AI Medical Compendium Journal:
AMIA ... Annual Symposium proceedings. AMIA Symposium

Showing 51 to 60 of 377 articles

MKRAG: Medical Knowledge Retrieval Augmented Generation for Medical Question Answering.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Large Language Models (LLMs), although powerful in general domains, often perform poorly on domain-specific tasks such as medical question answering (QA). In addition, LLMs tend to function as "black-boxes", making it challenging to modify their beha...

Exposing Vulnerabilities in Clinical LLMs Through Data Poisoning Attacks: Case Study in Breast Cancer.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Training Large Language Models (LLMs) with billions of parameters on a dataset and publishing the model for public access is the current standard practice. Despite their transformative impact on natural language processing (NLP), public LLMs present ...

Towards Interpretable End-Stage Renal Disease (ESRD) Prediction: Utilizing Administrative Claims Data with Explainable AI Techniques.

AMIA ... Annual Symposium proceedings. AMIA Symposium
This study explores the potential of utilizing administrative claims data, combined with advanced machine learning and deep learning techniques, to predict the progression of Chronic Kidney Disease (CKD) to End-Stage Renal Disease (ESRD). We analyze ...

Better Blood Pressure Control for Stroke Patients in the ICU: A Deep Reinforcement Learning with Supervised Guidance Approach for Adaptive Infusion Rate Tuning.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Blood pressure variability (BPV) plays a critical role in vascular diseases, particularly in acute ischemic stroke patients in intensive care units (ICUs), where higher BPV correlates with increased mortality rates. Current interventions lack effecti...

Time Matters: Examine Temporal Effects on Biomedical Language Models.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Time roots in applying language models for biomedical applications: models are trained on historical data and will be deployed for new or future data, which may vary from training data. While increasing biomedical tasks have employed state-of-the-art...

Ensuring Fairness in Detecting Mild Cognitive Impairment with MRI.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Machine learning (ML) algorithms play a crucial role in the early and accurate diagnosis of Alzheimer's Disease (AD), which is essential for effective treatment planning. However, existing methods are not well-suited for identifying Mild Cognitive Im...

A Generative Foundation Model for Structured Patient Trajectory Data.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Advancements in artificial intelligence propelled the implementation of general-purpose multitasking agents called foundation models. However, it has been challenging for foundation models to handle structured longitudinal medical data due to the mix...

A Comprehensive System for Searching and Evaluating Genomic Variant Evidence Using AI and Knowledge Bases to Support Personalized Medicine.

AMIA ... Annual Symposium proceedings. AMIA Symposium
We introduce an innovative automated system for the search and assessment of genetic variant evidence, meticulously aligned with ACMG guidelines. Leveraging the synergistic power of artificial intelligence (AI), elastic search, and an extensive knowl...

RDguru: An Intelligent Agent for Rare Diseases.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Large language models (LLMs) have shown great promise in clinical medicine, but their adoption in real-world settings has been limited by their tendency to generate incorrect and sometimes even toxic statements. This study presents a reliable rare di...