Clinical Decision Support and Diagnostics
Research on LLMs for medical diagnosis, treatment recommendations, and clinical decision support systems

Clinical Decision Support and Diagnostics
Research on Large Language Models in Clinical Decision Support and Diagnostics

Evaluating AI for Medical Self-Diagnosis
A new method for detecting medical misinformation in LLMs

Enhancing Medical Diagnosis with AI
Integrating Medical Knowledge Graphs with LLMs for Improved Diagnostic Accuracy

RaDialog: AI Assistant for Radiologists
Transforming Radiology With Conversational AI and Report Generation

AI-Powered Medication Recommendations
Using Large Language Models to Enhance Prescription Accuracy

Revolutionizing Clinical Trial Documentation with AI
How LLMs can streamline document creation while maintaining regulatory compliance

Evaluating LLMs for Complex Medical Decision Support
Benchmarking AI capabilities in challenging clinical scenarios

Unlocking Medical Insights with Small Models
How small trigger models help LLMs excel with medical tabular data

AI-Powered X-Ray Diagnosis
Integrating Visual Data with Clinical Records for Better Diagnostic Accuracy

Breakthrough in Medical AI: 3D CT Scan Foundation Models
First multimodal dataset enables text-guided AI for 3D medical imaging

LLMs as Medical Rule Testers
Using AI to validate cancer registry data systems

Smart Classification on a Budget
Optimizing the cost-accuracy tradeoff in machine learning inference

CancerLLM: Specialized AI for Oncology
A 7B parameter LLM optimized for cancer diagnosis and phenotyping

Enhancing Clinical Diagnosis with AI
Combining LLMs and Knowledge Graphs for Improved Medical Decision-Making

Predicting LLM Uncertainty
How prompt information affects reliability in critical applications

Humans + AI: Better Together
Confidence-weighted integration creates superior decision outcomes

HELIOT: Reducing Medication Errors with AI
An LLM-powered Clinical Decision Support System for safer drug management

HealthQ: Transforming AI-Patient Conversations
Evaluating LLMs' ability to ask the right questions in healthcare

ColaCare: Revolutionizing EHR Analysis
Enhancing healthcare decision support through LLM-driven multi-agent collaboration

Smart OOD Detection Selection
Automating the choice of distribution shift detection models

Advancing Chinese Medical AI for Patient Care
Building robust medical dialogue systems through large-scale data integration

Controlling Conversations with LLMs
Zero-Shot Dialog Planning for Safer AI Interactions

Improved Confidence in AI Decision-Making
New calibration techniques for language model reliability in security applications

Medical Decision Support Enhanced by AI
Integrating Medical Calculators with LLM Agents

Enhancing Medical Diagnosis with AI
A dual-knowledge approach to clinical reasoning

Transparent AI for Skin Lesion Diagnosis
A two-step approach enhancing interpretability without sacrificing accuracy

LLMs vs. Humans in Clinical Decision-Making
Evaluating AI models' performance with medical calculators

AI-Powered Cancer Support
Leveraging Large Language Models for Improved Cancer Care

AI-Powered Patient Matching for Clinical Trials
Multi-Agent Systems Revolutionizing Clinical Trial Recruitment

Leveraging LLMs as Expert Proxies
Using AI to enhance predictive models when data is scarce

AI Predicting Clinical Trial Outcomes
GPT-4o shows promise but struggles with negative outcome identification

Benchmarking LLMs for Radiology Agents
Evaluating AI capabilities in clinical radiology environments

RareAgents: AI-Powered Rare Disease Care
Using LLMs to create multi-disciplinary expert teams for rare disease management

KG4Diagnosis: Enhancing Medical AI Diagnosis
A hierarchical multi-agent framework with knowledge graph integration

Bridging East & West: AI for TCM
First specialized LLM for Traditional Chinese Medicine

AI-Enhanced Mental Health Diagnosis
Combining Large Language Models with Logic Programming for Interpretable Clinical Support

Advancing Medical AI with FineMedLM-o1
Enhancing medical reasoning through innovative fine-tuning techniques

Reimagining Virtual Patient Simulations
Bridging the Gap Between Medical Inquiry and Diagnosis with LLMs

