Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Chloé Pou-Prom"'
Publikováno v:
Frontiers in Digital Health, Vol 4 (2022)
BackgroundDeploying safe and effective machine learning models is essential to realize the promise of artificial intelligence for improved healthcare. Yet, there remains a large gap between the number of high-performing ML models trained on healthcar
Externí odkaz:
https://doaj.org/article/8d512c5c97d54ae2aa57668fcf552d6d
Autor:
Zhen Yang, Chloé Pou-Prom, Ashley Jones, Michaelia Banning, David Dai, Muhammad Mamdani, Jiwon Oh, Tony Antoniou
Publikováno v:
JMIR Medical Informatics, Vol 10, Iss 1, p e25157 (2022)
BackgroundThe Expanded Disability Status Scale (EDSS) score is a widely used measure to monitor disability progression in people with multiple sclerosis (MS). However, extracting and deriving the EDSS score from unstructured electronic health records
Externí odkaz:
https://doaj.org/article/1945cf14b23e4357a61b5491f1a5a8ac
Autor:
Majid Komeili, Chloé Pou-Prom, Daniyal Liaqat, Kathleen C Fraser, Maria Yancheva, Frank Rudzicz
Publikováno v:
PLoS ONE, Vol 14, Iss 3, p e0212342 (2019)
Language is one the earliest capacities affected by cognitive change. To monitor that change longitudinally, we have developed a web portal for remote linguistic data acquisition, called Talk2Me, consisting of a variety of tasks. In order to facilita
Externí odkaz:
https://doaj.org/article/1cd1645ea6864ff3bd1178feb89db318
Autor:
Zhen Yang, Chloé Pou-Prom, Ashley Jones, Michaelia Banning, David Dai, Muhammad Mamdani, Jiwon Oh, Tony Antoniou
Publikováno v:
JMIR Medical Informatics
Background The Expanded Disability Status Scale (EDSS) score is a widely used measure to monitor disability progression in people with multiple sclerosis (MS). However, extracting and deriving the EDSS score from unstructured electronic health record
Autor:
Zhen Yang, Chloé Pou-Prom, Ashley Jones, Michaelia Banning, David Dai, Muhammad Mamdani, Jiwon Oh, Tony Antoniou
BACKGROUND The Expanded Disability Status Scale (EDSS) score is a widely used measure to monitor disability progression in people with multiple sclerosis (MS). However, extracting and deriving the EDSS score from unstructured electronic health record
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0a9717407150870c2244572bb8fb02c4
https://doi.org/10.2196/preprints.25157
https://doi.org/10.2196/preprints.25157
Autor:
Amol A. Verma, MD, Chloe Pou-Prom, MSc, Liam G. McCoy, MD, Joshua Murray, MSc, Bret Nestor, MEng, Shirley Bell, RN, Ophyr Mourad, MD, Michael Fralick, MD, Jan Friedrich, MD, Marzyeh Ghassemi, PhD, Muhammad Mamdani, PharmD
Publikováno v:
Critical Care Explorations, Vol 5, Iss 5, p e0897 (2023)
OBJECTIVES:. Hospital early warning systems that use machine learning (ML) to predict clinical deterioration are increasingly being used to aid clinical decision-making. However, it is not known how ML predictions complement physician and nurse judgm
Externí odkaz:
https://doaj.org/article/5a8049e87e9e40dd9f8282dd3a27b9d8
Autor:
David Landsman, Ahmed Abdelbasit, Christine Wang, Michael Guerzhoy, Ujash Joshi, Shaun Mathew, Chloe Pou-Prom, David Dai, Victoria Pequegnat, Joshua Murray, Kamalprit Chokar, Michaelia Banning, Muhammad Mamdani, Sharmistha Mishra, Jane Batt
Publikováno v:
PLoS ONE, Vol 16, Iss 3, p e0247872 (2021)
BackgroundTuberculosis (TB) is a major cause of death worldwide. TB research draws heavily on clinical cohorts which can be generated using electronic health records (EHR), but granular information extracted from unstructured EHR data is limited. The
Externí odkaz:
https://doaj.org/article/87153f6088b946ef99eb4e7260255090