The application of artificial intelligence (AI) in diagnostic imaging has gained significant interest in recent years, particularly in lung cancer detection. This systematic review aims to assess the accuracy of machine learning (ML) AI algorithms in lung cancer detection, identify the ML architectures currently in use, and evaluate the clinical relevance of these diagnostic imaging methods. A systematic search of PubMed, Web of Science, Cochrane, and Scopus databases was conducted in February 2023, encompassing the literature published up until December 2022. The review included nine studies, comprising five case–control studies, three retrospective cohort studies, and one prospective cohort study. Various ML architectures were analyzed, including artificial neural network (ANN), entropy degradation method (EDM), probabilistic neural network (PNN), support vector machine (SVM), partially observable Markov decision process (POMDP), and random forest neural network (RFNN). The ML architectures demonstrated promising results in detecting and classifying lung cancer across different lesion types. The sensitivity of the ML algorithms ranged from 0.81 to 0.99, while the specificity varied from 0.46 to 1.00. The accuracy of the ML algorithms ranged from 77.8% to 100%. The AI architectures were successful in differentiating between malignant and benign lesions and detecting small-cell lung cancer (SCLC) and non-small-cell lung cancer (NSCLC). This systematic review highlights the potential of ML AI architectures in the detection and classification of lung cancer, with varying levels of diagnostic accuracy. Further studies are needed to optimize and validate these AI algorithms, as well as to determine their clinical relevance and applicability in routine practice.

Preeclampsia is a pregnancy-specific illness that is hypothesized to occur due to vitamin D deficiency during pregnancy. Therefore, vitamin D supplementation in early pregnancy should be explored for preventing preeclampsia and promoting neonatal well-being. The present study follows a case-control analysis that aims to determine the effect of vitamin D supplements on reducing the probability of recurrent preeclampsia. We identified 59 patients for the control group without vitamin D supplementation during pregnancy, while 139 patients were included in the cases group of pregnant women with a history of preeclampsia who confirmed taking daily vitamin D supplements in either 2000 UI or 4000 UI until the 36th week of pregnancy. There were 61 (80.3%) patients with a normal serum vitamin D level measured at 32 weeks in the pregnant women who took a daily dose of 4000 UI vitamin D and 43 (68.3%) in those who took a 2000 UI dose of vitamin D, compared to just 32 (54.2%) in those who did not take vitamin D at all. Regarding the blood pressure of pregnant women measured at 32 weeks, it was observed that 20.3% were hypertensive in the no supplementation group, compared to only 11.1% and 6.6% in those who were taking vitamin D during pregnancy (p-value = 0.049). Serum vitamin D levels at 32 weeks were measured at an average value of 23.9 ng/mL, compared with 28.4 ng/mL in the group taking a 2000 UI daily dose and 33.6 in those who supplemented with 4000 UI daily (p-value < 0.001). Proteinuria was identified more often in the group at risk for preeclampsia who did not take vitamin D supplements, while systolic blood pressure (p-value = 0.036) as well as diastolic blood pressure (p-value = 0.012), were all identified to have significantly higher values in the pregnant women with a history of preeclampsia that did not take vitamin D during the current pregnancy. The significant risk factors for preeclampsia development in pregnant patients at risk are: insufficient vitamin D serum levels (<20 ng/mL), OR = 2.52; no vitamin D supplementation, OR = 1.46; more than two pregnancies, OR = 1.89; gestational diabetes mellitus, OR = 1.66; and cardiovascular comorbidities, OR = 2.18. These findings imply that vitamin D has a role in the preservation of placental function and, therefore, in the prevention of the development of late preeclampsia. Pregnant mothers who supplemented their diets with vitamin D were protected against preeclampsia recurrence. Vitamin D supplementation during pregnancy may aid in the prevention of gestational hypertension and preeclampsia.

