Posts Tagged ‘Machine Learning’
Evaluating the accuracy of a state-of-the-art large language model for prediction of admissions from the emergency room.
Link: https://doi.org/10.1093/jamia/ocae103 Authors: Glicksberg, Benjamin S; Timsina, Prem; Patel, Dhaval; Sawant, Ashwin; Vaid, Akhil; Raut, Ganesh; Charney, Alexander W; Apakama, Donald; Carr, Brendan G; Freeman, Robert; Nadkarni, Girish N; Klang, Eyal Abstract: Artificial intelligence (AI) and large language models (LLMs) can play a critical role in emergency room operations by augmenting decision-making about patient admission.…
Read MoreTransforming Cardiovascular Care With Artificial Intelligence: From Discovery to Practice: JACC State-of-the-Art Review.
Link: https://doi.org/S0735-1097(24)07195-X Authors: Khera, Rohan; Oikonomou, Evangelos K; Nadkarni, Girish N; Morley, Jessica R; Wiens, Jenna; Butte, Atul J; Topol, Eric J Abstract: Artificial intelligence (AI) has the potential to transform every facet of cardiovascular practice and research. The exponential rise in technology powered by AI is defining new frontiers in cardiovascular care, with innovations…
Read MoreExtracting social support and social isolation information from clinical psychiatry notes: comparing a rule-based natural language processing system and a large language model.
Link: https://doi.org/10.1093/jamia/ocae260 Authors: Patra, Braja Gopal; Lepow, Lauren A; Kasi Reddy Jagadeesh Kumar, Praneet; Vekaria, Veer; Sharma, Mohit Manoj; Adekkanattu, Prakash; Fennessy, Brian; Hynes, Gavin; Landi, Isotta; Sanchez-Ruiz, Jorge A; Ryu, Euijung; Biernacka, Joanna M; Nadkarni, Girish N; Talati, Ardesheer; Weissman, Myrna; Olfson, Mark; Mann, J John; Zhang, Yiye; Charney, Alexander W; Pathak, Jyotishman Abstract:…
Read MoreDeep Learning-Based Electrocardiogram Analysis Predicts Biventricular Dysfunction and Dilation in Congenital Heart Disease.
Link: https://doi.org/S0735-1097(24)07676-9 Authors: Mayourian, Joshua; Gearhart, Addison; La Cava, William G; Vaid, Akhil; Nadkarni, Girish N; Triedman, John K; Powell, Andrew J; Wald, Rachel M; Valente, Anne Marie; Geva, Tal; Duong, Son Q; Ghelani, Sunil J Abstract: Artificial intelligence-enhanced electrocardiogram (AI-ECG) analysis shows promise to detect biventricular pathophysiology. However, AI-ECG analysis remains underexplored in congenital…
Read MoreClinical factors associated with hospital mortality in critically ill adult COVID-19 patients with AKI requiring CRRT: A multicenter study.
Link: https://doi.org/10.5414/CN111404 Authors: Cama-Olivares, Augusto; Tamhane, Ashutosh; Ortiz-Soriano, Victor; Farrell, Douglas; Wen, Huei Hsun; Takeuchi, Tomonori; Devansh, Patel; Galasso, Francesco; Chen, Jin; Chan, Lili; Tolwani, Ashita J; Nadkarni, Girish N; Neyra, Javier A Abstract: Acute kidney injury (AKI) is a common complication of critically ill COVID-19 patients which is associated with adverse outcomes. We examined…
Read MoreArtificial intelligence-guided detection of under-recognised cardiomyopathies on point-of-care cardiac ultrasonography: a multicentre study.
Link: https://doi.org/S2589-7500(24)00249-8 Authors: Oikonomou, Evangelos K; Vaid, Akhil; Holste, Gregory; Coppi, Andreas; McNamara, Robert L; Baloescu, Cristiana; Krumholz, Harlan M; Wang, Zhangyang; Apakama, Donald J; Nadkarni, Girish N; Khera, Rohan Abstract: Point-of-care ultrasonography (POCUS) enables cardiac imaging at the bedside and in communities but is limited by abbreviated protocols and variation in quality. We aimed…
Read MoreNatural Language Processing Identifies Under-Documentation of Symptoms in Patients on Hemodialysis.
Link: https://doi.org/10.34067/KID.0000000694 Authors: Dai, Yang; Wen, Huei Hsun; Yang, Joanna; Gupta, Neepa; Rhee, Connie; Horowitz, Carol R; Mohottige, Dinushika; Nadkarni, Girish N; Coca, Steven; Chan, Lili Abstract: Patients on hemodialysis (HD) have a high burden of emotional and physical symptoms. These symptoms are often under-recognized. NLP can be used to identify patient symptoms from the…
Read MorePhysiological Data Collected From Wearable Devices Identify and Predict Inflammatory Bowel Disease Flares.
Link: https://doi.org/10.1053/j.gastro.2024.12.024 Authors: Hirten, Robert P; Danieletto, Matteo; Sanchez-Mayor, Milagros; Whang, Jessica K; Lee, Kyung Won; Landell, Kyle; Zweig, Micol; Helmus, Drew; Fuchs, Thomas J; Fayad, Zahi A; Nadkarni, Girish N; Keefer, Laurie; Suarez-Farinas, Mayte; Sands, Bruce E Abstract: Wearable devices capture physiological signals noninvasively and passively. Many of these parameters have been linked to…
Read MoreVisual-textual integration in LLMs for medical diagnosis: A preliminary quantitative analysis.
Link: https://doi.org/10.1016/j.csbj.2024.12.019 Authors: Agbareia, Reem; Omar, Mahmud; Soffer, Shelly; Glicksberg, Benjamin S; Nadkarni, Girish N; Klang, Eyal Abstract: Visual data from images is essential for many medical diagnoses. This study evaluates the performance of multimodal Large Language Models (LLMs) in integrating textual and visual information for diagnostic purposes. We tested GPT-4o and Claude Sonnet 3.5…
Read MoreA Natural Language Processing Pipeline based on the Columbia-Suicide Severity Rating Scale.
Link: https://doi.org/10.1101/2024.12.19.24319352 Authors: Lepow, Lauren A; Adekkanattu, Prakash; Cusick, Marika; Coon, Hilary; Fennessy, Brian; O’Connell, Shane; Pierce, Charlotte; Rabbany, Jessica; Sharma, Mohit; Olfson, Mark; Bakian, Amanda; Xiao, Yunyu; Mullins, Niamh; Nadkarni, Girish N; Charney, Alexander W; Pathak, Jyotishman; Mann, J John Abstract: Diagnostic codes in the Electronic Health Record (EHR) are known to be limited…
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