Posts by Amir Safavi
Automated Diagnostic Reports from Images of Electrocardiograms at the Point-of-Care.
Link: https://doi.org/10.1101/2024.02.17.24302976 Authors: Khunte, Akshay; Sangha, Veer; Oikonomou, Evangelos K; Dhingra, Lovedeep S; Aminorroaya, Arya; Coppi, Andreas; Shankar, Sumukh Vasisht; Mortazavi, Bobak J; Bhatt, Deepak L; Krumholz, Harlan M; Nadkarni, Girish N; Vaid, Akhil; Khera, Rohan Abstract: Timely and accurate assessment of electrocardiograms (ECGs) is crucial for diagnosing, triaging, and clinically managing patients. Current workflows…
Read MorePublication: Simulation – What Is the Impact of Predictive AI in the Health Care Setting?
Models built on machine learning in health care can be victims of their own success, according to researchers at the Icahn School of Medicine and the University of Michigan. Their study assessed the impact of implementing predictive models on the subsequent performance of those and other models. Their findings—that using the models to adjust how care is delivered…
Read MorePublication: Deep Learning Insights on RV Function from ECG
In a groundbreaking study published on 29 December 2023 in the Journal of the American Heart Association, AIMS researchers have unveiled a novel approach to assess right ventricular (RV) size and function using deep learning-enabled electrocardiogram (ECG) analysis. Traditionally, assessing metrics like right ventricular ejection fraction (RVEF) and end-diastolic volume (RVEDV) required advanced imaging techniques,…
Read MoreAssociations between Sperm Epigenetic Age and Semen Parameters: An Evaluation of Clinical and Non-Clinical Cohorts.
Link: https://doi.org/10.3390/cimb46020101 Authors: Sawant, Savni; Oluwayiose, Oladele A; Nowak, Karolina; Maxwell, DruAnne L; Houle, Emily; Paskavitz, Amanda L; Saddiki, Hachem; Bertolla, Ricardo P; Pilsner, J Richard Abstract:
Read MoreComparison of predicting cardiovascular disease hospitalization using individual, ZIP code-derived, and machine learning model-predicted educational attainment in New York City.
Link: https://doi.org/10.1371/journal.pone.0297919 Authors: Takkavatakarn, Kullaya; Dai, Yang; Hsun Wen, Huei; Kauffman, Justin; Charney, Alexander; Coca, Steven G; Nadkarni, Girish N; Chan, Lili Abstract: Area-level social determinants of health (SDOH) based on patients’ ZIP codes or census tracts have been commonly used in research instead of individual SDOHs. To our knowledge, whether machine learning (ML) could…
Read MorePediatric ECG-Based Deep Learning to Predict Left Ventricular Dysfunction and Remodeling.
Link: https://doi.org/10.1161/CIRCULATIONAHA.123.067750 Authors: Mayourian, Joshua; La Cava, William G; Vaid, Akhil; Nadkarni, Girish N; Ghelani, Sunil J; Mannix, Rebekah; Geva, Tal; Dionne, Audrey; Alexander, Mark E; Duong, Son Q; Triedman, John K Abstract: Artificial intelligence-enhanced ECG analysis shows promise to detect ventricular dysfunction and remodeling in adult populations. However, its application to pediatric populations remains…
Read MoreDerivation, External Validation and Clinical Implications of a deep learning approach for intracranial pressure estimation using non-cranial waveform measurements.
Link: https://doi.org/10.1101/2024.01.30.24301974 Authors: Gulamali, Faris; Jayaraman, Pushkala; Sawant, Ashwin S; Desman, Jacob; Fox, Benjamin; Chang, Annie; Soong, Brian Y; Arivazaghan, 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 MoreRemote Monitoring and Artificial Intelligence: Outlook for 2050.
Link: https://doi.org/10.1213/ANE.0000000000006712 Authors: Feinstein, Max; Katz, Daniel; Demaria, Samuel; Hofer, Ira S Abstract: Remote monitoring and artificial intelligence will become common and intertwined in anesthesiology by 2050. In the intraoperative period, technology will lead to the development of integrated monitoring systems that will integrate multiple data streams and allow anesthesiologists to track patients more effectively.…
Read MoreQuantitative Prediction of Right Ventricular Size and Function From the ECG.
Link: https://doi.org/10.1161/JAHA.123.031671 Authors: Duong, Son Q; Vaid, Akhil; My, Vy Thi Ha; Butler, Liam R; Lampert, Joshua; Pass, Robert H; Charney, Alexander W; Narula, Jagat; Khera, Rohan; Sakhuja, Ankit; Greenspan, Hayit; Gelb, Bruce D; Do, Ron; Nadkarni, Girish N Abstract: Right ventricular ejection fraction (RVEF) and end-diastolic volume (RVEDV) are not readily assessed through traditional…
Read MoreEvaluating the role of ChatGPT in gastroenterology: a comprehensive systematic review of applications, benefits, and limitations.
Link: https://doi.org/10.1177/17562848231218618 Authors: Klang, Eyal; Sourosh, Ali; Nadkarni, Girish N; Sharif, Kassem; Lahat, Adi Abstract: The integration of artificial intelligence (AI) into healthcare has opened new avenues for enhancing patient care and clinical research. In gastroenterology, the potential of AI tools, specifically large language models like ChatGPT, is being explored to understand their utility and…
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