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Patient Similarity in Prediction Models Based on Health Data: A Scoping Review

Patient Similarity in Prediction Models Based on Health Data: A Scoping Review

Clinics31560Cross-sectionalUCI repository[20]-Pima Indians Diabetes: NR8760Cross-sectionalUCI repository[20]-Liver Disorders: BUPA Medical Research7340Saeed et al [21]LongitudinalMIMIC-II [22]-The Multiparameter Intelligent Monitoring in Intensive Care at Boston’s Beth

Anis Sharafoddini, Joel A Dubin, Joon Lee

JMIR Med Inform 2017;5(1):e7

Unpacking Prevalence and Dichotomy in Quick Sequential Organ Failure Assessment and Systemic Inflammatory Response Syndrome Parameters: Observational Data–Driven Approach Backed by Sepsis Pathophysiology

Unpacking Prevalence and Dichotomy in Quick Sequential Organ Failure Assessment and Systemic Inflammatory Response Syndrome Parameters: Observational Data–Driven Approach Backed by Sepsis Pathophysiology

[21,22,34-36].The recent major release of Medical Information Mart for Intensive Care (MIMIC-III, Version 1.4) is an extensive, single-center, and comprehensive database comprising information pertaining to patients admitted to the critical care units at Beth

Nazmus Sakib, Sheikh Iqbal Ahamed, Rumi Ahmed Khan, Paul M Griffin, Md Munirul Haque

JMIR Med Inform 2020;8(12):e18352

A Lightweight Deep Learning Model for Fast Electrocardiographic Beats Classification With a Wearable Cardiac Monitor: Development and Validation Study

A Lightweight Deep Learning Model for Fast Electrocardiographic Beats Classification With a Wearable Cardiac Monitor: Development and Validation Study

The model resulted in an average accuracy of 94.03% compared with the MIT-BIH (Massachusetts Institute of Technology-Beth Israel Hospital) gold standard.However, a limitation of CNNs is that the length of inputs must be fixed since the filters of the networks

Eunjoo Jeon, Kyusam Oh, Soonhwan Kwon, HyeongGwan Son, Yongkeun Yun, Eun-Soo Jung, Min Soo Kim

JMIR Med Inform 2020;8(3):e17037

Computing Health Quality Measures Using Informatics for Integrating Biology and the Bedside

Computing Health Quality Measures Using Informatics for Integrating Biology and the Bedside

Buck’s terminology, and Beth Israel Deaconess Medical Center). Each library utilizes all features of the translator (see Table 1 and the discussion above).

Jeffrey G. Klann, Shawn N. Murphy

J Med Internet Res 2013;15(4):e75

Correction: OpenNotes After 7 Years: Patient Experiences With Ongoing Access to Their Clinicians’ Outpatient Visit Notes

Correction: OpenNotes After 7 Years: Patient Experiences With Ongoing Access to Their Clinicians’ Outpatient Visit Notes

BIDMC: Beth Israel Deaconess Medical Center; UW: University of Washington Medicine.The correction will appear in the online version of the paper on the JMIR website on April 30, 2020, together with the publication of this correction notice.

Jan Walker, Suzanne Leveille, Sigall Bell, Hannah Chimowitz, Zhiyong Dong, Joann G Elmore, Leonor Fernandez, Alan Fossa, Macda Gerard, Patricia Fitzgerald, Kendall Harcourt, Sara Jackson, Thomas H Payne, Jocelyn Perez, Hannah Shucard, Rebecca Stametz, Catherine DesRoches, Tom Delbanco

J Med Internet Res 2020;22(4):e18639

Patient and Family Engagement in the Design of a Mobile Health Solution for Pediatric Asthma: Development and Feasibility Study

Patient and Family Engagement in the Design of a Mobile Health Solution for Pediatric Asthma: Development and Feasibility Study

Here we describe the approach used to engage pediatric patients, their caregivers, and their providers, while providing additional perspectives from Beth, a parent who participated on the development team.MethodsUser-Centric Design ApproachWe created a process

Andrew McWilliams, Kelly Reeves, Lindsay Shade, Elizabeth Burton, Hazel Tapp, Cheryl Courtlandt, Andrew Gunter, Michael F Dulin

JMIR Mhealth Uhealth 2018;6(3):e68

Toward Optimal Heparin Dosing by Comparing Multiple Machine Learning Methods: Retrospective Study

Toward Optimal Heparin Dosing by Comparing Multiple Machine Learning Methods: Retrospective Study

The MIMIC-III database contains data from the intensive care unit at the Beth Israel Deaconess Medical Center and is published by the Laboratory for Computational Physiology at Massachusetts Institute of Technology.

Longxiang Su, Chun Liu, Dongkai Li, Jie He, Fanglan Zheng, Huizhen Jiang, Hao Wang, Mengchun Gong, Na Hong, Weiguo Zhu, Yun Long

JMIR Med Inform 2020;8(6):e17648

OpenNotes After 7 Years: Patient Experiences With Ongoing Access to Their Clinicians’ Outpatient Visit Notes

OpenNotes After 7 Years: Patient Experiences With Ongoing Access to Their Clinicians’ Outpatient Visit Notes

findings from a large survey of patients conducted in the institutions that participated in the pilot OpenNotes inquiry.MethodsSettingWe conducted a Web-based survey of patients who had been seen in hospital offices and community practices at 3 health systems: Beth

Jan Walker, Suzanne Leveille, Sigall Bell, Hannah Chimowitz, Zhiyong Dong, Joann G Elmore, Leonor Fernandez, Alan Fossa, Macda Gerard, Patricia Fitzgerald, Kendall Harcourt, Sara Jackson, Thomas H Payne, Jocelyn Perez, Hannah Shucard, Rebecca Stametz, Catherine DesRoches, Tom Delbanco

J Med Internet Res 2019;21(5):e13876

Utilizing a Personal Smartphone Custom App to Assess the Patient Health Questionnaire-9 (PHQ-9) Depressive Symptoms in Patients With Major Depressive Disorder

Utilizing a Personal Smartphone Custom App to Assess the Patient Health Questionnaire-9 (PHQ-9) Depressive Symptoms in Patients With Major Depressive Disorder

as well as enable us to capture day-to-day variability in depressive symptoms and accurately represent intraindividual symptoms and their variation.MethodsDesign of Study and Smartphone AppSubjects were recruited from the outpatient psychiatry clinics at Beth

John Torous, Patrick Staples, Meghan Shanahan, Charlie Lin, Pamela Peck, Matcheri Keshavan, Jukka-Pekka Onnela

JMIR Ment Health 2015;2(1):e8