Zobrazeno 1 - 10
of 27
pro vyhledávání: '"Benjamin Glicksberg"'
Autor:
Akhil Vaid, Joy Jiang, Ashwin Sawant, Stamatios Lerakis, Edgar Argulian, Yuri Ahuja, Joshua Lampert, Alexander Charney, Hayit Greenspan, Jagat Narula, Benjamin Glicksberg, Girish N Nadkarni
Publikováno v:
npj Digital Medicine, Vol 6, Iss 1, Pp 1-8 (2023)
Abstract The electrocardiogram (ECG) is a ubiquitous diagnostic modality. Convolutional neural networks (CNNs) applied towards ECG analysis require large sample sizes, and transfer learning approaches for biomedical problems may result in suboptimal
Externí odkaz:
https://doaj.org/article/91be2fa3a0f7494c9d9c088a378a693d
Autor:
Faris F. Gulamali, Ashwin S. Sawant, Patricia Kovatch, Benjamin Glicksberg, Alexander Charney, Girish N. Nadkarni, Eric Oermann
Publikováno v:
npj Digital Medicine, Vol 5, Iss 1, Pp 1-8 (2022)
Abstract Sample size estimation is a crucial step in experimental design but is understudied in the context of deep learning. Currently, estimating the quantity of labeled data needed to train a classifier to a desired performance, is largely based o
Externí odkaz:
https://doaj.org/article/58170488a06d42cbb95fa02c45949816
Publikováno v:
Diagnostics, Vol 13, Iss 11, p 1950 (2023)
Background and aims: Patients frequently have concerns about their disease and find it challenging to obtain accurate Information. OpenAI’s ChatGPT chatbot (ChatGPT) is a new large language model developed to provide answers to a wide range of ques
Externí odkaz:
https://doaj.org/article/743d94a9126441f18ed8f9c16f8b873e
Autor:
Joshua Lampert, Matthew Pulaski, Marc A. Miller, William Whang, Jacob Koruth, Benjamin Glicksberg, Samin Sharma, Srinivas R. Dukkipati, Valentin Fuster, Vivek Y. Reddy
Publikováno v:
Journal of the American College of Cardiology. 79:2467-2469
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a9beed29e712236f645d7f00257357c9
https://doi.org/10.1016/j.jacc.2022.04.012
https://doi.org/10.1016/j.jacc.2022.04.012
Autor:
Akhil Vaid, Ashwin Sawant, Mayte Suarez-Farinas, Juhee Lee, Sanjeev Kaul, Patricia Kovatch, Robert Freeman, Joy Jiang, Pushkala Jayaraman, Zahi Fayad, Edgar Argulian, Stamatios Lerakis, Alexander Charney, Fei Wang, Matthew Levin, Benjamin Glicksberg, Jagat Narula, Ira Hofer, Karandeep Singh, Girish N Nadkarni
BackgroundSubstantial effort has been directed towards demonstrating use cases of Artificial Intelligence in healthcare, yet limited evidence exists about the long-term viability and consequences of machine learning model deployment.MethodsWe use dat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::015ab90e0c016ce523860caa01356cc9
https://doi.org/10.1101/2022.11.17.22282440
https://doi.org/10.1101/2022.11.17.22282440
Autor:
Tingyi Wanyan, Mingquan Lin, Eyal Klang, Kartikeya M. Menon, Faris F. Gulamali, Ariful Azad, Yiye Zhang, Ying Ding, Zhangyang Wang, Fei Wang, Benjamin Glicksberg, Yifan Peng
Publikováno v:
ACM BCB
Clinical EHR data is naturally heterogeneous, where it contains abundant sub-phenotype. Such diversity creates challenges for outcome prediction using a machine learning model since it leads to high intra-class variance. To address this issue, we pro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::071a38f00cdca7ab93ba56efc4767dc8
https://europepmc.org/articles/PMC9365529/
https://europepmc.org/articles/PMC9365529/
Autor:
Ishan Paranjpe, Roy Lan, Suraj Jaladanki, Jagat Narula, Benjamin Glicksberg, Girish Nadkarni, Samir Kamat
Publikováno v:
Journal of the American College of Cardiology. 81:1685
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::403fab4fa624ce7ee7e7115143ef15c6
https://doi.org/10.1016/s0735-1097(23)02129-0
https://doi.org/10.1016/s0735-1097(23)02129-0
The standard of care for a physician to review laboratory tests results is to weigh each individual laboratory test result and compare it to against a standard reference range. Such a method of scanning can lead to missing high-level information. Dif
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d82422e2e564602169e8b0a194e1adfc
https://doi.org/10.3233/shti220441
https://doi.org/10.3233/shti220441
Publikováno v:
Studies in health technology and informatics. 294
The standard of care for a physician to review laboratory tests results is to weigh each individual laboratory test result and compare it to against a standard reference range. Such a method of scanning can lead to missing high-level information. Dif
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::92c13587c579ca07260351ebc0f17925
https://pubmed.ncbi.nlm.nih.gov/35612060
https://pubmed.ncbi.nlm.nih.gov/35612060
Autor:
Girish Nadkarni, Ishan Paranjpe, Pushkala Jayaraman, Chen-Yang Su, Sirui Zhou, Steven Chen, Diane Del Valle, Ryan Thompson, Ephraim Kenigsberg, Shan Zhao, Suraj Jaladanki, Kumardeep Chaudhary, Steven Ascolillo, Akhil Vaid, Edgar Gonzalez-Kozlova, Arvind Kumar, Manish Paranjpe, Ross O'Hagan, Samir Kamat, Faris Gulamali, Justin Kauffman, Hui Xie, Joceyln Harris, Manishkumar Patel, Kimberly Argueta, Craig Batchelor, Kai Nie, Sergio Dellepiane, Leisha Scott, Matthew Levin, John He, Mayte Suárez-Fariñas, Steven Coca, Lili Chan, Evren Azeloglu, Eric Schadt, Noam Beckmann, Sacha Gnjatic, Miriam Merad, Seunghee Kim-Schulze, J. Brent Richards, Benjamin Glicksberg, Alexander Charney
Background Acute kidney injury (AKI) is a known complication of COVID-19 and is associated with an increased risk of in-hospital mortality. Unbiased proteomics using biological specimens can lead to improved risk stratification and discover pathophys
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ca3faf191c85bd2e7504675ad30d7210
https://doi.org/10.1101/2021.12.09.21267548
https://doi.org/10.1101/2021.12.09.21267548