopausal women. Vitamin D and bisphosphonates are widely used to treat osteoporosis, and these may have different effects on the risk of AF. The goal of this study was to evaluate whether different agents for treating osteoporosis modulate the risk of AF in a population-based database. We identified 20,788 female patients suffering from osteoporosis who were or were not treated with vitamin D or bisphosphonates using the Taiwan National Health Insurance nationwide database from 2000 to 2008 and followed them up for 5 consecutive years to determine if they had a new diagnosis of AF after the diagnosis of osteoporosis. There were 14 (2.67%) new AF diagnoses in osteoporosis patients treated with bisphosphonates, one (0.28%) new AF diagnosis in patients treated with vitamin D, and 279 (1.40%) new AF diagnoses in patients who were not treated with vitamin D or bisphosphonates (neither group). Osteoporosis patients who received bisphosphonates showed a higher incidence of AF occurrence than those that were not treated with bisphosphonates (P = .015). In contrast, 1 patient who received vitamin D had a new diagnosis of AF during the study period; thus, the incidence was significantly lower than that in the patients treated with bisphosphonates (P = .007). In addition, the patients who were treated with vitamin D had a lower incidence of AF than did those who were not treated with either vitamin D or bisphosphonates (P = .074). Kaplan–Meier analysis also showed a significant difference in AF occurrence in different groups during the 5-year follow-up (P = .010). Different treatment for osteoporosis may carry diverse risks of AF occurrence. Vitamin D may have potential beneficial effects of reducing AF occurrence in osteoporosis patients.
Hung-Yu Yang; Jen-Hung Huang; Hung-Wen Chiu; Yung-Kuo Lin; Chien-Yeh Hsu; Yi-Jen Chen. Vitamin D and bisphosphonates therapies for osteoporosis are associated with different risks of atrial fibrillation in women. Medicine 2018, 97, e12947 .
AMA StyleHung-Yu Yang, Jen-Hung Huang, Hung-Wen Chiu, Yung-Kuo Lin, Chien-Yeh Hsu, Yi-Jen Chen. Vitamin D and bisphosphonates therapies for osteoporosis are associated with different risks of atrial fibrillation in women. Medicine. 2018; 97 (43):e12947.
Chicago/Turabian StyleHung-Yu Yang; Jen-Hung Huang; Hung-Wen Chiu; Yung-Kuo Lin; Chien-Yeh Hsu; Yi-Jen Chen. 2018. "Vitamin D and bisphosphonates therapies for osteoporosis are associated with different risks of atrial fibrillation in women." Medicine 97, no. 43: e12947.
There is a typographical error in the International Classification of Disease Ninth Revision, Clinical Modification (ICD-9-CM) diagnostic code used for palmar hyperhidrosis. The published manuscript wrongly reports that the ICD-9-CM code used for palmar hyperhidrosis was 708.8 (which indicates a diagnosis of "Other specified urticaria"), when, in actuality, the correct code 780.8 ("Hyperhidrosis") was applied. The authors regret this typographical error.
Chun-An Cheng; Chun-Gu Cheng; Hsin Chu; Hung-Che Lin; Chi-Hsiang Chung; Hung-Wen Chiu; Wu-Chien Chien. Correction to: Risk reduction of long-term major adverse cardiovascular events after endoscopic thoracic sympathectomy in palmar hyperhidrosis. Clinical Autonomic Research 2018, 28, 439 -439.
AMA StyleChun-An Cheng, Chun-Gu Cheng, Hsin Chu, Hung-Che Lin, Chi-Hsiang Chung, Hung-Wen Chiu, Wu-Chien Chien. Correction to: Risk reduction of long-term major adverse cardiovascular events after endoscopic thoracic sympathectomy in palmar hyperhidrosis. Clinical Autonomic Research. 2018; 28 (4):439-439.
