Marius Biris

Dr. Marius Biris

orcid

Research Focus & Metrics

Academic Career Length

5Years (2022-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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22 June 2023 in Diagnostics
Verified
Journal Article
Open access
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APAlina Cornelia Pacurari
Alina Cornelia Pacurari
SBSanket Bhattarai
Sanket Bhattarai
Muhammad AbdullahMuhammad Abdullah
Muhammad Abdullah
CAClaudiu Avram
Claudiu Avram
Mederle Alexandru OvidiuMederle Alexandru Ovidiu
Mederle Alexandru Ovidiu
AMAdelina Mavrea
Adelina Mavrea
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.

15 March 2022 in Journal of Clinical Medicine
Verified
Journal Article
Open access
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CCCosmin Ioan Citu
Cosmin Ioan Citu
Florin GorunFlorin Gorun
Florin Gorun
AMAndrei Gheorghe Marius Motoc
Andrei Gheorghe Marius Motoc
ISIoan Sas
Ioan Sas
BBBogdan Laniard Burlea
Bogdan Laniard Burlea
OGOana Maria Gorun
Oana Maria Gorun
Postpartum depression is a major mental health disorder that can negatively affect both mother and baby. In addition, the COVID-19 pandemic associated with extreme measures of the lockdown had profound effects on humanity, increasing the rates of anxiety and depression, especially among women in the postpartum period. The aim of this study was threefold: to determine the prevalence of postpartum depression, to compare the prevalence of postpartum depression at two different times during the COVID-19 pandemic, and to assess a possible association between the timing of childbirth in a given period of the pandemic and the risk of postpartum depression. A cross-sectional study involving 154 women who were interviewed immediately postpartum, using the EPDS scale, was conducted at the Timisoara Municipal Hospital, Romania at two different periods during the COVID-19 pandemic (March–April 2020 during the first wave and August–September 2021 during the fourth wave). The overall prevalence of postpartum depression (EPDS score > 13) was 18.8%, with a statistically significantly higher rate among participants surveyed during the fourth wave of the COVID-19 pandemic in Romania; the COVID-19 pandemic represents an impact on women’s mental health in the postpartum period, increasing the risk of developing postpartum depression.

26 March 2025 in Medicina
Verified
Journal Article
Open access
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AJAna Maria Cristina Jura
Ana Maria Cristina Jura
Daniela-Eugenia PopescuDaniela-Eugenia Popescu
Daniela-Eugenia Popescu
CCCitu Cosmin
Citu Cosmin
MBMarius Biris
Marius Biris
CPCorina Pienar
Corina Pienar
IRIoana Rosca
Ioana Rosca
Background and Objectives: Patent ductus arteriosus (PDA) is common in newborns, being associated with high morbidity and mortality. While maternal and neonatal conditions are known contributors, few studies use advanced machine learning (ML) as predictive factors. This study assessed how maternal pathologies, medications, and neonatal factors affect the risk of PDA using traditional statistics and ML algorithms: Random Forest (RF) and XGBoost (XGB). Materials and Methods: A retrospective 3-year cohort study of 201 NICU neonates assessed maternal and neonatal factors. Logistic regression (LR) and chi-square analyses identified significant predictors, while ML models enhanced predictive accuracy and pinpointed key PDA factors. Results: LR identified prolonged rupture of membranes (>18 h) as the most significant predictor (OR: 13.03, p < 0.001). The ML models identified gestational age, maternal anemia, prenatal care level, birth weight, prolonged rupture of membranes, medication usage, diabetes, pregnancy-induced hypertension, SARS-CoV-2 infection, and cervical cerclage as key predictors. The RF model had 76.3% accuracy, moderate sensitivity (47.4%), and high specificity (90%). XGB performed better with 81.4% accuracy, an AUC of 0.872, sensitivity of 92.5%, and specificity of 57.9%. Conclusions: This study shows that maternal and neonatal factors significantly influence the risk of PDA. ML, particularly XGBoost, enhances predictive abilities, guiding targeted interventions and improving neonatal outcomes.

19 November 2023 in Healthcare
Verified
Journal Article
Open access
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DHDenisa Hinoveanu
Denisa Hinoveanu
DADoru Mihai Anastasiu
Doru Mihai Anastasiu
CCCosmin Ioan Citu
Cosmin Ioan Citu
ZPZoran Popa
Zoran Popa
IEIzabella Erdelean
Izabella Erdelean
LSLavinia Stelea
Lavinia Stelea
During the COVID-19 pandemic, significant shifts occurred in reproductive health, especially among teenagers and young adult women in Romania. This study, conducted from 2020 to 2022, aimed to longitudinally assess contraceptive awareness and its correlation with mental well-being in this demographic. A cohort of 210 participants aged 15–25, with a history of wanted or unwanted pregnancy, was studied. The research involved collaborations with Romanian educational institutions and strict adherence to ethical standards. Participants’ data on contraceptive knowledge and practices were analyzed, considering factors like substance use and prior sexual education. Mental well-being was evaluated using the SF-36, WHOQOL-BREF, GAD-7, and PHQ-9 scales. The study revealed a positive correlation between increased contraceptive knowledge and improved mental health scores. In 2022, 68% of participants displayed proficient contraceptive awareness, up from 52% in 2020. Those with good contraceptive knowledge had an average SF-36 score of 72, indicating a better quality of life, compared to a score of 58 among those with limited knowledge. Furthermore, there was a notable decrease in GAD-7 and PHQ-9 scores among individuals with better contraceptive awareness, suggesting reduced anxiety and depression levels. The SF-36 survey results showed significant improvements across the years: the physical score increased from 52.1 (±6.3) in 2020 to 56.5 (±6.8) in 2022, the mental score from 51.4 (±7.2) to 55.0 (±6.9), and the total score from 53.6 (±7.9) to 57.5 (±8.0). WHOQOL-BREF results showed a substantial increase in the social domain score from 53.6 (±18.2) in 2020 to 63.0 (±20.5) in 2022. GAD-7 scores declined from 7.9 (±2.6) in 2020 to 6.5 (±3.3) in 2022, indicating a decrease in anxiety symptoms. PHQ-9 scores, measuring depression, also showed a downward trend, from 4.8 (±2.2) in 2020 to 3.9 (±2.8) in 2022. These findings highlight the intertwined nature of contraceptive awareness and mental well-being. The improvements in contraceptive awareness positively impacted mental health outcomes, emphasizing the need for targeted educational interventions in this demographic, particularly during global crises like the pandemic.

