F. Liao
7 Papers
F. Liao is an academic researcher. The author has contributed to research in topics: Computer science & Medicine. The author has an hindex of 2, co-authored 6 publications.
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Papers
Governance of Clinical AI applications to facilitate safe and equitable deployment in a large health system: Key elements and early successes
TL;DR: This case study describes the development of a governance structure at University of Wisconsin Health that provides oversight of AI applications from assessment of validity and user acceptability through safe deployment with continuous monitoring for effectiveness.
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Deployment of Real-time Natural Language Processing and Deep Learning Clinical Decision Support in the Electronic Health Record: Pipeline Implementation for an Opioid Misuse Screener in Hospitalized Adults
Majid Afshar,Sabrina A. Adelaine,Felice Resnik,Marlon P. Mundt,John J. Long,Margaret Leaf,T. Ampian,B. Schnapp,M. Chao,Cara Joyce,Brihat Sharma,Dmitriy Dligach,Elizabeth S. Burnside,Matthew M. Churpek,Brian W. Patterson,F. Liao +15 more
TL;DR: In this article , a real-time NLP-driven clinical decision support (CDS) tool was proposed for electronic health records (EHRs) using a convolutional neural network (CNN).
Operationalizing a real-time scoring model to predict fall risk among older adults in the emergency department
TL;DR: In this paper , a case study describes challenges and barriers identified and overcome in such an operationalization for a model aimed at predicting risk of outpatient falls after Emergency Department (ED) visits among older adults.
Multisite evaluation of prediction models for emergency department crowding before and during the COVID-19 pandemic
Ari J Smith,Brian W. Patterson,Michael S. Pulia,John E. Mayer,Rebecca J. Schwei,Radha Nagarajan,F. Liao,Manish N. Shah,Justin J. Boutilier +8 more
TL;DR: In this article , a machine learning framework was developed to forecast emergency department (ED) crowding and to evaluate model performance under spatial and temporal data drift, and the results demonstrate that ED boarding is a predictable metric for ED crowding, and any attempts at implementation must consider spatial data drift.
Effectiveness of an Emergency Department Based Machine Learning Clinical Decision Support Tool to Prevent Outpatient Falls among Older Adults: A Protocol Paper for a Quasi-experimental Study (Preprint)
Daniel J. Hekman,Amy L. Cochran,Apoorva Maru,Manish N. Shah,F. Liao,Hanna J. Barton,W. Wiegmann,Maureen A. Smith,Brian W. Patterson +8 more
TL;DR: A research protocol for evaluating the effectiveness of an automated screening and referral intervention using machine learning and artificial intelligence to augment medical decision-making and the impact of an ML-CDS intervention on patient behavior and outcomes is described.
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