Posts Tagged ‘LLM-NLP’
Unveiling the Future of Postoperative Outcomes Prediction: The Role of Machine Learning and Trust in Healthcare.
Link: https://doi.org/10.1007/s10916-024-02106-7 Authors: Hofer, Ira S; Wax, David B Abstract:
Read MoreAdvancing rheumatology with natural language processing: insights and prospects from a systematic review.
Link: https://doi.org/10.1093/rap/rkae120 Authors: Omar, Mahmud; Naffaa, Mohammad E; Glicksberg, Benjamin S; Reuveni, Hagar; Nadkarni, Girish N; Klang, Eyal Abstract: Natural language processing (NLP) and large language models (LLMs) have emerged as powerful tools in healthcare, offering advanced methods for analysing unstructured clinical texts. This systematic review aims to evaluate the current applications of NLP and…
Read MoreClosing the gap between open source and commercial large language models for medical evidence summarization.
Link: https://doi.org/10.1038/s41746-024-01239-w Authors: Zhang, Gongbo; Jin, Qiao; Zhou, Yiliang; Wang, Song; Idnay, Betina; Luo, Yiming; Park, Elizabeth; Nestor, Jordan G; Spotnitz, Matthew E; Soroush, Ali; Campion, Thomas R; Lu, Zhiyong; Weng, Chunhua; Peng, Yifan Abstract: Large language models (LLMs) hold great promise in summarizing medical evidence. Most recent studies focus on the application of proprietary…
Read MoreDerivation, external and clinical validation of a deep learning approach for detecting intracranial hypertension.
Link: https://doi.org/10.1038/s41746-024-01227-0 Authors: Gulamali, Faris; Jayaraman, Pushkala; Sawant, Ashwin S; Desman, Jacob; Fox, Benjamin; Chang, Annette; Soong, Brian Y; Arivazagan, Naveen; Reynolds, Alexandra S; Duong, Son Q; Vaid, Akhil; Kovatch, Patricia; Freeman, Robert; Hofer, Ira S; Sakhuja, Ankit; Dangayach, Neha S; Reich, David S; Charney, Alexander W; Nadkarni, Girish N Abstract: Increased intracranial pressure (ICP)…
Read MoreExploring the role of Large Language Models in haematology: A focused review of applications, benefits and limitations.
Link: https://doi.org/10.1111/bjh.19738 Authors: Mudrik, Aya; Nadkarni, Girish N; Efros, Orly; Glicksberg, Benjamin S; Klang, Eyal; Soffer, Shelly Abstract: Large language models (LLMs) have significantly impacted various fields with their ability to understand and generate human-like text. This study explores the potential benefits and limitations of integrating LLMs, such as ChatGPT, into haematology practices. Utilizing systematic…
Read MoreAssessing GPT-4 multimodal performance in radiological image analysis.
Link: https://doi.org/10.1007/s00330-024-11035-5 Authors: Brin, Dana; Sorin, Vera; Barash, Yiftach; Konen, Eli; Glicksberg, Benjamin S; Nadkarni, Girish N; Klang, Eyal Abstract: This study aims to assess the performance of a multimodal artificial intelligence (AI) model capable of analyzing both images and textual data (GPT-4V), in interpreting radiological images. It focuses on a range of modalities, anatomical…
Read MoreMultimodal fusion learning for long QT syndrome pathogenic genotypes in a racially diverse population.
Link: https://doi.org/10.1038/s41746-024-01218-1 Authors: Jiang, Joy; Thi Vy, Ha My; Charney, Alexander; Kovatch, Patricia; Reddy, Vivek; Jayaraman, Pushkala; Do, Ron; Khera, Rohan; Chugh, Sumeet; Bhatt, Deepak L; Vaid, Akhil; Lampert, Joshua; Nadkarni, Girish Nitin Abstract: Congenital long QT syndrome (LQTS) diagnosis is complicated by limited genetic testing at scale, low prevalence, and normal QT corrected interval…
Read MoreDistinguishing neonatal culture-negative sepsis from rule-out sepsis with artificial intelligence-derived graphs.
Link: https://doi.org/10.1038/s41390-024-03458-z Authors: Holmes, Emma; Kauffman, Justin; Juliano, Courtney; Duchon, Jennifer; Nadkarni, Girish N Abstract: Novel artificial intelligence methods can aide in identification of cases of conditions using only unstructured electronic health record data. This graph-based method compares comprehensive electronic health records among neonates using temporal data. This provides a scalable solution to distinguish culture…
Read MoreAdvancing radiology practice and research: harnessing the potential of large language models amidst imperfections.
Link: https://doi.org/10.1093/bjro/tzae022 Authors: Klang, Eyal; Alper, Lee; Sorin, Vera; Barash, Yiftach; Nadkarni, Girish N; Zimlichman, Eyal Abstract: Large language models (LLMs) are transforming the field of natural language processing (NLP). These models offer opportunities for radiologists to make a meaningful impact in their field. NLP is a part of artificial intelligence (AI) that uses computer…
Read MoreThe Role of Artificial Intelligence in Nephrology Clinical Trials.
Link: https://doi.org/10.1681/ASN.0000000000000486 Authors: Chan, Lili; Nadkarni, Girish N Abstract:
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