Tag:
Medicine/Public Health
AI
Optimizing Neural Architecture with Large Language Models for Efficient Universal Disease Diagnosis in Histopathology Slides
In this study, we present a robust framework for pathology image analysis utilizing large-scale datasets from various sources like Kaggle and Grand-Challenge. We employed...
AI
Optimizing Large Language Models for Improved Detection of Depression and Anxiety
This study, approved by the Human Research Ethics Committee of the University of Hong Kong (EA240276), developed a generative pipeline to transform case descriptions...
AI
Enhancing Human Evaluation of Large Language Models in Healthcare: Addressing Gaps, Challenges, and the Imperative for Standardization
Recent research highlights significant advancements and challenges in utilizing large language models (LLMs) in healthcare. Notably, AlphaFold demonstrates high accuracy in protein structure predictions,...
AI
Assessing the Effectiveness of General-Purpose Large Language Models in Detecting Human Facial Emotions
The study, IRB-exempt from Beth Israel Deaconess Medical Center, utilized the NimStim dataset—comprised of 672 facial expression images from 43 multiracial actors—to evaluate facial...
AI
Harnessing Large Language Models in Clinical Trials: Innovations, Applications, and Future Prospects | BMC Medicine
The recent literature emphasizes significant advancements in drug discovery and clinical trial methodologies, notably through the integration of artificial intelligence (AI) and machine learning....
AI
When Good Intentions Go Wrong: The Dangers of LLMs Spreading Inaccurate Medical Information through Sycophantic Responses
To evaluate language models' familiarity with drugs, we utilized the RABBITS30 dataset, comprising 550 drugs with brand-generic mappings. Using various pre-training corpora and the...
AI
Leveraging a Fine-Tuned Large Language Model for Symptom-Based Depression Assessment
This study investigates a BERT-based language model, MADRS-BERT, fine-tuned on German MADRS interview data for predicting depression severity. The model significantly improved prediction accuracy,...
AI
Leveraging Large Language Models to Predict Patient Health Trajectories for Enhanced Digital Twin Applications
DT-GPT is a novel framework that utilizes fine-tuned pre-trained large language models (LLMs) on clinical data to forecast patients' laboratory values. This method is...