Detalhe da pesquisa
1.
Characterizing the limitations of using diagnosis codes in the context of machine learning for healthcare.
BMC Med Inform Decis Mak
; 24(1): 51, 2024 Feb 14.
Artigo
em Inglês
| MEDLINE | ID: mdl-38355486
2.
Detecting Developmental Delay and Autism Through Machine Learning Models Using Home Videos of Bangladeshi Children: Development and Validation Study.
J Med Internet Res
; 21(4): e13822, 2019 04 24.
Artigo
em Inglês
| MEDLINE | ID: mdl-31017583
3.
EHR foundation models improve robustness in the presence of temporal distribution shift.
Sci Rep
; 13(1): 3767, 2023 03 07.
Artigo
em Inglês
| MEDLINE | ID: mdl-36882576
4.
Evaluation of Feature Selection Methods for Preserving Machine Learning Performance in the Presence of Temporal Dataset Shift in Clinical Medicine.
Methods Inf Med
; 62(1-02): 60-70, 2023 05.
Artigo
em Inglês
| MEDLINE | ID: mdl-36812932
5.
Self-supervised machine learning using adult inpatient data produces effective models for pediatric clinical prediction tasks.
J Am Med Inform Assoc
; 30(12): 2004-2011, 2023 11 17.
Artigo
em Inglês
| MEDLINE | ID: mdl-37639620
6.
Performance of a Commonly Used Pressure Injury Risk Model Under Changing Incidence.
Jt Comm J Qual Patient Saf
; 48(3): 131-138, 2022 03.
Artigo
em Inglês
| MEDLINE | ID: mdl-34866024
7.
Systematic Review of Approaches to Preserve Machine Learning Performance in the Presence of Temporal Dataset Shift in Clinical Medicine.
Appl Clin Inform
; 12(4): 808-815, 2021 08.
Artigo
em Inglês
| MEDLINE | ID: mdl-34470057