Hospital-Based Medicine

Intensivists

Latest AI and machine learning research in intensivists for healthcare professionals.

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Automating Candidate Gene Prioritization with Large Language Models: From Naive Scoring to Literature-Grounded Validation

Identifying promising therapeutic targets from thousands of genes in transcriptomic studies remains ...

Multi-modal data integration for machine learning applications

The integration of multi-modal genomic data, encompassing sequences, annotations, and coverage track...

A Non-Intrusive Computer Vision Framework for Real-Time Vital Sign Digitization and Adaptive Drug Infusion in Critical Care Environments

This work proposes a computer vision framework to automate the extraction of vital signs from bedsid...

E1: Retrieval-Augmented Protein Encoder Models

Large language models trained on natural proteins learn powerful representations of protein sequence...

MOTLAB: A Weighted Multi-Omics Transfer Learning Approach to Mitigate Breast Cancer Racial Disparities

Breast cancer (BC) is a leading cause of cancer death among women in United States. Previous studies...

Care Phenotypes In Critical Care

The Social Determinants of Health (SDoH) have long been recognised as significant drivers of health ...

Deep Learning–Based Early Detection of Major Adverse Cerebral Injuries in Cardiothoracic and Vascular Surgery

Despite advances in central nervous system (CNS)-protective anesthetic and surgical strategies, peri...

ORAKLE: Optimal Risk prediction for mAke30 in patients with acute Kidney injury using deep Learning

Major Adverse Kidney Events within 30 days (MAKE30) is an important patient-centered outcome for ass...

Summarizing Clinical Notes using LLMs for ICU Bounceback and Length-of-Stay Prediction

Recent advances in the Large Language Models (LLMs) provide a promising avenue for retrieving releva...

ICU Readmission Prediction for Intracerebral Hemorrhage Patients using MIMIC III and MIMIC IV Databases

Intracerebral hemorrhage (ICH) is a critical form of stroke resulting from bleeding within the brain...

NutriSighT: Interpretable Transformer Model for Dynamic Prediction of Hypocaloric Enteral Nutrition in Mechanically Ventilated Patients

Achieving adequate enteral nutrition among mechanically ventilated patients is challenging, yet crit...

A deep learning model for clinical outcome prediction using longitudinal inpatient electronic health records

Recent advances in deep learning show significant potential in analyzing continuous monitoring elect...

Generative AI Mitigates Representation Bias and Improves Model Fairness Through Synthetic Health Data

Representation bias in health data can lead to unfair decisions and compromise the generalisability ...

Multi-contrast machine learning improves schistosomiasis diagnostic performance

Schistosomiasis currently affects over 250 million people and remains a public health burden despite...

Predicting mortality in critically ill patients with hypertension using machine learning and deep learning models

Accurate prediction of mortality in critically ill patients with hypertension admitted to the Intens...

Development of Interactive Nomograms for Predicting Short-Term Survival in ICU Patients with Aplastic Anemia

Aplastic anemia is a severe hematologic disorder marked by pancytopenia and bone marrow failure. ICU...

InfEHR: Resolving Clinical Uncertainty through Deep Geometric Learning on Electronic Health Records

Electronic health records (EHRs) contain multimodal data that can inform diagnostic and prognostic c...

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