30 January 2024 in Journal of Clinical Medicine
Verified
Journal Article
Open access
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MIMihaela Ionica
Mihaela Ionica
MBMarius Biris
Marius Biris
Florin GorunFlorin Gorun
Florin Gorun
NNNicoleta Nicolae
Nicoleta Nicolae
ZPZoran Popa
Zoran Popa
ONOctavian Neagoe
Octavian Neagoe
This study aims to investigate the association between anemia and early recurrence in endometrial cancer patients. We retrospectively analyzed the data of 473 endometrial cancer patients treated at our hospital from January 2015 to December 2020. Patients were divided into two groups based on their hemoglobin (Hb) level: anemia group (Hb < 12 g/dL) and non-anemia group (Hb ≥12 g/dL). Early recurrence was defined as recurrence within 2 years of diagnosis. Univariate and multivariate logistic regression analyses were used to identify the predictors of early recurrence. The prevalence of anemia was 38.26% (181/473). The incidence of early recurrence was 12.89% (61/473) in the anemia group and 9.24% (38/412) in the non-anemia group (p = 0.004). Univariate analysis showed that anemia was a significant predictor of early recurrence (odds ratio (OR) = 2.27, 95% confidence interval (CI): 1.35–3.80, p = 0.003). Multivariate analysis confirmed that anemia was an independent predictor of early recurrence (OR = 2.11, 95% CI: 1.21–3.84, p = 0.01). Anemia is an independent predictor of early recurrence in endometrial cancer patients. Patients with endometrial cancer should be screened for anemia and treated if present. Additionally, patients with anemia should be closely monitored for early signs of recurrence and treated aggressively.

20 July 2023 in JMIR Research Protocols
Verified
Journal Article
Open access
FMFilippo Murina
Filippo Murina
PIPaolo Inghirami
Paolo Inghirami
MBMarius Biris
Marius Biris
DSDaniela Sîrbu
Daniela Sîrbu
DBDionisio Franco Barattini
Dionisio Franco Barattini
CCCiprian Doru Crișan
Ciprian Doru Crișan
Background: The medical literature has reported that recurrent bacterial vaginosis (RBV) has a relapse rate of 35% within 3 months and 60% within 12 months after antibiotic administration. Products that are able to provide a barrier effect against the biofilm produced by Gardnerella vaginalis could play a role in improving the results of bacterial vaginosis (BV) treatment. Objective: This study aims to assess the performance and safety of a medical device (Polybactum) containing polycarbophil, lauryl glucoside, and glycerides (PLGG) for reducing the rate of recurrence of BV. Methods: The study includes women who are aged above 18 years, are willing to provide signed informed consent, have a diagnosis of BV according to the Amsel criteria, and have been affected by at least 2 episodes of RBV in the last 12 months. The trial includes 2 phases. In the first phase (according to an open-label noncontrolled design), the treatment involving PLGG is administered for 3 cycles and is followed by a 1-month period of follow-up without treatment. In the second phase, a 9-month follow-up period is envisaged. Thus, for each patient, a 10-month follow-up period without treatment is planned. The study involves 5 centers (2 in Italy and 3 in Romania). We calculated a sample size of 44 pairs to achieve a power of 80% and a 1-sided significance of 5% for detecting a difference of 0.25 between marginal proportions, in comparison with the mean recurrence rate of BV reported in the medical literature. We estimated a potential dropout rate of 20%, and thus, we decided to enroll 55 patients (1-group chi-square test). Results: The study received ethics approval in 2016 in Romania and 1 year later in Italy. Recruitment started in September 2016. An interim analysis was performed in 2019, and full study analysis results are expected in July 2023. Conclusions: The tested medical device involving PLGG could modify the mechanisms involved in the pathogenesis of BV and could improve microbiological parameters owing to the acidifying effect on vaginal pH. We believe that the findings of our study could be useful for other investigators who want to test different products against RBV using a standardized protocol and standardized procedures. Trial Registration: ClinicalTrials.gov NCT02863536; https://clinicaltrials.gov/ct2/show/NCT02863536 International Registered Report Identifier (IRRID): RR1-10.2196/42787