Works matching IS 10675027 AND DT 2024 AND VI 31 AND IP 9
Results: 39
Large language models in biomedicine and health: current research landscape and future directions.
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- Journal of the American Medical Informatics Association, 2024, v. 31, n. 9, p. 1801, doi. 10.1093/jamia/ocae202
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The potential and pitfalls of using a large language model such as ChatGPT, GPT-4, or LLaMA as a clinical assistant.
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- Journal of the American Medical Informatics Association, 2024, v. 31, n. 9, p. 1884, doi. 10.1093/jamia/ocae184
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A question-answering framework for automated abstract screening using large language models.
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- Journal of the American Medical Informatics Association, 2024, v. 31, n. 9, p. 1939, doi. 10.1093/jamia/ocae166
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Public comfort with the use of ChatGPT and expectations for healthcare.
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- Journal of the American Medical Informatics Association, 2024, v. 31, n. 9, p. 1976, doi. 10.1093/jamia/ocae164
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Disambiguation of acronyms in clinical narratives with large language models.
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- Journal of the American Medical Informatics Association, 2024, v. 31, n. 9, p. 2040, doi. 10.1093/jamia/ocae157
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LEAP: LLM instruction-example adaptive prompting framework for biomedical relation extraction.
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- Journal of the American Medical Informatics Association, 2024, v. 31, n. 9, p. 2010, doi. 10.1093/jamia/ocae147
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A publishing infrastructure for Artificial Intelligence (AI)-assisted academic authoring.
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- Journal of the American Medical Informatics Association, 2024, v. 31, n. 9, p. 2103, doi. 10.1093/jamia/ocae139
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Fine-tuning large language models for rare disease concept normalization.
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- Journal of the American Medical Informatics Association, 2024, v. 31, n. 9, p. 2076, doi. 10.1093/jamia/ocae133
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Reasoning with large language models for medical question answering.
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- Journal of the American Medical Informatics Association, 2024, v. 31, n. 9, p. 1964, doi. 10.1093/jamia/ocae131
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RefAI: a GPT-powered retrieval-augmented generative tool for biomedical literature recommendation and summarization.
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- Journal of the American Medical Informatics Association, 2024, v. 31, n. 9, p. 2030, doi. 10.1093/jamia/ocae129
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BioInstruct: instruction tuning of large language models for biomedical natural language processing.
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- Journal of the American Medical Informatics Association, 2024, v. 31, n. 9, p. 1821, doi. 10.1093/jamia/ocae122
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Impact of high-quality, mixed-domain data on the performance of medical language models.
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- Journal of the American Medical Informatics Association, 2024, v. 31, n. 9, p. 1875, doi. 10.1093/jamia/ocae120
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Evaluation of GPT-4 ability to identify and generate patient instructions for actionable incidental radiology findings.
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- Journal of the American Medical Informatics Association, 2024, v. 31, n. 9, p. 1983, doi. 10.1093/jamia/ocae117
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An example of leveraging AI for documentation: ChatGPT-generated nursing care plan for an older adult with lung cancer.
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- Journal of the American Medical Informatics Association, 2024, v. 31, n. 9, p. 2089, doi. 10.1093/jamia/ocae116
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CoRTEx: contrastive learning for representing terms via explanations with applications on constructing biomedical knowledge graphs.
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- Journal of the American Medical Informatics Association, 2024, v. 31, n. 9, p. 1912, doi. 10.1093/jamia/ocae115
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Knowledge-guided generative artificial intelligence for automated taxonomy learning from drug labels.
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- Journal of the American Medical Informatics Association, 2024, v. 31, n. 9, p. 2065, doi. 10.1093/jamia/ocae105
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Evaluating the accuracy of a state-of-the-art large language model for prediction of admissions from the emergency room.
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- Journal of the American Medical Informatics Association, 2024, v. 31, n. 9, p. 1921, doi. 10.1093/jamia/ocae103
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RT: a Retrieving and Chain-of-Thought framework for few-shot medical named entity recognition.
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- Journal of the American Medical Informatics Association, 2024, v. 31, n. 9, p. 1929, doi. 10.1093/jamia/ocae095
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The first step is the hardest: pitfalls of representing and tokenizing temporal data for large language models.
