COVID-19

Regulatory risk loci link disrupted androgen response to pathophysiology of Polycystic Ovary Syndrome

A major challenge in deciphering the complex genetic landscape of Polycystic Ovary Syndrome (PCOS) lies in the limited understanding of how susceptibility loci drive molecular mechanisms across diverse phenotypes. To address this, we integrated molecular and epigenomic annotations from proposed causal cell-types and employed a deep learning (DL) framework to predict cell-type-specific regulatory e...

Cross-dataset Evaluation of Dementia Longitudinal Progression Prediction Models

Accurately predicting Alzheimer’s Disease (AD) progression is useful for clinical care. The 2019 TADPOLE (The Alzheimer’s Disease Prediction Of Longitudinal Evolution) challenge evaluated 92 algorithms from 33 teams worldwide. Unlike typical clinical prediction studies, TADPOLE accommodates (1) variable number of observed timepoints across patients, (2) missing data across modalities and visits, a...

DeepSeek as the paradigm shift in rare disease diagnosis – the power of a fully automated genetic variant classification system

Large language models (LLMs) have been extensively tested for incorporating into medical applications in recent years, yet their potential in clinical...

Diagnostic accuracy of a high-throughput multiplex immunoassay for the detection of Mpox virus infection and MVA-BN vaccination up to two years after exposure

Mpox, caused by mpox virus (MPXV), has gained global attention following the 2022 Clade IIb outbreak and the emergence of two novel Clade I lineages i...

Nucleotide motif-guided selection of plasma microRNA biomarkers for organ injury prediction in trauma

Trauma remains a leading cause of morbidity and mortality in part due to secondary organ injury and infection. Yet, our ability to predict the downstr...

Enhancing Pandemic Prediction: A Deep Learning Approach Using Transformer Neural Networks and Multi-Source Data Fusion for Infectious Disease Forecasting

The Covid-19 pandemic has highlighted the urgent need for accurate prediction of pandemic trends. We propose a deep learning model for predicting Covi...

Evaluation of the Bangkok Health Research and Ethics Interest Group: reflecting on the experiences of group members, researchers and facilitators participating in an urban community advisory board in Thailand

The Mahidol Oxford Tropical Medicine Research Unit (MORU), headquartered in Bangkok, conducts research on tropical medicine and global health. MORU wo...

Attention-based deep learning for analysis of pathology images and gene expression data in lung squamous premalignant lesions

Molecular and cellular alterations to the normal pseudostratified columnar bronchial epithelium results in the development of bronchial premalignant l...

Event-based seizure detection in human iEEG with neuromorphic hardware

Epilepsy is a neurological disorder that affects approximately 1% of the global population. The current method for seizure monitoring, seizure diaries...

Zero-Shot Large Language Models for Long Clinical Text Summarization with Temporal Reasoning

Recent advances in large language models (LLMs) have shown potential in clinical text summarization, but their ability to handle long patient trajecto...

Prematurity and Genetic Liability for Autism Spectrum Disorder

Autism Spectrum Disorder (ASD) is a neurodevelopmental condition characterized by diverse presentations and a strong genetic component. Environmental ...

Invisible Text Injection: The Trojan Horse of AI-Assisted Medical Peer Review

Are large language models robust against adversarial attacks in medical peer review? In this factorial experimental study, invisible text injection at...

Development of a novel musculoskeletal hypothesis using sparse Group Factor Analysis: the ADVANCE cohort

Musculoskeletal conditions are a leading global cause of disability, yet the factors influencing long-term musculoskeletal health, particularly follow...

Risk Prediction Modelling of 30-day all-cause mortality following percutaneous coronary intervention in an Australian population: Leveraging Machine Learning

Pre-procedural risk prediction of 30-day all-cause mortality after percutaneous coronary intervention (PCI) aids in clinical decision-making and bench...

Performance of Universal and Stratified Computer-Aided Detection Thresholds for Chest X-Ray-Based Tuberculosis Screening: A Cross-Sectional Diagnostic Accuracy Study

Computer-aided detection (CAD) software analyzes chest X-rays for features suggestive of tuberculosis (TB) and provides a numeric abnormality score. H...

Using SpliceAI to triage splice-altering variants in 7,220 individuals with rare conditions highlights limitations of the precomputed scores

SpliceAI is a deep learning algorithm that predicts whether genetic variants are likely to affect splicing. Precomputed spliceAI predictions for all t...

Delineating retinal breaks in ultra-widefield fundus images with a PraNet-based machine learning model

Retinal breaks are critical lesions that can lead to retinal detachment and vision loss if not detected and treated early. Automated and precise delin...

A Systematic Review of Multimodal Deep Learning and Machine Learning Fusion Techniques for Prostate Cancer Classification

Prostate cancer remains one of the most prevalent malignancies and a leading cause of cancer-related deaths among men worldwide. Despite advances in t...

Regulating Flexibility for Artificial Intelligence FDA Experience with Predetermined Change Control Plans

Predetermined Change Control Plans (PCCPs) are a recent regulatory innovation by the U.S. Food and Drug Administration (FDA) introduced to enable dyna...

Artificial Intelligence quantified prostate specific membrane antigen imaging in metastatic castrate-resistant prostate cancer patients treated with Lutetium-177-PSMA-617

The VISION study1 found that Lutetium-177 (177Lu)–PSMA-617 (“Lu-177”) improved overall survival in metastatic castrate resistant prostate cancer (mCRP...