A sco** review of using large language models (LLMs) to investigate electronic health records (EHRs)

L Li, J Zhou, Z Gao, W Hua, L Fan, H Yu… - arxiv preprint arxiv …, 2024 - arxiv.org
Electronic Health Records (EHRs) play an important role in the healthcare system. However,
their complexity and vast volume pose significant challenges to data interpretation and …

Large language models in medical and healthcare fields: applications, advances, and challenges

D Wang, S Zhang - Artificial Intelligence Review, 2024 - Springer
Large language models (LLMs) are increasingly recognized for their advanced language
capabilities, offering significant assistance in diverse areas like medical communication …

Fingpt: Democratizing internet-scale data for financial large language models

XY Liu, G Wang, H Yang, D Zha - arxiv preprint arxiv:2307.10485, 2023 - arxiv.org
Large language models (LLMs) have demonstrated remarkable proficiency in
understanding and generating human-like texts, which may potentially revolutionize the …

Prompt engineering for healthcare: Methodologies and applications

J Wang, E Shi, S Yu, Z Wu, C Ma, H Dai, Q Yang… - arxiv preprint arxiv …, 2023 - arxiv.org
Prompt engineering is a critical technique in the field of natural language processing that
involves designing and optimizing the prompts used to input information into models, aiming …

Artificial Intelligence in Oncology: Current Landscape, Challenges, and Future Directions

W Lotter, MJ Hassett, N Schultz, KL Kehl, EM Van Allen… - Cancer Discovery, 2024 - AACR
Artificial intelligence (AI) in oncology is advancing beyond algorithm development to
integration into clinical practice. This review describes the current state of the field, with a …

A continued pretrained llm approach for automatic medical note generation

D Yuan, E Rastogi, G Naik, SP Rajagopal… - arxiv preprint arxiv …, 2024 - arxiv.org
LLMs are revolutionizing NLP tasks. However, the use of the most advanced LLMs, such as
GPT-4, is often prohibitively expensive for most specialized fields. We introduce HEAL, the …

Unifying corroborative and contributive attributions in large language models

T Worledge, JH Shen, N Meister… - … IEEE Conference on …, 2024 - ieeexplore.ieee.org
As businesses, products, and services spring up around large language models, the
trustworthiness of these models hinges on the verifiability of their outputs. However, methods …

Assessing and enhancing large language models in rare disease question-answering

G Wang, J Ran, R Tang, CY Chang, YN Chuang… - arxiv preprint arxiv …, 2024 - arxiv.org
Despite the impressive capabilities of Large Language Models (LLMs) in general medical
domains, questions remain about their performance in diagnosing rare diseases. To answer …

Utilizing ChatGPT to enhance clinical trial enrollment

G Peikos, S Symeonidis, P Kasela, G Pasi - arxiv preprint arxiv …, 2023 - arxiv.org
Clinical trials are a critical component of evaluating the effectiveness of new medical
interventions and driving advancements in medical research. Therefore, timely enrollment of …

Prospects for AI clinical summarization to reduce the burden of patient chart review

C Lee, KA Vogt, S Kumar - Frontiers in Digital Health, 2024 - frontiersin.org
Effective summarization of unstructured patient data in electronic health records (EHRs) is
crucial for accurate diagnosis and efficient patient care, yet clinicians often struggle with …