Posts Tagged ‘LLM-NLP’
A strategy for cost-effective large language model use at health system-scale.
Link: https://doi.org/10.1038/s41746-024-01315-1 Authors: Klang, Eyal; Apakama, Donald; Abbott, Ethan E; Vaid, Akhil; Lampert, Joshua; Sakhuja, Ankit; Freeman, Robert; Charney, Alexander W; Reich, David; Kraft, Monica; Nadkarni, Girish N; Glicksberg, Benjamin S Abstract: Large language models (LLMs) can optimize clinical workflows; however, the economic and computational challenges of their utilization at the health system scale are…
Read MoreDisagreements in Medical Ethics Question Answering Between Large Language Models and Physicians.
Link: https://doi.org/10.21203/rs.3.rs-5382879/v1 Authors: Soffer, Shelly; Nesselroth, Dafna; Pragier, Keren; Anteby, Roi; Apakama, Donald; Holmes, Emma; Sawant, Ashwin Shreekant; Abbott, Ethan; Lepow, Lauren Alyse; Vasudev, Ishita; Lampert, Joshua; Gendler, Moran; Horesh, Nir; Efros, Orly; Glicksberg, Benjamin S; Freeman, Robert; Reich, David L; Charney, Alexander W; Nadkarni, Girish N; Klang, Eyal Abstract: Medical ethics is inherently complex,…
Read MoreDetection of neurologic changes in critically ill infants using deep learning on video data: a retrospective single center cohort study.
Link: https://doi.org/10.1016/j.eclinm.2024.102919 Authors: Gleason, Alec; Richter, Florian; Beller, Nathalia; Arivazhagan, Naveen; Feng, Rui; Holmes, Emma; Glicksberg, Benjamin S; Morton, Sarah U; La Vega-Talbott, Maite; Fields, Madeline; Guttmann, Katherine; Nadkarni, Girish N; Richter, Felix Abstract: Infant alertness and neurologic changes can reflect life-threatening pathology but are assessed by physical exam, which can be intermittent and subjective.…
Read MoreLeveraging Artificial Intelligence and Data Science for Integration of Social Determinants of Health in Emergency Medicine: Scoping Review.
Link: https://doi.org/10.2196/57124 Authors: Abbott, Ethan E; Apakama, Donald; Richardson, Lynne D; Chan, Lili; Nadkarni, Girish N Abstract: Social determinants of health (SDOH) are critical drivers of health disparities and patient outcomes. However, accessing and collecting patient-level SDOH data can be operationally challenging in the emergency department (ED) clinical setting, requiring innovative approaches. This scoping review…
Read MoreApplications of ChatGPT in Heart Failure Prevention, Diagnosis, Management, and Research: A Narrative Review.
Link: https://doi.org/10.3390/diagnostics14212393 Authors: Ghanta, Sai Nikhila; Al’Aref, Subhi J; Lala-Trinidade, Anuradha; Nadkarni, Girish N; Ganatra, Sarju; Dani, Sourbha S; Mehta, Jawahar L Abstract: Heart failure (HF) is a leading cause of mortality, morbidity, and financial burden worldwide. The emergence of advanced artificial intelligence (AI) technologies, particularly Generative Pre-trained Transformer (GPT) systems, presents new opportunities to…
Read MoreAutomated Identification of Heart Failure With Reduced Ejection Fraction Using Deep Learning-Based Natural Language Processing.
Link: https://doi.org/S2213-1779(24)00618-8 Authors: Nargesi, Arash A; Adejumo, Philip; Dhingra, Lovedeep Singh; Rosand, Benjamin; Hengartner, Astrid; Coppi, Andreas; Benigeri, Simon; Sen, Sounok; Ahmad, Tariq; Nadkarni, Girish N; Lin, Zhenqiu; Ahmad, Faraz S; Krumholz, Harlan M; Khera, Rohan Abstract: The lack of automated tools for measuring care quality limits the implementation of a national program to assess…
Read MoreAdvancing Clinical Practice: The Potential of Multimodal Technology in Modern Medicine.
Link: https://doi.org/10.3390/jcm13206246 Authors: Artsi, Yaara; Sorin, Vera; Glicksberg, Benjamin S; Nadkarni, Girish N; Klang, Eyal Abstract: Multimodal technology is poised to revolutionize clinical practice by integrating artificial intelligence with traditional diagnostic modalities. This evolution traces its roots from Hippocrates’ humoral theory to the use of sophisticated AI-driven platforms that synthesize data across multiple sensory channels.…
Read MoreAssessing Retrieval-Augmented Large Language Model Performance in Emergency Department ICD-10-CM Coding Compared to Human Coders.
Link: https://doi.org/10.1101/2024.10.15.24315526 Authors: Klang, Eyal; Tessler, Idit; Apakama, Donald U; Abbott, Ethan; Glicksberg, Benjamin S; Arnold, Monique; Moses, Akini; Sakhuja, Ankit; Soroush, Ali; Charney, Alexander W; Reich, David L; McGreevy, Jolion; Gavin, Nicholas; Carr, Brendan; Freeman, Robert; Nadkarni, Girish N Abstract: Accurate medical coding is essential for clinical and administrative purposes but complicated, time-consuming, and…
Read MoreAutomated Transformation of Unstructured Cardiovascular Diagnostic Reports into Structured Datasets Using Sequentially Deployed Large Language Models.
Link: https://doi.org/10.1101/2024.10.08.24315035 Authors: Shankar, Sumukh Vasisht; Dhingra, Lovedeep S; Aminorroaya, Arya; Adejumo, Philip; Nadkarni, Girish N; Xu, Hua; Brandt, Cynthia; Oikonomou, Evangelos K; Pedroso, Aline F; Khera, Rohan Abstract: Rich data in cardiovascular diagnostic testing are often sequestered in unstructured reports, with the necessity of manual abstraction limiting their use in real-time applications in patient…
Read MoreA foundation model for clinician-centered drug repurposing.
Link: https://doi.org/10.1038/s41591-024-03233-x Authors: Huang, Kexin; Chandak, Payal; Wang, Qianwen; Havaldar, Shreyas; Vaid, Akhil; Leskovec, Jure; Nadkarni, Girish N; Glicksberg, Benjamin S; Gehlenborg, Nils; Zitnik, Marinka Abstract: Drug repurposing-identifying new therapeutic uses for approved drugs-is often a serendipitous and opportunistic endeavour to expand the use of drugs for new diseases. The clinical utility of drug-repurposing artificial…
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