Browsing by Author "Edwards, Brandon"

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    Federated learning as a catalyst for digital healthcare innovations
    (Elsevier, 2024-07-12) Yang, Guang; Edwards, Brandon; Bakas, Spyridon; Dou, Qi; Xu, Daguang; Li, Xiaoxiao; Wang, Wanying; Pathology and Laboratory Medicine, School of Medicine
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    Impact of Telestroke Implementation on Emergency Department Transfer Rate
    (AAN, 2022-04) Lyerly, Michael; Daggy, Joanne; LaPradd, Michelle; Martin, Holly; Edwards, Brandon; Graham, Glenn D.; Martini, Sharyl; Anderson, Jane; Williams, Linda; Biostatistics, School of Public Health
    Background and Objectives Telestroke networks are associated with improved outcomes from acute ischemic stroke (AIS) and facilitate greater access to care, particularly in underserved regions. These networks also have the potential to influence patient disposition through avoiding unnecessary interhospital transfers. This study examines the effect of implementation of the VA National Telestroke Program (NTSP) on interhospital transfer among Veterans. Methods We analyzed patients with AIS presenting to the emergency departments of 21 VA hospitals before and after telestroke implementation. Transfer rates were determined through review of administrative data and chart review and patient and facility-level characteristics were collected to identify predictors of transfer. Comparisons were made using t test, Wilcoxon rank sum, and χ2 analysis. Multivariable logistic regression with sensitivity analysis was conducted to assess the influence of telestroke implementation on transfer rates. Results We analyzed 3,488 stroke encounters (1,056 pre-NTSP and 2,432 post-NTSP). Following implementation, we observed an absolute 14.4% decrease in transfers across all levels of stroke center designation. Younger age, higher stroke severity, and shorter duration from symptom onset were associated with transfer. At the facility level, hospitals with lower annual stroke volume were more likely to transfer; 1 hospital saw an increase in transfer rates following implementation. After adjusting for patient and facility characteristics, the implementation of VA NTSP resulted in a nearly 60% reduction in odds of transfer (odds ratio 0.39 [0.19, 0.77]). Discussion In addition to improving treatment in acute stroke, telestroke networks have the potential to positively affect the efficiency of interhospital networks through disposition optimization and the avoidance of unnecessary transfers.
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    Privacy preservation for federated learning in health care
    (Elsevier, 2024-07-12) Pati, Sarthak; Kumar, Sourav; Varma, Amokh; Edwards, Brandon; Lu, Charles; Qu, Liangqiong; Wang, Justin J.; Lakshminarayanan, Anantharaman; Wang, Shih-han; Sheller, Micah J.; Chang, Ken; Singh, Praveer; Rubin, Daniel L.; Kalpathy-Cramer, Jayashree; Bakas, Spyridon; Pathology and Laboratory Medicine, School of Medicine
    Artificial intelligence (AI) shows potential to improve health care by leveraging data to build models that can inform clinical workflows. However, access to large quantities of diverse data is needed to develop robust generalizable models. Data sharing across institutions is not always feasible due to legal, security, and privacy concerns. Federated learning (FL) allows for multi-institutional training of AI models, obviating data sharing, albeit with different security and privacy concerns. Specifically, insights exchanged during FL can leak information about institutional data. In addition, FL can introduce issues when there is limited trust among the entities performing the compute. With the growing adoption of FL in health care, it is imperative to elucidate the potential risks. We thus summarize privacy-preserving FL literature in this work with special regard to health care. We draw attention to threats and review mitigation approaches. We anticipate this review to become a health-care researcher's guide to security and privacy in FL.