Bridging the Gap in Medical AI
Combining LLMs with Specialized Models for Enhanced Medical Time Series Analysis

Enhancing LLMs for Radiation Oncology
Fine-tuning open-source models for specialized medical applications

LLMs for Clinical Diagnosis: MERA
Enhancing disease prediction through memory and ranking techniques

Multi-Agent Reasoning with Layered CoT
Enhancing LLM Explainability Through Structured Reasoning Layers

LLMs Advancing Rare Disease Diagnosis
Using AI to prioritize genes for improved diagnostic accuracy

Enhancing Mental Health Care with AI
LLMs improve prediction and interpretation of ED return risks

Harnessing LLMs for Disease Prediction
Multi-layered approach revolutionizing telehealth diagnosis

AI for Medicare Conversations
Comparing Fine-tuning vs. RAG for Medical Dialogues

JingFang: Expert-Level AI for Traditional Chinese Medicine
Bridging ancient healing practices with modern AI technology

The Rigid Reasoning of Medical AI
Uncovering Critical Limitations in Clinical LLM Applications

AI-Powered Early Detection of Alzheimer's Disease
Using LLMs to analyze speech patterns for timely diagnosis

Smarter Medical AI with MedRAG
Enhancing diagnostic accuracy using knowledge graph-based reasoning

AI Revolution in Alzheimer's Care
Leveraging Large Language Models for Neurodegenerative Disease Management

Patient-Centric Medical AI
Improving LLMs for Interactive Medical Consultations

Enhancing Food Safety with AI
Data Augmentation Powers Better Hazard Detection Models

Smart LLM Cascades That Know When to Step Back
Reducing costs while managing risk through strategic abstention

Next-Gen Medical AI: Proactive Diagnosis Systems
Transforming doctor-patient interactions with multi-round vision-language models

Transparent AI for Resource Allocation
Combining LLMs with Reinforcement Learning for Explainable Decision-Making

OctoTools: Solving Complex Reasoning Challenges
A flexible, training-free framework that integrates diverse tools with LLMs

Enhancing Medical QA with Factual Knowledge
A new retrieval approach that improves LLM accuracy for healthcare

Voice-Powered Medical Diagnostics
Integrating ASR and LLMs for Advanced Healthcare Support

Controlling What LLMs Learn
A framework for removing unwanted features from classification models

Predicting Lab Test Results with AI
A unified language modeling approach for EHR data

Smarter Medical Diagnosis with Adaptive RAG
Fine-tuning LLM retrieval based on information density

Teaching LLMs to Ask Better Questions
Improving clinical reasoning through attribute-focused question alignment

LLMs for Rare Disease Diagnosis
Advancing healthcare with AI that helps identify challenging rare conditions

AutoMedPrompt: Optimizing LLM Performance in Medicine
Enhancing Medical AI Through Textual Gradients Without Model Retraining

AI-Powered Heart Failure Assessment
A Composable Framework Using Video-Text Large Language Models

Citrus: AI Physician's Cognitive Assistant
Transforming Medical Decision Support Through Expert Cognitive Pathways

AI-Powered Clinical Trial Recruitment
Secure LLM Pipeline for Hepatopathy Patient Pre-screening

AI-Powered Medical Diagnosis
A Modular Framework for Explainable Differential Diagnosis

AI-Powered Decision Agents for Complex Eligibility Problems
Using Program Synthesis Dialogue to Navigate Legal & Medical Decisions

The Large Language Expert
Merging LLMs with Expert Systems for Clinical Decision Support

NeuroSymAD: Interpretable AI for Alzheimer's Diagnosis
Combining neural networks with symbolic reasoning for transparent medical decisions

LLMs Revolutionizing Cancer Diagnostics
Automated extraction of critical cancer insights from pathology reports

AI-Powered Early Dementia Detection
A Context-Aware Multimodal Approach Using Large Pre-trained Models

AI-Powered Medication Management
Fine-Tuning Large Language Models to Reduce Overprescription

RiskAgent: Revolutionizing Medical Risk Prediction
An AI Copilot for Comprehensive Disease Risk Assessment

Adaptive Expert Selection for Complex Reasoning
A symbolic approach to dynamically route queries to specialized LLM experts

