Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 23,141 to 23,150 of 217,176 articles

DoFormer: Causal Transformer for Gene Perturbation

bioRxiv
Learning causal gene regulatory mechanisms from single-cell data, and thereby predicting the effects of unseen perturbations, remains challenging. Observational RNA-seq data alone is insufficient for causal modeling, whereas perturbational data is es... read more 

Polysemanticity in human hippocampal neurons

bioRxiv
To comprehend language, the brain must navigate a high-dimensional semantic landscape while seamlessly contextualizing meaning. Inspired by recent advances in the mechanistic interpretability of large language models (LLMs), we hypothesized that the ... read more 

Whole-body 3D kinematics of freely behaving Drosophila

bioRxiv
Understanding how nervous systems generate coordinated movement requires precise measurement of body kinematics during natural behavior. The fruit fly, Drosophila, is a model organism with sophisticated behavior and well-studied neural circuits, but ... read more 

AI-guided discovery of atypical protein assemblies

bioRxiv
Artificial intelligence (AI) systems such as AlphaFold have transformed structural biology by enabling accurate prediction of protein structures. However, their capacity to uncover new classes of macromolecular assemblies remains largely untapped. We... read more 

A Digital Twin for Tracking and Forecasting Glycemia with Septic Patients in ICUs

medRxiv
We present a digital twin framework for real time glucose monitoring and forecasting in septic patients in intensive care units (ICUs). The framework combines advanced machine learning models trained on continuous glucose measurements with a dynamic ... read more 

Full-Field Stimulus Test for Visual Function Assessment in Ultra-Low Vision with Retinitis Pigmentosa

medRxiv
Purpose: Assessing visual function in patients with ultra-low vision (ULV), particularly those with retinitis pigmentosa (RP), remains a significant challenge in therapeutic development. Full-field stimulus test (FST) provides a quantitative measure ... read more 

Engaging Community and Healthcare Stakeholders in the Design of HIV Retesting Messages: Findings from Human-Centered Design Workshops in Kenya and Uganda

medRxiv
Frequent HIV testing, or "retesting," the practice of regular HIV testing following a negative test result, among persons at high risk of HIV exposure is critical for initiating treatment early among newly infected persons and reducing the risk of HI... read more 

Performance of Large Language Models as a Tool for Primary Care Consultations: Evaluation Study

medRxiv
Since the release of the first ChatGPT model in 2022, large language models (LLMs) have evolved significantly, and an increasing number of users now turn to these generative information systems for inquiries as sensitive and consequential as those re... read more 

Development and Validation of Machine Learning Models for Predicting Mortality in Hospitalised Systemic Lupus Erythematosus Patients in Dr. Sardjito Hospital, Indonesia Machine Learning Prediction of In-Hospital Mortality in SLE

medRxiv
Objectives This study aimed to develop and validate machine learning models to predict in-hospital mortality among systemic lupus erythematosus (SLE) patients using administrative claims data in a tertiary referral center in Indonesia. Methods We con... read more 

Can large language models approximate human perceptions of disease severity? An evaluation using Global Burden of Disease 2010 disability weights

medRxiv
Background: Disability weights (DWs) quantify the severity of health loss and are essential for estimating disability-adjusted life years in the Global Burden of Disease (GBD) framework. Conventional DW estimation relies on resource-intensive populat... read more