Large language models in medicine: the potentials and pitfalls: a narrative review
Large language models (LLMs) are artificial intelligence models trained on vast text data to
generate humanlike outputs. They have been applied to various tasks in health care …
generate humanlike outputs. They have been applied to various tasks in health care …
A comprehensive review of model compression techniques in machine learning
This paper critically examines model compression techniques within the machine learning
(ML) domain, emphasizing their role in enhancing model efficiency for deployment in …
(ML) domain, emphasizing their role in enhancing model efficiency for deployment in …
Improving medical reasoning through retrieval and self-reflection with retrieval-augmented large language models
Recent proprietary large language models (LLMs), such as GPT-4, have achieved a
milestone in tackling diverse challenges in the biomedical domain, ranging from multiple …
milestone in tackling diverse challenges in the biomedical domain, ranging from multiple …
Biomedical knowledge graph-optimized prompt generation for large language models
Abstract Motivation Large language models (LLMs) are being adopted at an unprecedented
rate, yet still face challenges in knowledge-intensive domains such as biomedicine …
rate, yet still face challenges in knowledge-intensive domains such as biomedicine …
Improving large language models for clinical named entity recognition via prompt engineering
Importance The study highlights the potential of large language models, specifically GPT-3.5
and GPT-4, in processing complex clinical data and extracting meaningful information with …
and GPT-4, in processing complex clinical data and extracting meaningful information with …
[HTML][HTML] An empirical evaluation of prompting strategies for large language models in zero-shot clinical natural language processing: algorithm development and …
S Sivarajkumar, M Kelley… - JMIR Medical …, 2024 - medinform.jmir.org
Background Large language models (LLMs) have shown remarkable capabilities in natural
language processing (NLP), especially in domains where labeled data are scarce or …
language processing (NLP), especially in domains where labeled data are scarce or …
The first step is the hardest: pitfalls of representing and tokenizing temporal data for large language models
Abstract Objectives Large language models (LLMs) have demonstrated remarkable
generalization and across diverse tasks, leading individuals to increasingly use them as …
generalization and across diverse tasks, leading individuals to increasingly use them as …
[HTML][HTML] Large language models for wearable sensor-based human activity recognition, health monitoring, and behavioral modeling: a survey of early trends, datasets …
E Ferrara - Sensors, 2024 - mdpi.com
The proliferation of wearable technology enables the generation of vast amounts of sensor
data, offering significant opportunities for advancements in health monitoring, activity …
data, offering significant opportunities for advancements in health monitoring, activity …
Lingdan: enhancing encoding of traditional Chinese medicine knowledge for clinical reasoning tasks with large language models
Objective The recent surge in large language models (LLMs) across various fields has yet to
be fully realized in traditional Chinese medicine (TCM). This study aims to bridge this gap by …
be fully realized in traditional Chinese medicine (TCM). This study aims to bridge this gap by …
[HTML][HTML] Ascle—a Python natural language processing toolkit for medical text generation: development and evaluation study
Background Medical texts present significant domain-specific challenges, and manually
curating these texts is a time-consuming and labor-intensive process. To address this …
curating these texts is a time-consuming and labor-intensive process. To address this …