Chicago/Turabian StyleChun-An Cheng; Chun-Gu Cheng; Hsin Chu; Hung-Che Lin; Chi-Hsiang Chung; Hung-Wen Chiu; Wu-Chien Chien. 2018. "Correction to: Risk reduction of long-term major adverse cardiovascular events after endoscopic thoracic sympathectomy in palmar hyperhidrosis." Clinical Autonomic Research 28, no. 4: 439-439.
In general, cerebrovascular diseases are composed of approximately 80% ischemic strokes. They are both expensive and time consuming while physicians take care of the acute ischemic stroke (AIS) patients. It is well-known that thrombolysis treatment in AIS patients can reduce disability and increase survival rate, however only one-half of patients have good outcomes. Therefore, we designed a functional recovery prediction model by artificial neural network (ANN) for AIS patients after intravenous thrombolysis to help make better clinical decisions. In this study, we retrospectively collected 157 AIS patients who received intravenous thrombolysis at a medical center in north Taiwan. The outcome defined Modified Rankin Scale ≤2 after three-months follow-up as favorable recovery. 80% data were selected for training this predictive ANN model and 20% data were used for validation. The performance of models is evaluated by Receiver Operating Characteristic (ROC) Curve Analysis. An ANN with 5 inputs and 6 neurons in hidden layer was obtained. The performance of this model was with accuracy 83.87% and the area under ROC curve 0.87. This results showed that this ANN model could achieve a high prediction accuracy for functional recovery evaluation. It is an important issue to predict prognosis of treatment for personalized medicine. Risk and benefit should always be balanced before any treatment is to be applied. The developed prediction models may help physicians to individually discuss and explain the likely recovery probability to patients and their families within short therapeutic time before thrombolysis treatment in the emergency room.
Hung-Wen Chiu; Yu-Ting Huang; Chun-An Cheng. Using Artificial Neural Network to Predict Functional Recovery of Patients Treated by Intravenous Thrombolysis in Acute Ischemic Stroke. VI Latin American Congress on Biomedical Engineering CLAIB 2014, Paraná, Argentina 29, 30 & 31 October 2014 2018, 331 -334.
AMA StyleHung-Wen Chiu, Yu-Ting Huang, Chun-An Cheng. Using Artificial Neural Network to Predict Functional Recovery of Patients Treated by Intravenous Thrombolysis in Acute Ischemic Stroke. VI Latin American Congress on Biomedical Engineering CLAIB 2014, Paraná, Argentina 29, 30 & 31 October 2014. 2018; ():331-334.
Chicago/Turabian StyleHung-Wen Chiu; Yu-Ting Huang; Chun-An Cheng. 2018. "Using Artificial Neural Network to Predict Functional Recovery of Patients Treated by Intravenous Thrombolysis in Acute Ischemic Stroke." VI Latin American Congress on Biomedical Engineering CLAIB 2014, Paraná, Argentina 29, 30 & 31 October 2014 , no. : 331-334.
Hung-Wen Chiu; Yu-Chuan (Jack) Li. Improving healthcare management with data science. Computer Methods and Programs in Biomedicine 2018, 154, A1 .
AMA StyleHung-Wen Chiu, Yu-Chuan (Jack) Li. Improving healthcare management with data science. Computer Methods and Programs in Biomedicine. 2018; 154 ():A1.
Chicago/Turabian StyleHung-Wen Chiu; Yu-Chuan (Jack) Li. 2018. "Improving healthcare management with data science." Computer Methods and Programs in Biomedicine 154, no. : A1.
Hung-Wen Chiu; Yu-Chuan (Jack) Li. Toward precise and preventive healthcare with computational tools. Computer Methods and Programs in Biomedicine 2018, 153, A1 .
AMA StyleHung-Wen Chiu, Yu-Chuan (Jack) Li. Toward precise and preventive healthcare with computational tools. Computer Methods and Programs in Biomedicine. 2018; 153 ():A1.
