18 results for "Jeremy Petch"
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Journal Article
Opening the Black Box: The Promise and Limitations of Explainable Machine Learning in Cardiology
Many clinicians remain wary of machine learning because of longstanding concerns about "black box" models. "Black box" is shorthand for models that are sufficiently complex that they are not straightforwardly interpretable to humans. Lack of interpretability in predictive models can undermine trust…
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Journal Article Full text
Maximizing the value of patient and public involvement in the digital health co-design process: A qualitative descriptive study with design leaders and patient-public partners.
Digital health interventions have enormous potential to support patients and the public in achieving their health goals. Nonetheless, many digital health interventions are failing to effectively engage patients and the public. One solution that has been proposed is to directly involve patients and…
Also available at: PLOS
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Journal Article
Optimizing Health Coaching for Patients With Type 2 Diabetes Using Machine Learning: Model Development and Validation Study
BackgroundHealth coaching is an emerging intervention that has been shown to improve clinical and patient-relevant outcomes for type 2 diabetes. Advances in artificial intelligence may provide an avenue for developing a more personalized, adaptive, and cost-effective approach to diabetes health…
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Journal Article
Making Sense of Theories, Models, and Frameworks in Digital Health Behavior Change Design: Qualitative Descriptive Study
BackgroundDigital health interventions are increasingly being designed to support health behaviors. Although digital health interventions informed by behavioral science theories, models, and frameworks (TMFs) are more likely to be effective than those designed without them, design teams often…
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Journal Article
Optimizing Patient Record Linkage in a Master Patient Index Using Machine Learning: Algorithm Development and Validation
BackgroundTo provide quality care, modern health care systems must match and link data about the same patient from multiple sources, a function often served by master patient index (MPI) software. Record linkage in the MPI is typically performed manually by health care providers, guided by…
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Journal Article
甲襞毛细血管镜检测与深度学习在糖尿病中的应用
Abstract Objective To determine whether nailfold capillary images, acquired using video capillaroscopy, can provide diagnostic information about diabetes and its complications. Research Design and Methods Nailfold video capillaroscopy was performed in 120 adult patients with and without type 1 or…
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Journal Article
Machine Learning Approaches for the Image-Based Identification of Surgical Wound Infections: Scoping Review
BackgroundSurgical site infections (SSIs) occur frequently and impact patients and health care systems. Remote surveillance of surgical wounds is currently limited by the need for manual assessment by clinicians. Machine learning (ML)–based methods have recently been used to address various aspects…
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Journal Article
Integrating Behavioral Science and Design Thinking to Develop Mobile Health Interventions: Systematic Scoping Review
BackgroundMobile health (mHealth) interventions are increasingly being designed to facilitate health-related behavior change. Integrating insights from behavioral science and design science can help support the development of more effective mHealth interventions. Behavioral Design (BD) and Design…
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Journal Article
Breast cancer learning health system: Patient information from a data and analytics platform characterizes care provided
Abstract Purpose In a learning health system (LHS), data gathered from clinical practice informs care and scientific investigation. To demonstrate how a novel data and analytics platform can enable an LHS at a regional cancer center by characterizing the care provided to breast cancer patients…
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Journal Article
AI-Based Automation for Medication Reconciliation: Scoping Review
Abstract BackgroundMedication reconciliation (MedRec) has the potential to improve patient safety by enhancing the continuity of medication information across settings. MedRec involves 3 core tasks: the creation of a best possible medication history, the identification of medication discrepancies…
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Journal Article
A machine learning–based clinical decision support algorithm for reducing unnecessary coronary angiograms
Background: Conventional clinical risk scores and diagnostic algorithms are proving to be suboptimal in the prediction of obstructive coronary artery disease, contributing to the low diagnostic yield of invasive angiography. Machine learning could help better predict which patients would benefit…
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Journal Article
A versatile, fast and unbiased method for estimation of gene-by-environment interaction effects on biobank-scale datasets
Abstract Identification of gene-by-environment interactions (GxE) is crucial to understand the interplay of environmental effects on complex traits. However, current methods evaluating GxE on biobank-scale datasets have limitations. We introduce MonsterLM, a multiple linear regression method that…
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Journal Article
Optimizing warfarin dosing for patients with atrial fibrillation using machine learning
Abstract While novel oral anticoagulants are increasingly used to reduce risk of stroke in patients with atrial fibrillation, vitamin K antagonists such as warfarin continue to be used extensively for stroke prevention across the world. While effective in reducing the risk of strokes, the complex…
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Journal Article
Coronary Computed Tomographic Angiography to Optimize the Diagnostic Yield of Invasive Angiography for Low-Risk Patients Screened With Artificial Intelligence: Protocol for the CarDIA-AI Randomized Controlled Trial
BackgroundInvasive coronary angiography (ICA) is the gold standard in the diagnosis of coronary artery disease (CAD). Being invasive, it carries rare but serious risks including myocardial infarction, stroke, major bleeding, and death. A large proportion of elective outpatients undergoing ICA have…
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Journal Article
Continuous Noninvasive Remote Automated Blood Pressure Monitoring With Novel Wearable Technology: A Preliminary Validation Study
BackgroundWearable continuous monitoring biosensor technologies have the potential to transform postoperative care with early detection of impending clinical deterioration. ObjectiveOur aim was to validate the accuracy of Cloud DX Vitaliti continuous vital signs monitor (CVSM) continuous…
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Journal Article
Impact of Virtual Care With Remote Automated Monitoring on the Rate of Acute Hospital Care Post Discharge and Index Length of Hospital Stay: Protocol for the Post Discharge After Surgery Virtual Care With Remote Automated Monitoring Technology 3 (PVC-RAM-3) Trial
BackgroundA substantial proportion of patients require acute hospital care after hospital discharge post surgery, and many regions and countries have surgical backlogs. ObjectiveThe Post Discharge After Surgery Virtual Care with Remote Automated Monitoring Technology-3 (PCV-RAM-3) trial tests the…
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Journal Article
Correction: “Impact of Virtual Care With Remote Automated Monitoring on the Rate of Acute Hospital Care Post Discharge and Index Length of Hospital Stay: Protocol for the Post Discharge After Surgery Virtual Care With Remote Automated Monitoring Technology 3 (PVC-RAM-3) Trial”
A substantial proportion of patients require acute hospital care after hospital discharge post surgery, and many regions and countries have surgical backlogs. The Post Discharge After Surgery Virtual Care with Remote Automated Monitoring Technology-3 (PCV-RAM-3) trial tests the hypothesis that…