Zobrazeno 1 - 10
of 207
pro vyhledávání: '"Kartoun, Uri"'
Autor:
Kwon, Bum Chul, Kartoun, Uri, Khurshid, Shaan, Yurochkin, Mikhail, Maity, Subha, Brockman, Deanna G, Khera, Amit V, Ellinor, Patrick T, Lubitz, Steven A, Ng, Kenney
Disease risk models can identify high-risk patients and help clinicians provide more personalized care. However, risk models developed on one dataset may not generalize across diverse subpopulations of patients in different datasets and may have unex
Externí odkaz:
http://arxiv.org/abs/2209.06378
Autor:
Kartoun, Uri
Electronic medical records (EMR) contain sensitive personal information. For example, they may include details about infectious diseases, such as human immunodeficiency virus (HIV), or they may contain information about a mental illness. They may als
Externí odkaz:
http://arxiv.org/abs/1608.00570
Autor:
Kartoun, Uri
The paper presents a time-series-based classification approach to identify similarities in pairs of simulated human-generated patterns. An example for a pattern is a time-series representing a heart rate during a specific time-range, wherein the time
Externí odkaz:
http://arxiv.org/abs/1306.0541
Autor:
Kartoun, Uri
The paper presents new machine learning methods: signal composition, which classifies time-series regardless of length, type, and quantity; and self-labeling, a supervised-learning enhancement. The paper describes further the implementation of the me
Externí odkaz:
http://arxiv.org/abs/1303.0283
Autor:
Kartoun, Uri
This paper describes a time-series-based classification approach to identify similarities between bio-medical-based situations. The proposed approach allows classifying collections of time-series representing bio-medical measurements, i.e., situation
Externí odkaz:
http://arxiv.org/abs/1303.0076
Autor:
Kartoun, Uri
The paper presents new machine learning methods: signal composition, which classifies time-series regardless of length, type, and quantity; and self-labeling, a supervised-learning enhancement. The paper describes further the implementation of the me
Externí odkaz:
http://arxiv.org/abs/1303.0073
Autor:
Jones, Tom, do Valle Miranda, Luiz, Cerf, Vinton G., Glass, Robert L., Larus, James, Schell, Roger, Vardi, Moshe Y., Kartoun, Uri, Balasubramanian, Vineeth N., Berry, Daniel, Kugler, Logan
Publikováno v:
Communications of the ACM; Feb2023, Vol. 66 Issue 2, p8-11, 4p
Autor:
Kartoun, Uri1 (AUTHOR), Khurshid, Shaan2,3 (AUTHOR), Kwon, Bum Chul1 (AUTHOR), Patel, Aniruddh P.2,4 (AUTHOR), Batra, Puneet5 (AUTHOR), Philippakis, Anthony2 (AUTHOR), Khera, Amit V.2,4 (AUTHOR), Ellinor, Patrick T.2,3 (AUTHOR), Lubitz, Steven A.2,3 (AUTHOR), Ng, Kenney1 (AUTHOR) kenney.ng@us.ibm.com
Publikováno v:
Scientific Reports. 8/19/2022, Vol. 12 Issue 1, p1-11. 11p.
Autor:
Ng, Kenney1 kenney.ng@us.ibm.com, Kartoun, Uri1, Stavropoulos, Harry1, Zambrano, John A.2, Tang, Paul C.3
Publikováno v:
Scientific Reports. 1/13/2021, Vol. 11 Issue 1, p1-13. 13p.
Autor:
Kartoun, Uri
Publikováno v:
Communications of the ACM. Jun2022, Vol. 65 Issue 6, p10-10. 1/3p.