Chicago/Turabian StyleHung-Wen Chiu; Yu-Chuan (Jack) Li. 2018. "Toward precise and preventive healthcare with computational tools." Computer Methods and Programs in Biomedicine 153, no. : A1.
Sepsis increases the long-term incidence of ischemic stroke (IS). The chances for long-term IS in patients who are discharged after sepsis are unclear. Our aim was to demonstrate long-term risk chances of IS after septicemia discharge. We used a nomogram to identify those septicemia survivors with the higher risk of developing IS.
Chun-An Cheng; Chun-Gu Cheng; Jiuun-Tay Lee; Hung-Che Lin; Cheng-Chung Cheng; Hung-Wen Chiu. An Analysis of Long-Term Ischemic Stroke Risk in Survivors of Septicemia. Journal of Stroke and Cerebrovascular Diseases 2017, 26, 2893 -2900.
AMA StyleChun-An Cheng, Chun-Gu Cheng, Jiuun-Tay Lee, Hung-Che Lin, Cheng-Chung Cheng, Hung-Wen Chiu. An Analysis of Long-Term Ischemic Stroke Risk in Survivors of Septicemia. Journal of Stroke and Cerebrovascular Diseases. 2017; 26 (12):2893-2900.
Chicago/Turabian StyleChun-An Cheng; Chun-Gu Cheng; Jiuun-Tay Lee; Hung-Che Lin; Cheng-Chung Cheng; Hung-Wen Chiu. 2017. "An Analysis of Long-Term Ischemic Stroke Risk in Survivors of Septicemia." Journal of Stroke and Cerebrovascular Diseases 26, no. 12: 2893-2900.
Abdominal pain is one of the key symptoms of irritable bowel syndrome (IBS). Studies have indicated an increase in the incidence of IBS in Asia. However, yet the pathophysiology of this disease remains unknown. Women are more likely to develop the condition than men, especially the constipation-predominant type. Essential fatty acid (EFA) malnutrition is one of several theories discussing the mechanism of IBS. The authors hypothesized that significant EFA deficiency may cause abdominal pain in patients with IBS. However, because patterns in the oral intake of EFAs differ between cultures, the authors narrowed this study to examine the nutritional status of Asian female patients with IBS The authors investigated Asian female patients with IBS and compared them with a group of healthy controls. Thirty patients with IBS and 39 healthy individuals were included in this study. The participants’ age, height, weight, and waist size were recorded. The 24-item Hamilton Depression Rating Scale was documented. Both erythrocyte and plasma fatty acid content were analyzed through gas–liquid chromatography. The authors found that patients with IBS exhibited significantly higher scores for depression, higher proportions of plasma saturated fatty acids and monounsaturated fatty acids, and lower proportions of docosahexaenoic acid and total omega-3 polyunsaturated fatty acids in plasma are associated with IBS in Asian female patients. Further study is indicated to confirm the causality of this association.
Chian Sem Chua; Shih-Yi Huang; Chiao-Wen Cheng; Chyi-Huey Bai; Chien-Yeh Hsu; Hung-Wen Chiu; Jung-Lung Hsu. Fatty acid components in Asian female patients with irritable bowel syndrome. Medicine 2017, 96, e9094 .
AMA StyleChian Sem Chua, Shih-Yi Huang, Chiao-Wen Cheng, Chyi-Huey Bai, Chien-Yeh Hsu, Hung-Wen Chiu, Jung-Lung Hsu. Fatty acid components in Asian female patients with irritable bowel syndrome. Medicine. 2017; 96 (49):e9094.
Chicago/Turabian StyleChian Sem Chua; Shih-Yi Huang; Chiao-Wen Cheng; Chyi-Huey Bai; Chien-Yeh Hsu; Hung-Wen Chiu; Jung-Lung Hsu. 2017. "Fatty acid components in Asian female patients with irritable bowel syndrome." Medicine 96, no. 49: e9094.
