Obstetrics & Gynecology

Systems Vaccinology Reveals Distinct Immune Signatures of Inhaled and Intramuscular SARS-CoV-2 Vaccination in Humans

Mucosal vaccines may reduce both infection and transmission by engaging local immunity, yet the immunological pathways they activate in humans remain poorly defined. Here, we present a comprehensive systems vaccinology analysis of a Modified Vaccinia virus Ankara (MVA)-based SARS-CoV-2 vaccine candidate tested in two distinct phase 1 clinical trials as a booster vaccination with either inhaled or ...

Arkangel AI, OpenEvidence, ChatGPT, Medisearch: are they objectively up to medical standards? A real-life assessment of LLMs in healthcare

Large language models (LLMs) are increasingly used in healthcare, but standardized benchmarks fail to capture their validity and safety in real-world scenarios. Evaluating their quality and reliability is critical for safe integration into practice. Four fictitious clinical vignettes (orthopedics, pediatrics, gynecology, psychiatry) were developed by independent specialists and tested in four conv...

Probing the Surgical Competence of LLMs: A global health study leveraging AfriMedQA benchmarks

Global surgical care faces a severe workforce shortage, with more than 1.2 million additional specialists needed by 2030, particularly in low- and mid...

Clinical Implementation of an AI Algorithm for Substance Misuse Screening in Hospitalized Adults

Manual inpatient screening for substance misuse is labor-intensive and inconsistently applied. Evaluation of artificial intelligence (AI)–assisted scr...

Evaluating Large Language Models in Interpreting Cervical Cytology

Large language models (LLMs) have shown promise in medical imaging, but their utility in cytology remains underexplored. This study evaluates GPT-5 an...

Prediction of TP53 biomarkers and survival outcomes from whole slide images using a vision transformer-based multi-instance learning framework

Accurate molecular profiling and prognostication from routine histopathology slides could transform precision oncology. We developed a Vision Transfor...

CLINPREAI: AN AGENTIC AI SYSTEM FOR EARLY POSTPARTUM DEPRESSION RISK PREDICTION FROM MULTIMODAL EHR DATA

Postpartum depression (PPD) affects 10–15% of mothers annually, yet early identification remains challenging. We introduce ClinPreAI, a novel agentic ...

SPELL: A Scalable NLP Method Using Regular Expressions and Large Language Models for Clinical Information Extraction

Electronic health records (EHRs) contain valuable information for clinical research and decision-making. However, leveraging these data remains challe...

Predicting Polycystic Ovary Syndrome among Reproductive-Aged Women in Bangladesh Using Machine Learning Algorithms: Development of a Hospital-Based Predictive Model

Polycystic ovary syndrome (PCOS) is one of the most common endocrine disorders among reproductive aged women, which is characterized by hormonal imbal...

The Promise and Peril of Large Language Models in Digital Health: GPT-4 Personalizes Cardiovascular Patient Education but Amplifies Gender Biases

Gender-neutral patient education materials often overlook critical sex-based differences in cardiovascular disease (CVD). Large Language Models (LLMs)...

Multidisciplinary large language model agent teams for precision oncology enhance complex gynecologic oncology decision support

Large language models can help with clinical decision-making tasks. Complex oncology cases are best managed through multidisciplinary tumor boards but...

The Role of Food Delivery Apps in Transforming Urban Eating Patterns: A Comprehensive Behavioral and Mathematical Analysis of Swiggy and Zomato Ecosystems

The proliferation of food delivery applications has fundamentally transformed urban dietary behaviors, creating unprecedented shifts in meal consumpti...

Traditional Machine Learning Outperforms Automated Machine Learning for Postpartum Readmission Prediction: A Comprehensive Performance and Health-Economic Analysis

Automated machine learning (AutoML) promises to democratize predictive modeling in healthcare by automating algorithm selection and hyperparameter opt...

Environmental Chemicals as Modifiers of the Association between Age and Ovarian Reserve

To evaluate whether the well-established age-related reduction in antral follicle counts (AFC) is greater among women with higher concentrations of en...

Transcriptome profiling to identify blood biomarkers for peritoneal endometriosis

Peritoneal endometriosis (PE) remains challenging to diagnose, as it cannot be detected using standard imaging modalities and no clinically validated ...

Machine learning-optimized perinatal depression screening: Maximum impact, minimal burden

Perinatal depression affects up to 30% of pregnant and postpartum women, which has increased since the COVID-19 pandemic, making rapidly identifying a...

Implementing Inclusive and Community-Driven AI for Health programs: Lessons from Frontier Technology Pilots in Developing Contexts

The use of Artificial Intelligence (AI) in healthcare is a field of growing relevance and importance, but in many LMICs, those seeking to develop AI b...

Comparative Performance of Machine Learning Models in Predicting Fertility Based on Insights from BDHS Data

Fertility is a social indicator that represents the country’s growth and economic sustainability. The fertility rate in a country signifies the averag...

Comprehensive analysis of mRNA and lncRNA expression for predicting lymph node metastasis in cervical cancer: a novel seven-gene signature approach.

OBJECTIVE: Lymph node metastasis (LNM) critically determines recurrence and survival in cervical cancer (CC), yet current imaging-based methods lack a...

The Hypothalamic Medial Preoptic Area-Paraventricular Nucleus Circuit Modulates Depressive-Like Behaviors in a Mouse Model of Postpartum Depression.

Estrogen fluctuations have been implicated in various mood disorders, including perimenopausal and postpartum depression (PPD), likely through complex...