Ai In Medicine
Wearable Data and Multi-Instance Learning for Frailty Estimation in Elderly Cancer Patients
Frailty in elderly cancer patients significantly impacts treatment outcomes, but current assessment methods are often insufficient. This study proposes and validates a multimodal wearable framework utilizing smartwatch and chest strap data to estimate frailty-related functional changes between clini…
Wearable-Based Stress Detection for Elderly Cancer Patients Shows Moderate Agreement with Self-Reported Scores
This study explores the use of multimodal wearable data (smartwatch and ECG sensor) to estimate perceived stress in elderly breast cancer patients. By transforming wearable streams into visual representations and employing an attention-based multiple instance learning (MIL) approach with a Tiny-BioM…
Orthogonal Subspace Decomposition for Multimodal MRI-PET Fusion Reveals Modality-Specific Information
This paper introduces a novel subspace decomposition framework for multimodal imaging analysis, specifically focusing on MRI and PSMA PET data. The method separates PET uptake into an MRI-explainable physiological component and an orthogonal residual, which represents information unique to PET. This…
Ensemble Deep Clustering Enhances EHR Analysis for Heart Failure
Traditional clustering methods often outperform deep learning approaches when analyzing tabular EHR data, as deep learning models are primarily designed for image processing. This paper introduces an ensemble-based deep clustering framework that aggregates multiple embedding dimensions, improving pe…
AI-Powered Personalized Medicine Accelerates Drug Discovery Beyond Traditional Pharmaceutical Pipelines
A single individual, leveraging AI tools like ChatGPT and AlphaFold with a modest investment, successfully designed a custom mRNA cancer vaccine for a pet, achieving significant tumor reduction. This case demonstrates AI's potential to democratize and accelerate drug discovery, outpacing conventiona…
STARC-9: A Diverse Dataset for Colorectal Cancer Histopathology Classification
STARC-9 is a new large-scale dataset for multi-class tissue classification in colorectal cancer (CRC) histopathology. It addresses limitations of existing datasets by providing morphologically diverse, high-quality image tiles across nine clinically relevant tissue classes. The dataset was construct…
MedAgentBench: A Virtual EHR Environment for LLM Agent Benchmarking
MedAgentBench is a novel, comprehensive evaluation suite designed to benchmark large language model (LLM) agents in medical record contexts. It provides a standardized environment for assessing LLM capabilities in complex, interactive healthcare tasks, addressing a critical gap in current evaluation…
From EDA to Bio-Simulation: Applying In Silico Design to Drug Discovery
The convergence of generative AI and multimodality is shifting computing from a tool requiring specialized languages to an intuitive, intention-based system. By applying the 'in silico' simulation paradigms of electronic design automation to biology, the industry is moving toward computer-aided drug…