Obstetrics & Gynecology

A Data-Driven Approach to Polycystic Ovary Syndrome Diagnosis: Evaluating Machine Learning Models

PCOS is recognized as a major health concern affecting women around the world. Early detection and treatment of PCOS significantly reduce implications in the future. Conventional diagnostic methods are resource-intensive and may be prone to inaccuracies. We should utilize early diagnostic techniques to reduce the severity and overall impact. Machine learning offers a promising approach to improvin...

Translation of miRNA blood-based discovery to molecular testing for clinical diagnosis of endometriosis

Endometriosis is a common yet often underdiagnosed condition, partly due to the lack of reliable diagnostics. This study examines the clinical feasibility of a blood-based, miRNA-driven test to diagnose endometriosis and address the challenges of translating next-generation sequencing (NGS) findings into clinical use. Serum from 20 patients and 20 controls underwent miRNA sequencing to identify di...

Association between zidovudine and adverse pregnancy outcomes/congenital malformations: A pharmacovigilance study using FAERS data

Zidovudine (AZT), a key antiretroviral drug used for HIV treatment and preventing mother-to-child transmission, has insufficient post-marketing pharma...

Concordant and discordant gene expression signatures of twin placentas in the setting of preeclampsia

Multifetal pregnancies are associated with increased risk for preeclampsia (PreE), but the underlying pathogenesis may differ from singleton gestation...

Diagnostic accuracy of Impedance Spectroscopy versus Digital Rectal Examination for Obstetric Anal Sphincter Injuries: a postpartum post-hoc analysis

Accurate diagnosis of obstetric anal sphincter injuries (OASIs) is critical for timely repair and prevention of long-term morbidity, yet digital recta...

Deep Learning-Assisted Skeletal Muscle Radiation Attenuation at C3 Predicts Survival in Head and Neck Cancer

Head and neck cancer (HNC) patients face an increased risk of malnutrition due to lifestyle, tumor localization, and treatment effects. While skeletal...

Signal Mining and Analysis of Adverse Events of Isotretinoin: 20-year real-world pharmacovigilance analysis based on the FAERS database

To identify post-marketing adverse event (AE) signals associated with isotretinoin using real-world data from the U.S. Food and Drug Administration (F...

Machine learning algorithm to predict fragility fractures and identification of important features – an explainable approach

In this study, we developed ML algorithms to predict fragility fractures, considering the occurrence of fractures at different skeletal sites. We inve...

A Case Study on Colposcopy-Based Cervical Cancer Staging Reveals an Alarming Lack of Data Sharing Hindering the Adoption of Machine Learning in Clinical Practice

The inbuilt ability to adapt existing models to new applications has been one of the key drivers of the success of deep learning models. Thereby, shar...

Cross-Species and Tissue-Agnostic Prediction of Human Cancer Treatment Response using AI-Powered Cellular Morphometric Biomarkers from a Genetically Diverse Erbb2 Mouse Model

The success of drug development relies heavily on the use of animal models. However, increasing evidence shows that discoveries in these models often ...

A Comprehensive Approach to Days’ Supply Estimation in a Real-World Prescription Database: Data Cleaning, Imputation, and Adherence Analysis

For accurate medication usage statistics and medication adherence calculations, we need to have an accurate days’ supply (DS) for each prescription. U...

Revealing Shared Tumor Microenvironment Dynamics Related to Microsatellite Instability Across Different Cancers Using Cellular Social Network Analysis

Microsatellite instability (MSI) is a key biomarker for immunotherapy response and prognosis across multiple cancers, yet its identification from rout...

The human milk microbiome varies by environmental factors and is associated with infant growth: findings from the IMiC Consortium

Human milk (HM) is a complex ecological matrix that connects mothers and infants to the surrounding environment, and promotes infant growth and health...

Clinical Validation of RlapsRisk BC in an international multi-cohorts setting

This study evaluated the prognostic performance of RlapsRisk BC, a multimodal deep learning tool designed to predict distant recurrence-free interval ...

Deep learning-based prediction of cardiopulmonary disease in retinal images of premature infants

Bronchopulmonary dysplasia (BPD) and pulmonary hypertension (PH) are leading causes of morbidity and mortality in premature infants. To determine whet...

Predictive Modelling’s role in Improving Pre-exposure Prophylaxis (PrEP) Uptake in High-Risk HIV Groups in Africa: An Integrative Scoping Review

This scoping review explores how predictive modelling can strengthen pre-exposure prophylaxis (PrEP) uptake among high-risk populations in Africa, whe...

Evaluation of Easy-to-Implement Intervention for Menstrual Pain in a Series of N-of-1 Trials: Study Protocol of the Menstrual Pain Intervention Among Students Study (MPIS)

Dysmenorrhea, or menstrual pain, is a prevalent issue among female university students that negatively influences their productivity, academic perform...

Development of Self-Assessment Tools for Osteoporosis among Postmenopausal Vietnamese Women: A Machine Learning Approach

Osteoporosis is a major health concern in Vietnam due to a rise in aging rates. However, cost-effective early screening tools tailored to the Vietname...

Reinforcement learning optimization of automated insulin delivery in type 1 and type 2 diabetes mellitus

Closed-loop insulin delivery systems have proven effective in regulating blood glucose (BG) concentration, thereby reducing the burden of self-care in...

AI-Powered Radiotherapy for Resource-Limited Settings: Advancing Cervical and Prostate Cancer Treatment Planning with the Radiation Planning Assistant (RPA)

Radiotherapy treatment planning is a resource-intensive process characterized by multiple manual steps and clinical hand-offs that contribute to treat...