Zobrazeno 1 - 10
of 143
pro vyhledávání: '"Shamim Nemati"'
Autor:
Supreeth P. Shashikumar, PhD, Joshua Pei Le, BS, Nathan Yung, MD, James Ford, MD, Karandeep Singh, MD, Atul Malhotra, MD, Shamim Nemati, PhD, Gabriel Wardi, MD, MPH
Publikováno v:
Critical Care Explorations, Vol 6, Iss 9, p e1151 (2024)
BACKGROUND:. Prediction-based strategies for physiologic deterioration offer the potential for earlier clinical interventions that improve patient outcomes. Current strategies are limited because they operate on inconsistent definitions of deteriorat
Externí odkaz:
https://doaj.org/article/20cbc77e294f4956be116b05c39411d6
Autor:
Fatemeh Amrollahi, MS, Brent D. Kennis, BS, Supreeth Prajwal Shashikumar, PhD, Atul Malhotra, MD, Stephanie Parks Taylor, MD, MSc, James Ford, MD, Arianna Rodriguez, MD, Julia Weston, MD, Romir Maheshwary, MD, Shamim Nemati, PhD, Gabriel Wardi, MD, Angela Meier, MD, PhD
Publikováno v:
Critical Care Explorations, Vol 6, Iss 6, p e1099 (2024)
OBJECTIVES:. To determine the predictive value of social determinants of health (SDoH) variables on 30-day readmission following a sepsis hospitalization as compared with traditional clinical variables. DESIGN:. Multicenter retrospective cohort study
Externí odkaz:
https://doaj.org/article/adfa8aeb65424962b20c352a9a6a3e5c
Autor:
Sai Ashish Somayajula, Onkar Litake, Youwei Liang, Ramtin Hosseini, Shamim Nemati, David O. Wilson, Robert N. Weinreb, Atul Malhotra, Pengtao Xie
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-14 (2024)
Abstract The emergence of long COVID during the ongoing COVID-19 pandemic has presented considerable challenges for healthcare professionals and researchers. The task of identifying relevant literature is particularly daunting due to the rapidly evol
Externí odkaz:
https://doaj.org/article/3e3d4401510b48a197641f6d03d25e47
Autor:
Aaron Boussina, Supreeth P. Shashikumar, Atul Malhotra, Robert L. Owens, Robert El-Kareh, Christopher A. Longhurst, Kimberly Quintero, Allison Donahue, Theodore C. Chan, Shamim Nemati, Gabriel Wardi
Publikováno v:
npj Digital Medicine, Vol 7, Iss 1, Pp 1-9 (2024)
Abstract Sepsis remains a major cause of mortality and morbidity worldwide. Algorithms that assist with the early recognition of sepsis may improve outcomes, but relatively few studies have examined their impact on real-world patient outcomes. Our ob
Externí odkaz:
https://doaj.org/article/b461fc4226524012bf4fd58623c0aec8
Author Correction: Impact of a deep learning sepsis prediction model on quality of care and survival
Autor:
Aaron Boussina, Supreeth P. Shashikumar, Atul Malhotra, Robert L. Owens, Robert El-Kareh, Christopher A. Longhurst, Kimberly Quintero, Allison Donahue, Theodore C. Chan, Shamim Nemati, Gabriel Wardi
Publikováno v:
npj Digital Medicine, Vol 7, Iss 1, Pp 1-1 (2024)
Externí odkaz:
https://doaj.org/article/0b6e37246e354952898b6bcdf7917272
Autor:
Aaron Boussina, Gabriel Wardi, Supreeth Prajwal Shashikumar, Atul Malhotra, Kai Zheng, Shamim Nemati
Publikováno v:
Journal of Medical Internet Research, Vol 25, p e45614 (2023)
BackgroundRecent attempts at clinical phenotyping for sepsis have shown promise in identifying groups of patients with distinct treatment responses. Nonetheless, the replicability and actionability of these phenotypes remain an issue because the pati
Externí odkaz:
https://doaj.org/article/c960db3151cd40aca34c2c1d6bc34ce6
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-6 (2022)
Abstract Kawasaki disease (KD), the most common cause of acquired heart disease in children, can be easily missed as it shares clinical findings with other pediatric illnesses, leading to risk of myocardial infarction or death. KD remains a clinical
Externí odkaz:
https://doaj.org/article/83912bc023a142d6ae435126922460aa
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-10 (2022)
Abstract The inherent flexibility of machine learning-based clinical predictive models to learn from episodes of patient care at a new institution (site-specific training) comes at the cost of performance degradation when applied to external patient
Externí odkaz:
https://doaj.org/article/c59cdcd86ec045bf987e6d9a72603fa5
Autor:
Parker Rogers, Aaron E Boussina, Supreeth P Shashikumar, Gabriel Wardi, Christopher A Longhurst, Shamim Nemati
Publikováno v:
Journal of Medical Internet Research, Vol 25, p e43486 (2023)
BackgroundSepsis costs and incidence vary dramatically across diagnostic categories, warranting a customized approach for implementing predictive models. ObjectiveThe aim of this study was to optimize the parameters of a sepsis prediction model with
Externí odkaz:
https://doaj.org/article/a794160af61549aca05d58bdf61248aa
Autor:
Eric Mlodzinski, Gabriel Wardi, Clare Viglione, Shamim Nemati, Laura Crotty Alexander, Atul Malhotra
Publikováno v:
JMIR Perioperative Medicine, Vol 6, p e41056 (2023)
BackgroundAlthough there is considerable interest in machine learning (ML) and artificial intelligence (AI) in critical care, the implementation of effective algorithms into practice has been limited. ObjectiveWe sought to understand physician persp
Externí odkaz:
https://doaj.org/article/e145ad8ccdcb481fa17b8f2c02010466