Zobrazeno 1 - 10
of 22
pro vyhledávání: '"Lin Lawrence Guo"'
Autor:
Lin Lawrence Guo, Jason Fries, Ethan Steinberg, Scott Lanyon Fleming, Keith Morse, Catherine Aftandilian, Jose Posada, Nigam Shah, Lillian Sung
Publikováno v:
npj Digital Medicine, Vol 7, Iss 1, Pp 1-9 (2024)
Abstract Foundation models are transforming artificial intelligence (AI) in healthcare by providing modular components adaptable for various downstream tasks, making AI development more scalable and cost-effective. Foundation models for structured el
Externí odkaz:
https://doaj.org/article/bc024ab4b59f443d94c32dab6a226ca1
Autor:
Lin Lawrence Guo, Keith E. Morse, Catherine Aftandilian, Ethan Steinberg, Jason Fries, Jose Posada, Scott Lanyon Fleming, Joshua Lemmon, Karim Jessa, Nigam Shah, Lillian Sung
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 24, Iss 1, Pp 1-9 (2024)
Abstract Background Diagnostic codes are commonly used as inputs for clinical prediction models, to create labels for prediction tasks, and to identify cohorts for multicenter network studies. However, the coverage rates of diagnostic codes and their
Externí odkaz:
https://doaj.org/article/947161b3afdd48b8b6bd5931600923ac
Autor:
Lin Lawrence Guo, Ethan Steinberg, Scott Lanyon Fleming, Jose Posada, Joshua Lemmon, Stephen R. Pfohl, Nigam Shah, Jason Fries, Lillian Sung
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-11 (2023)
Abstract Temporal distribution shift negatively impacts the performance of clinical prediction models over time. Pretraining foundation models using self-supervised learning on electronic health records (EHR) may be effective in acquiring informative
Externí odkaz:
https://doaj.org/article/9e28a0f17b57475b806f0414f5e07a6e
Autor:
Lin Lawrence Guo, Maryann Calligan, Emily Vettese, Sadie Cook, George Gagnidze, Oscar Han, Jiro Inoue, Joshua Lemmon, Johnson Li, Medhat Roshdi, Bohdan Sadovy, Steven Wallace, Lillian Sung
Publikováno v:
Heliyon, Vol 9, Iss 11, Pp e21586- (2023)
Objectives: To describe the processes developed by The Hospital for Sick Children (SickKids) to enable utilization of electronic health record (EHR) data by creating sequentially transformed schemas for use across multiple user types. Methods: We use
Externí odkaz:
https://doaj.org/article/22dcf145eb9b4594ba52fc879c37547e
Autor:
Lin Lawrence Guo, Stephen R. Pfohl, Jason Fries, Alistair E. W. Johnson, Jose Posada, Catherine Aftandilian, Nigam Shah, Lillian Sung
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-10 (2022)
Abstract Temporal dataset shift associated with changes in healthcare over time is a barrier to deploying machine learning-based clinical decision support systems. Algorithms that learn robust models by estimating invariant properties across time per
Externí odkaz:
https://doaj.org/article/d2a984b41a95432ca8ec87e3d320e5f3
Autor:
Natasha Alexander, Catherine Aftandilian, Lin Lawrence Guo, Erin Plenert, Jose Posada, Jason Fries, Scott Fleming, Alistair Johnson, Nigam Shah, Lillian Sung
Publikováno v:
JMIR Medical Informatics, Vol 10, Iss 11, p e40039 (2022)
BackgroundGiven the costs of machine learning implementation, a systematic approach to prioritizing which models to implement into clinical practice may be valuable. ObjectiveThe primary objective was to determine the health care attributes responde
Externí odkaz:
https://doaj.org/article/998f128604214af7a46aefc962345d02
Autor:
Annabel Wing-Yan Fan, Lin Lawrence Guo, Adam Frost, Robert L. Whitwell, Matthias Niemeier, Jonathan S. Cant
Publikováno v:
Frontiers in Psychology, Vol 12 (2021)
The visual system is known to extract summary representations of visually similar objects which bias the perception of individual objects toward the ensemble average. Although vision plays a large role in guiding action, less is known about whether e
Externí odkaz:
https://doaj.org/article/ad87eecff76e466dad194af1471a635d
Publikováno v:
Frontiers in Human Neuroscience, Vol 13 (2019)
Central to the mechanistic understanding of the human mind is to clarify how cognitive functions arise from simpler sensory and motor functions. A longstanding assumption is that forward models used by sensorimotor control to anticipate actions also
Externí odkaz:
https://doaj.org/article/afd9b1f99aeb4211afeb4ce0e781d835
Autor:
Joshua Lemmon, Lin Lawrence Guo, Jose Posada, Stephen R. Pfohl, Jason Fries, Scott Lanyon Fleming, Catherine Aftandilian, Nigam Shah, Lillian Sung
Publikováno v:
Methods of Information in Medicine. 62:060-070
Background Temporal dataset shift can cause degradation in model performance as discrepancies between training and deployment data grow over time. The primary objective was to determine whether parsimonious models produced by specific feature selecti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::30d798913cbfa120e695d5c5de02e475
https://doi.org/10.1055/s-0043-1762904
https://doi.org/10.1055/s-0043-1762904
Autor:
Lin Lawrence Guo, Keith E. Morse, Catherine Aftandilian, Ethan Steinberg, Jason Fries, Jose Posada, Scott Lanyon Fleming, Joshua Lemmon, Karim Jessa, Nigam Shah, Lillian Sung
ImportanceDiagnostic codes are commonly used as inputs for clinical prediction models, to create labels for prediction tasks, and to identify cohorts for multicenter network studies. However, the coverage rates of diagnostic codes and their variabili
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::14c901731a963d8314a18f6f59f1e7b2
https://doi.org/10.1101/2023.03.14.23287202
https://doi.org/10.1101/2023.03.14.23287202