Advancing Clinical Intelligence with LLMs
From diagnosis to comprehensive disease management

Explainable AI for Cannabis-Related Healthcare
Building Trust in Clinical Decision Support Systems

Raising the Bar for Medical AI
A new benchmark for testing complex medical reasoning in LLMs

Evaluating LLMs for Healthcare Referrals
New framework assesses AI models in outpatient referral systems

LLMs as Medical Diagnosticians
Comparing DeepSeek-R1 and O3 Mini's Disease Detection Capabilities

Evaluating LLMs for Medical Diagnosis
Assessing reliability for potential healthcare democratization

The Evolution of Reasoning in LLMs
Mapping strategies to bridge the gap between language proficiency and reasoning abilities

Enhancing Rare Disease Diagnosis with AI
Combining Chain-of-Thought and Retrieval Augmentation Improves LLM Diagnostic Capabilities

Advancing AI with Multimodal Chain-of-Thought Reasoning
How step-by-step reasoning is transforming multimodal AI systems

AI-Powered Inpatient Care Pathways
Multi-agent LLM framework for enhanced clinical decision support

Revolutionizing Patient Matching with LLMs
Leveraging AI to Connect Patients with Clinical Trials

MDTeamGPT: Revolutionizing Medical Consultations
A Self-Evolving Multi-Agent Framework for Collaborative Medical Decision-Making

CARE: Fast, Efficient Multi-Domain Chatbot
Fine-tuning LLMs with minimal resources for specialized customer support

Evolving Better Decision Trees with LLMs
A semantic approach to optimizing interpretable models

Enhancing Cancer Staging with AI
How Retrieval-Augmented Generation Improves LLM Accuracy in Medical Diagnosis

Enhancing AI Medical Diagnostics
Improving LLM performance through simulated clinical experience

AI-Powered Cardiac Event Adjudication
Revolutionizing Clinical Trials with Large Language Models

Clinical Calculator Chatbots: Enhancing Medical Decision Support
Combining LLMs with verifiable clinical calculators for 100% accuracy

Enhancing Medical LLM Consultations
Improving AI patient interactions through specialized retrieval and emotional learning

AI-Powered Gait Assessment
Enhancing clinical diagnosis with explainable LLM reasoning

MedAgent-Pro: AI-Powered Medical Diagnosis
Multi-modal Evidence-based Diagnosis through Agentic Reasoning

AI-Powered Lung Cancer Detection
Radiomic-Guided Vision-Language Models for Precise Nodule Analysis

AI-Powered Medical Diagnosis Discovery
Using LLMs to uncover hidden diagnoses in clinical notes

Enhancing Biomedical Knowledge Discovery
Deep Thinking LLMs + Retrieval for Clinical Support

AI-Powered Speech Pathology Detection
Leveraging ChatGPT for Interpretable Disease Detection from Speech

AI Medical Interviews: Advancing Healthcare Efficiency
Evaluating LLMs for Automated Patient History-Taking in OB-GYN

Enhancing Medical Reasoning with Test-Time Scaling
Optimizing LLM performance for healthcare applications

Enhancing Medical AI with Transparent Reasoning
Using Knowledge Graphs to Improve LLM Reasoning in Clinical Settings

Debiasing LLMs for Better Decision Support
Strategies to overcome cognitive biases in AI-assisted decision-making

Strategic Information Gathering with LLMs
Adaptive questioning techniques for uncovering latent information

Advancing Retrieval for Knowledge-Intensive AI
Beyond Semantic Matching: Causal Retrieval for Critical Domains

The Hidden Dangers of LLM Medical Diagnoses
When AI gets the right answer for the wrong reasons

AI-Powered Blood Culture Stewardship
Using Machine Learning and LLMs to Optimize Healthcare Resources

Revolutionizing Medical AI with Multi-Round Diagnostic Systems
A novel RAG framework simulating doctor-patient diagnostic conversations

ClinicalGPT-R1: AI Advancing Medical Diagnosis
How LLMs are being specialized for clinical reasoning in healthcare

Adaptive Medical Agents: The Future of Digital Diagnosis
Creating flexible LLM-based agents that learn to think like doctors

Predicting Overdose Risk with AI
Leveraging Large Language Models for Better Patient Outcomes
