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Guilherme Del Fiol

Professor and Vice-Chair for Research

University of Utah

United States

Research Interests

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About

Guilherme Del Fiol is a Professor and Vice-Chair for Research at the University of Utah, USA. His research areas focus on health interventions, patient safety, and the utilization of technology in clinical settings, as evidenced by his recent publications. These include systematic reviews on drug safety, prediction models for patient deterioration, and innovative digital health solutions such as mobile interventions for COVID-19 testing and chatbot applications for genetic screening results.

Articles (28)

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Collaborators (27)

Kensaku Kawamoto

University of Utah

UNITED STATES

Guilherme Del Fiol

Research Interests

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About

Articles (28)

Nonsteroidal Anti‐Inflammatory Drugs and Risk of Gastrointestinal Bleeding: A Systematic Review and Meta‐Analysis

Conceptual framework for prediction models of patient deterioration based on nursing documentation patterns: reproducibility and generalizability with a large number of hospitals across the United States

Population-Based Digital Health Interventions to Deliver at-Home COVID-19 Testing: SCALE-UP II Randomized Clinical Trial

Shared Decision-Making Tools Implemented in the Electronic Health Record: Scoping Review

A Randomized-Controlled Trial of SCALE-UP Counts: A Mobile Intervention for Increasing COVID-19 Testing in K-12 Schools Serving Disadvantaged Communities (Preprint)

Chatbot for the Return of Positive Genetic Screening Results for Hereditary Cancer Syndromes: Prompt Engineering Project

Virtual Patients Using Large Language Models: Scalable, Contextualized Simulation of Clinician-Patient Dialogue With Feedback

Social vulnerability and genetic service utilization among unaffected BRIDGE trial patients with inherited cancer susceptibility

Improved Interpretability Without Performance Reduction in a Sepsis Prediction Risk Score

Genetically guided precision medicine clinical decision support tools: a systematic review

The Business Process Management for Healthcare (BPM+ Health) Consortium: motivation, methodology, and deliverables for enabling clinical knowledge interoperability (CKI)

Impact of Hyperparameter Optimization to Enhance Machine Learning Performance: A Case Study on Breast Cancer Recurrence Prediction

Precision public health in the era of genomics and big data

Clinician perspectives on how situational context and augmented intelligence design features impact perceived usefulness of sepsis prediction scores embedded within a simulated electronic health record

SCALE-UP II: protocol for a pragmatic randomised trial examining population health management interventions to increase the uptake of at-home COVID-19 testing in community health centres

The MyLungHealth study protocol: a pragmatic patient-randomised controlled trial to evaluate a patient-centred, electronic health record-integrated intervention to enhance lung cancer screening in primary care

Leveraging Natural Language Processing to Extract Features of Colorectal Polyps From Pathology Reports for Epidemiologic Study

Implementing Machine Learning in the Electronic Health Record: Checklist of Essential Considerations

Machine Learning Algorithms to Predict Breast Cancer Recurrence Using Structured and Unstructured Sources from Electronic Health Records

Implementation of Lung Cancer Screening in Primary Care and Pulmonary Clinics: Pragmatic Clinical Trial of Electronic Health Record-Integrated Everyday Shared Decision Making Tool and Clinician-Facing Prompts.

Increasing the reach of evidence-based interventions for weight management and diabetes prevention among Medicaid patients: study protocol for a pilot Sequential Multiple Assignment Randomised Trial

Information displays for automated surveillance algorithms of in-hospital patient deterioration: a scoping review

Implementing lung cancer screening in primary care: needs assessment and implementation strategy design.

Shared Decision-Making for Drug-Drug Interactions: Formative Evaluation of an Anticoagulant Drug Interaction

Correction: Identifying Patients Who Meet Criteria for Genetic Testing of Hereditary Cancers Based on Structured and Unstructured Family Health History Data in the Electronic Health Record: Natural Language Processing Approach

Identifying Patients Who Meet Criteria for Genetic Testing of Hereditary Cancers Based on Structured and Unstructured Family Health History Data in the Electronic Health Record: Natural Language Processing Approach

The potential for leveraging machine learning to filter medication alerts

BeatPain Utah: study protocol for a pragmatic randomised trial examining telehealth strategies to provide non-pharmacologic pain care for persons with chronic low back pain receiving care in federally qualified health centers

Collaborators (27)

Kensaku Kawamoto

Martín López-Nores

David Wetter

Charlene R Weir

Abdelrahman Younis

Simon Lin

Melody Goodman

Jackilen Shannon

Kenrick Cato

Jose J. Pazos-Arias

Vernon Pankratz

Kathryn Holt

Tanner Caverly

Julie Fritz

Katy E. Trinkley

Mei Liu

Polina Kukhareva

Kimberly A. Kaphingst

Sarah Rossetti

Deniz Dishman

Thomas Reese

Keaton Morgan

Rachel Hess

Chelsey Schlechter

Bryan Gibson

Joseph Finkelstein

Jorie Michaela Butler

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