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- Journal of the American Medical Informatics Association, 2024, v. 31, n. 9, p. 2151, doi. 10.1093/jamia/ocae090
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Lingdan: enhancing encoding of traditional Chinese medicine knowledge for clinical reasoning tasks with large language models.
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- Journal of the American Medical Informatics Association, 2024, v. 31, n. 9, p. 2019, doi. 10.1093/jamia/ocae087
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Mixed methods assessment of the influence of demographics on medical advice of ChatGPT.
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- Journal of the American Medical Informatics Association, 2024, v. 31, n. 9, p. 2002, doi. 10.1093/jamia/ocae086
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Local large language models for privacy-preserving accelerated review of historic echocardiogram reports.
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- Journal of the American Medical Informatics Association, 2024, v. 31, n. 9, p. 2097, doi. 10.1093/jamia/ocae085
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Large language models leverage external knowledge to extend clinical insight beyond language boundaries.
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- Journal of the American Medical Informatics Association, 2024, v. 31, n. 9, p. 2054, doi. 10.1093/jamia/ocae079
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The potential and limitations of large language models in identification of the states of motivations for facilitating health behavior change.
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- Journal of the American Medical Informatics Association, 2024, v. 31, n. 9, p. 2047, doi. 10.1093/jamia/ocae057
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Large language models for biomedicine: foundations, opportunities, challenges, and best practices.
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- Journal of the American Medical Informatics Association, 2024, v. 31, n. 9, p. 2114, doi. 10.1093/jamia/ocae074
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Distilling large language models for matching patients to clinical trials.
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- Journal of the American Medical Informatics Association, 2024, v. 31, n. 9, p. 1953, doi. 10.1093/jamia/ocae073
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Large language models facilitate the generation of electronic health record phenotyping algorithms.
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- Journal of the American Medical Informatics Association, 2024, v. 31, n. 9, p. 1994, doi. 10.1093/jamia/ocae072
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Ensemble pretrained language models to extract biomedical knowledge from literature.
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- Journal of the American Medical Informatics Association, 2024, v. 31, n. 9, p. 1904, doi. 10.1093/jamia/ocae061
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Generative large language models are all-purpose text analytics engines: text-to-text learning is all your need.
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- Journal of the American Medical Informatics Association, 2024, v. 31, n. 9, p. 1892, doi. 10.1093/jamia/ocae078
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Leveraging large language models to foster equity in healthcare.
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- Journal of the American Medical Informatics Association, 2024, v. 31, n. 9, p. 2147, doi. 10.1093/jamia/ocae055
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BioLORD-2023: semantic textual representations fusing large language models and clinical knowledge graph insights.
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- Journal of the American Medical Informatics Association, 2024, v. 31, n. 9, p. 1844, doi. 10.1093/jamia/ocae029
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PMC-LLaMA: toward building open-source language models for medicine.
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- Journal of the American Medical Informatics Association, 2024, v. 31, n. 9, p. 1833, doi. 10.1093/jamia/ocae045
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Taiyi: a bilingual fine-tuned large language model for diverse biomedical tasks.
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- Journal of the American Medical Informatics Association, 2024, v. 31, n. 9, p. 1865, doi. 10.1093/jamia/ocae037
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Large language models and generative AI in telehealth: a responsible use lens.
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- Journal of the American Medical Informatics Association, 2024, v. 31, n. 9, p. 2125, doi. 10.1093/jamia/ocae035
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Clinical risk prediction using language models: benefits and considerations.
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- Journal of the American Medical Informatics Association, 2024, v. 31, n. 9, p. 1856, doi. 10.1093/jamia/ocae030
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A comparative analysis of Spanish Clinical encoder-based models on NER and classification tasks.
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- Journal of the American Medical Informatics Association, 2024, v. 31, n. 9, p. 2137, doi. 10.1093/jamia/ocae054
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Search still matters: information retrieval in the era of generative AI.
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- Journal of the American Medical Informatics Association, 2024, v. 31, n. 9, p. 2159, doi. 10.1093/jamia/ocae014
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Improving large language models for clinical named entity recognition via prompt engineering.
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- Journal of the American Medical Informatics Association, 2024, v. 31, n. 9, p. 1812, doi. 10.1093/jamia/ocad259
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Benchmarking the symptom-checking capabilities of ChatGPT for a broad range of diseases.
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- Journal of the American Medical Informatics Association, 2024, v. 31, n. 9, p. 2084, doi. 10.1093/jamia/ocad245
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