High-flow nasal cannula (HFNC) is an open oxygen delivery system, which provides heated and humidified oxygen at a high flow (up to 60 L/min). This effect can improve mucociliary function, airway clearance, and level of comfort to the patient. It can provide controlled and adequate fraction of inspired oxygen (FiO₂) between 21% and 100%. Generation of end-expiratory pressure helps in carbon dioxide washout, reduction of anatomical dead space, and recruitment of collapsed alveoli, ultimately improving tissue oxygenation. The use of HFNC in acute hypoxemic respiratory failure, post-extubation period, pre-intubation period, respiratory infection, and obstructive airway disease has been extensively studied, but there are very few studies regarding its use in cardiogenic pulmonary edema. This review provides the current understanding of the physiological effect of HFNC and its application in acute cardiogenic pulmonary edema (ACPE). We conducted a literature search on PubMed using appropriate terms and reviewed relevant articles published within the last 10 years. We found that initial therapy with HFNC in ACPE patients can improve oxygenation and respiratory rate. HFNC can potentially be an alternative to non-invasive positive-pressure ventilation in terms of initial oxygen therapy in patients with ACPE. There is a need for larger prospective studies to evaluate and develop guidelines to consider the use of HFNC in patients with ACPE. We also highlight the fact that if there is no improvement in arterial blood gas parameters after HFNC therapy, initiation of invasive ventilation should not be delayed.

Coronary artery disease (CAD) is a multifactorial disease that involves genetic and environmental interaction. In addition to the well-known CAD risk factors, such as diabetes mellitus, hypertension, hyperlipidemia, and atherosclerosis, it has a genetic component that predisposes to its occurrence even in young people. One of the most commonly studied genes that increase the susceptibility to CAD is renin-angiotensin system (RAS) genes polymorphisms mainly angiotensin-converting enzyme gene (ACE) polymorphisms, angiotensinogen polymorphisms, angiotensin- II type 1 receptor gene polymorphisms, and many other genes. These genetic polymorphisms have a direct association with CAD development or indirect association through causing atherosclerosis and hypertension which, in turn, are complicated by CAD later on. The difference between genetic mutations and polymorphisms lies in the frequency of the abnormal genotype. If the frequency is 1% and more in the general population, it is called polymorphism and if it is less than 1%, then it is called a mutation. According to our findings, after thorough searching, which support the association of RAS genes polymorphisms with premature CAD, hypertension, hypertrophic cardiomyopathy, and atherosclerosis, we recommend additional studies in the form of clinical trials and meta-analyses aiming to create a specific diagnostic tool for CAD risk assessment and discovering the high-risk people as early as possible. Targeted gene therapy, being the future of medicine, needs to be taken into researchers' consideration. It can have promising results in these cases.

Acute respiratory distress syndrome (ARDS) accounts for 10% of all diagnoses in the Intensive Care Unit, and about 40% of the patients succumb to the disease. Clinical methods alone can result in the under-recognition of this heterogeneous syndrome. The purpose of this study is to evaluate the role that big data and machine learning (ML) have played in understanding the heterogeneity of the disease and the development of various prediction algorithms. Most of the work in the field of ML in ARDS has been in the development of prediction models that have comparable efficacies to that of traditional models. Prediction algorithms have been useful in identifying new variables that may be important to consider in the future, supplementing the unknown information with the help of available noninvasive parameters, as well as predicting mortality. Phenotype identification using an unsupervised ML algorithm has been pivotal in classifying the heterogeneous population into more homogenous classes. Big data generated from ventilators in the form of ventilator waveform analysis and images in the form of radiomics have also been leveraged for the identification of the syndrome and can be incorporated into a clinical decision support system. Although the results are promising, lack of generalizability, "black box" nature of algorithms and concerns about "alarm fatigue" should be addressed for more mainstream adoption of these models.

Osteogenesis imperfecta (OI) is a group of rare, permanent genetic bone disorders resulting from the mutations in genes encoding type 1 collagen. It usually is inherited by an autosomal dominant pattern, but it can sometimes occur sporadically. Among the four main types, type III is the most severe type which presents with multiple bone fractures, skeletal deformities, blue sclera, hearing, and dental abnormalities. It is estimated that only 1 in 20,000 cases of OI are detected during infancy, and the diagnosis carries a poor prognosis. This case is reported for the rarity of sporadic OI diagnosis in neonates. We present a case of a 1-day-old neonate following a normal vaginal delivery referred to our center in the view of low birth weight and multiple bony deformities. Physical examination revealed an ill-looking child with poor suckling, gross bony deformities in upper and lower limbs, and blue sclera. X-ray showed thin gracile bones with multiple bone fractures. Echocardiography revealed a 4 mm patent ductus arteriosus. The patient was diagnosed with type III OI with patent ductus arteriosus. Though OI is rare in neonates and infants, it should be considered in the differentials in a newborn presenting with multiple bony deformities regardless of family history, history of trauma, or physical abuse. OI is also associated with cardiac anomalies such as the atrial septal defect and patent ductus arteriosus for which echocardiography is recommended routinely.