Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Michaelia Banning"'
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:
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
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
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dfc3c783e16dabac11db4e2708a633be
https://pubmed.ncbi.nlm.nih.gov/35019849
https://pubmed.ncbi.nlm.nih.gov/35019849
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:
Chloe Pou-Prom, Kamalprit Chokar, Sharmistha Mishra, Michael Guerzhoy, Shaun Mathew, Michaelia Banning, Ujash Joshi, Christine Wang, Victoria Pequegnat, Muhammad Mamdani, David Dai, Joshua Murray, Ahmed Abdelbasit, Jane Batt, David Landsman
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://explore.openaire.eu/search/publication?articleId=doi_________::494be0c12080522333ff20cbf64fff23
https://doi.org/10.1101/2020.09.11.20192419
https://doi.org/10.1101/2020.09.11.20192419
Autor:
Sharmistha Mishra, David Dai, Ujash Joshi, Joshua Murray, Chloe Pou-Prom, Jane Batt, Kamalprit Chokar, Michaelia Banning, Shaun Mathew, Victoria Pequegnat, David Landsman, Muhammad Mamdani, Michael Guerzhoy, Ahmed Abdelbasit, Christine Wang
Publikováno v:
PLoS ONE
PLoS ONE, Vol 16, Iss 3, p e0247872 (2021)
PLoS ONE, Vol 16, Iss 3, p e0247872 (2021)
Background Tuberculosis (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. Th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1c6d3597eebe478de631e65eab0e62ca
https://pubmed.ncbi.nlm.nih.gov/33657184
https://pubmed.ncbi.nlm.nih.gov/33657184