Todd Ferris
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View article: Environment scan of generative AI infrastructure for clinical and translational science
Environment scan of generative AI infrastructure for clinical and translational science Open
This study reports a comprehensive environmental scan of the generative AI (GenAI) infrastructure in the national network for clinical and translational science across 36 institutions supported by the CTSA Program led by the National Cente…
View article: Environment Scan of Generative AI Infrastructure for Clinical and Translational Science
Environment Scan of Generative AI Infrastructure for Clinical and Translational Science Open
This study reports a comprehensive environmental scan of the generative AI (GenAI) infrastructure in the national network for clinical and translational science across 36 institutions supported by the Clinical and Translational Science Awa…
The Stanford Medicine data science ecosystem for clinical and translational research Open
Objective To describe the infrastructure, tools, and services developed at Stanford Medicine to maintain its data science ecosystem and research patient data repository for clinical and translational research. Materials and Methods The dat…
The development of a mobile app‐focused deduplication strategy for the Apple Heart Study that informs recommendations for future digital trials Open
An app‐based clinical trial enrolment process can contribute to duplicated records, carrying data management implications. Our objective was to identify duplicated records in real time in the Apple Heart Study (AHS). We leveraged personal …
Lessons learned in the Apple Heart Study and implications for the data management of future digital clinical trials Open
The digital clinical trial is fast emerging as a pragmatic trial that can improve a trial's design including recruitment and retention, data collection and analytics. To that end, digital platforms such as electronic health records or wear…
Arrhythmias Other Than Atrial Fibrillation in Those With an Irregular Pulse Detected With a Smartwatch: Findings From the Apple Heart Study Open
Background: The Apple watch irregular pulse detection algorithm was found to have a positive predictive value of 0.84 for identification of atrial fibrillation (AF). We sought to describe the prevalence of arrhythmias other than AF in thos…
View article: Large-Scale Assessment of a Smartwatch to Identify Atrial Fibrillation
Large-Scale Assessment of a Smartwatch to Identify Atrial Fibrillation Open
The probability of receiving an irregular pulse notification was low. Among participants who received notification of an irregular pulse, 34% had atrial fibrillation on subsequent ECG patch readings and 84% of notifications were concordant…
Rationale and design of a large-scale, app-based study to identify cardiac arrhythmias using a smartwatch: The Apple Heart Study Open
The results of this trial will provide initial evidence for the ability of a smartwatch algorithm to identify pulse irregularity and variability which may reflect previously unknown AF. The Apple Heart Study will help provide a foundation …