AIMC Topic: Large Language Models

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A Causality-Aware Paradigm for Evaluating Creativity of Multimodal Large Language Models.

IEEE transactions on pattern analysis and machine intelligence
Recently, numerous benchmarks have been developed to evaluate the logical reasoning abilities of large language models (LLMs). However, assessing the equally important creative capabilities of LLMs is challenging due to the subjective, diverse, and d...

Aligning, Autoencoding and Prompting Large Language Models for Novel Disease Reporting.

IEEE transactions on pattern analysis and machine intelligence
Given radiology images, automatic radiology report generation aims to produce informative text that reports diseases. It can benefit current clinical practice in diagnostic radiology. Existing methods typically rely on large-scale medical datasets an...

Prompting large language models to extract chemical‒disease relation precisely and comprehensively at the document level: an evaluation study.

PloS one
Given the scarcity of annotated data, current deep learning methods face challenges in the field of document-level chemical-disease relation extraction, making it difficult to achieve precise relation extraction capable of identifying relation types ...

Year 2023 in Biomedical Natural Language Processing: a Tribute to Large Language Models and Generative AI.

Yearbook of medical informatics
OBJECTIVES: This synopsis gives insights into scientific publications from 2023 in Natural Language Processing for the biomedical domain. We present the process we followed to identify candidates for NLP's best papers and the two best papers of this ...

Natural Language Processing for Digital Health in the Era of Large Language Models.

Yearbook of medical informatics
OBJECTIVES: Large language models (LLMs) are revolutionizing the natural language pro-cessing (NLP) landscape within healthcare, prompting the need to synthesize the latest ad-vancements and their diverse medical applications. We attempt to summarize...

Knowledge Representation and Management in the Age of Long Covid and Large Language Models: a 2022-2023 Survey.

Yearbook of medical informatics
OBJECTIVES: To select, present, and summarize cutting edge work in the field of Knowledge Representation and Management (KRM) published in 2022 and 2023.

A Narrative Review on the Application of Large Language Models to Support Cancer Care and Research.

Yearbook of medical informatics
OBJECTIVES: The emergence of large language models has resulted in a significant shift in informatics research and carries promise in clinical cancer care. Here we provide a narrative review of the recent use of large language models (LLMs) to suppor...

Can off-the-shelf visual large language models detect and diagnose ocular diseases from retinal photographs?

BMJ open ophthalmology
BACKGROUND: The advent of generative artificial intelligence has led to the emergence of multiple vision large language models (VLLMs). This study aimed to evaluate the capabilities of commonly available VLLMs, such as OpenAI's GPT-4V and Google's Ge...

Using Large Language Models to Automate Data Extraction From Surgical Pathology Reports: Retrospective Cohort Study.

JMIR formative research
BACKGROUND: Popularized by ChatGPT, large language models (LLMs) are poised to transform the scalability of clinical natural language processing (NLP) downstream tasks such as medical question answering (MQA) and automated data extraction from clinic...

Evaluation of Large Language Models in Tailoring Educational Content for Cancer Survivors and Their Caregivers: Quality Analysis.

JMIR cancer
BACKGROUND: Cancer survivors and their caregivers, particularly those from disadvantaged backgrounds with limited health literacy or racial and ethnic minorities facing language barriers, are at a disproportionately higher risk of experiencing sympto...