Radiofrequency ablation (RFA) provides an effective treatment for patients who exhibit early hepatocellular carcinoma (HCC) stages or are waiting for liver transplantation. It is important to assess patients after RFA. The goal of this study was to build artificial neural network models with HCC-related variables to predict the 1-year and 2-year disease-free survival (DFS) of HCC patients receiving RFA treatments. Methods: This study was a retrospective study that tracked HCC patients who received computer tomography-guided percutaneous RFA between January 2009 and April 2012. The numbers of total patients with 1-year and 2-year DFS were 252 and 179, respectively. A total of 15 HCC clinical variables were collected for the construction of artificial neural network models for DFS prediction. Internal validation and validation conducted using simulated prospective data were performed. Results: The results showed that the model with 15 inputs showed better performance compared with the models including only significant features. Parameters for performance assessment of 1-year DFS prediction were as follows: accuracy 85.0% (70.0%), sensitivity 75.0% (63.3%), specificity 87.5% (71.8%), and area under the curve 0.84 (0.77) for internal validation (simulated prospective validation). For 2-year DFS prediction, the values of accuracy, sensitivity, specificity, and area under the curve were 67.9% (63.9%), 50.0% (56.3%), 85.7% (70.0%), and 0.75 (0.72), respectively, for internal validation (simulated prospective validation). Conclusion: This study revealed that the proposed artificial neural network models constructed with 15 clinical HCC relevant features could achieve an acceptable prediction performance for DFS. Such models can support clinical physicians to deal with clinical decision-making processes on the prognosis of HCC patients receiving RFA treatments
Chiueng-Fang Wu; Yu-Jen Wu; Po-Chin Liang; Chih-Horng Wu; Steven Shinn-Forng Peng; Hung-Wen Chiu. Disease-free survival assessment by artificial neural networks for hepatocellular carcinoma patients after radiofrequency ablation. Journal of the Formosan Medical Association 2017, 116, 765 -773.
AMA StyleChiueng-Fang Wu, Yu-Jen Wu, Po-Chin Liang, Chih-Horng Wu, Steven Shinn-Forng Peng, Hung-Wen Chiu. Disease-free survival assessment by artificial neural networks for hepatocellular carcinoma patients after radiofrequency ablation. Journal of the Formosan Medical Association. 2017; 116 (10):765-773.
Chicago/Turabian StyleChiueng-Fang Wu; Yu-Jen Wu; Po-Chin Liang; Chih-Horng Wu; Steven Shinn-Forng Peng; Hung-Wen Chiu. 2017. "Disease-free survival assessment by artificial neural networks for hepatocellular carcinoma patients after radiofrequency ablation." Journal of the Formosan Medical Association 116, no. 10: 765-773.
Palmar hyperhidrosis (PH) is excessive sweating of the palms resulting from sympathetic overactivity, and patients who undergo endoscopic thoracic sympathectomy (ETS) show reduced cardiac demand after 1 year and improved cerebral perfusion within 2–4 weeks. However, the long-term risks of major adverse cardiovascular events (MACE) following ETS remain unclear. We searched the Longitudinal National Health Insurance Database in Taiwan and identified PH patients (International Classification of Disease, Ninth Revision, Clinical Modification diagnostic code 708.8) from the outpatient database and patients who underwent ETS (procedure code 05.29) from the inpatient database between 2000 and 2010; furthermore, we excluded patients younger than 18 years of age or older than 65 years of age. We defined MACE as stroke (diagnostic codes 430–437), myocardial infarction (diagnostic code 410), or death. Patients followed until the first cardiac event or December 31, 2010. Risk factors were identified using a multivariable Cox proportional hazards regression. The incidence of MACE was significantly lower in patients with ETS (0.76%) than without (1.67%). In PH patients, ETS significantly reduced the risk of MACE (adjusted hazard ratio 0.473; 95% confidence interval 0.277–0.808). PH patients who underwent ETS showed a reduced risk of MACE over a long-term follow-up period. This result could provide support for patients with PH who are considering undergoing ETS because of its additional cardiovascular benefits.
