Latest AI and machine learning research in risk management for healthcare professionals.
Sensitivity to staining variation remains a major barrier to deploying computational pathology (CPath) models as hematoxylin and eosin (H&E) staining varies across laboratories, requiring systematic assessment of how this variability affects model prediction. In this work, we developed a three-step protocol for evaluating robustness to H&E staining variation in CPath models. Step 1: Select referen...
The rapid development of generative models for single-cell gene expression data has created an urgent need for standardised evaluation frameworks. Current evaluation practices suffer from inconsistent metric implementations, incomparable hyperparameter choices, and a lack of biologically-grounded metrics. We present Generated Genetic Expression Evaluator (GGE), an open-source Python framework that...
Recent advances in Large Language Models (LLMs) present new opportunities for automating critical bottlenecks in scientific workflows such as literatu...
Medication errors and adverse drug events (ADEs) pose significant risks to patient safety, often arising from difficulties in reliably identifying pha...
The T cell's ability to discern self and non-self depends on its T cell receptor (TCR), which recognizes peptides presented by MHC molecules. Understa...
Background: Remote patient monitoring (RPM) generates vast data, yet landmark trials (Tele-HF, BEAT-HF) failed because data volume overwhelmed clinica...
Document Image Machine Translation (DIMT) seeks to translate text embedded in document images from one language to another by jointly modeling both te...
Real-world image restoration (RWIR) is a highly challenging task due to the absence of clean ground-truth images. Many recent methods resort to pseudo...
Multimodal Large Language Models (MLLM) classification performance depends critically on evaluation protocol and ground truth quality. Studies compari...
Arterial spin labeling (ASL) perfusion MRI allows direct quantification of regional cerebral blood flow (CBF) without exogenous contrast, enabling non...
We developed and validated a self-administered clinical vignette platform powered by a large language model (LLM), deployed through a SurveyCTO web su...
Introduction: Physical fatigue is a key determinant of operational readiness in the physically demanding occupations of tactical athletes. Specific ho...
Recent methods for pathology report generation from whole-slide image (WSI) are capable of producing slide-level diagnostic descriptions but fail to g...
Significant progress has been made in the field of Instruction-based Image Editing Models (IIEMs). However, while these models demonstrate plausible a...
Objective: The objective of this study is to develop a machine learning (ML)-based framework for early risk stratification of clinical trials (CTs) ac...
Background: Objective Structured Clinical Examination (OSCE; Clinical Performance Examination [CPX] in South Korea) is a high-stakes assessment of cli...
Large language models (LLMs) are increasingly evaluated for structured clinical decision support tasks, often using multi-agent architectures. Prior w...
Background: EHR documentation and chart review contribute to clinician workload and burnout. To alleviate pre-charting burden, Epic has released a new...
Electronic health records (EHRs) have become the cornerstone of population-scale genetic studies1, but factors including patterns of healthcare use sh...
Objective: Electronic Health Record (EHR)-based trial emulation can support translation of randomized clinical trial (RCT) evidence into practice, yet...