Chun-An Cheng; Chun-Gu Cheng; Hsin Chu; Hung-Che Lin; Chi-Hsiang Chung; Hung-Wen Chiu; Wu-Chien Chien. Risk reduction of long-term major adverse cardiovascular events after endoscopic thoracic sympathectomy in palmar hyperhidrosis. Clinical Autonomic Research 2017, 27, 393 -400.
AMA StyleChun-An Cheng, Chun-Gu Cheng, Hsin Chu, Hung-Che Lin, Chi-Hsiang Chung, Hung-Wen Chiu, Wu-Chien Chien. Risk reduction of long-term major adverse cardiovascular events after endoscopic thoracic sympathectomy in palmar hyperhidrosis. Clinical Autonomic Research. 2017; 27 (6):393-400.
Chicago/Turabian StyleChun-An Cheng; Chun-Gu Cheng; Hsin Chu; Hung-Che Lin; Chi-Hsiang Chung; Hung-Wen Chiu; Wu-Chien Chien. 2017. "Risk reduction of long-term major adverse cardiovascular events after endoscopic thoracic sympathectomy in palmar hyperhidrosis." Clinical Autonomic Research 27, no. 6: 393-400.
Irritable bowel syndrome (IBS) manifests as chronic abdominal pain. One pathophysiological theory states that the brain–gut axis is responsible for pain control in the intestine. Although several studies have discussed the structural changes in the brain of IBS patients, most of these studies have been conducted in Western populations. Different cultures and sexes experience different pain sensations and have different pain responses. Accordingly, we aimed to identify the specific changes in the cortical thickness of Asian women with IBS and to compare these data to those of non-Asian women with IBS. Thirty Asian female IBS patients (IBS group) and 39 healthy individuals (control group) were included in this study. Brain structural magnetic resonance imaging was performed. We used FreeSurfer to analyze the differences in the cortical thickness and their correlations with patient characteristics. The left cuneus, left rostral middle frontal cortex, left supramarginal cortex, right caudal anterior cingulate cortex, and bilateral insula exhibited cortical thinning in the IBS group compared with those in the controls. Furthermore, the brain cortical thickness correlated negatively the severity as well as duration of abdominal pain. Some of our findings differ from those of Western studies. In our study, all of the significant brain regions in the IBS group exhibited cortical thinning compared with those in the controls. The differences in cortical thickness between the IBS patients and controls may provide useful information to facilitate regulating abdominal pain in IBS patients. These findings offer insights into the association of different cultures and sexes with differences in cortical thinning in patients with IBS.
Chian Sem Chua; Chyi-Huey Bai; Chen-Yu Shiao; Chien-Yeh Hsu; Chiao-Wen Cheng; Kuo-Ching Yang; Hung-Wen Chiu; Jung-Lung Hsu. Negative correlation of cortical thickness with the severity and duration of abdominal pain in Asian women with irritable bowel syndrome. PLoS ONE 2017, 12, e0183960 .
AMA StyleChian Sem Chua, Chyi-Huey Bai, Chen-Yu Shiao, Chien-Yeh Hsu, Chiao-Wen Cheng, Kuo-Ching Yang, Hung-Wen Chiu, Jung-Lung Hsu. Negative correlation of cortical thickness with the severity and duration of abdominal pain in Asian women with irritable bowel syndrome. PLoS ONE. 2017; 12 (8):e0183960.
Chicago/Turabian StyleChian Sem Chua; Chyi-Huey Bai; Chen-Yu Shiao; Chien-Yeh Hsu; Chiao-Wen Cheng; Kuo-Ching Yang; Hung-Wen Chiu; Jung-Lung Hsu. 2017. "Negative correlation of cortical thickness with the severity and duration of abdominal pain in Asian women with irritable bowel syndrome." PLoS ONE 12, no. 8: e0183960.