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Automated Categorization of Systemic Disease and Duration From Electronic Medical Record System Data Using Finite-State Machine Modeling: Prospective Validation Study

Automated Categorization of Systemic Disease and Duration From Electronic Medical Record System Data Using Finite-State Machine Modeling: Prospective Validation Study

diseases is vital to prognosticate the severity of the ocular condition and the treatment outcomes.In a systemic review based on extracting information from the text of EMRs to improve case detection, Ford et al [8] compared the accuracy of case-detection algorithms

Gumpili Sai Prashanthi, Ayush Deva, Ranganath Vadapalli, Anthony Vipin Das

JMIR Form Res 2020;4(12):e24490


A Nonproprietary Movement Analysis System (MoJoXlab) Based on Wearable Inertial Measurement Units Applicable to Healthy Participants and Those With Anterior Cruciate Ligament Reconstruction Across a Range of Complex Tasks: Validation Study

A Nonproprietary Movement Analysis System (MoJoXlab) Based on Wearable Inertial Measurement Units Applicable to Healthy Participants and Those With Anterior Cruciate Ligament Reconstruction Across a Range of Complex Tasks: Validation Study

However, motion tracking using IMUs uses an inherently different principle, where the relative angular motion of each IMU sensor is combined using sensor fusion algorithms to calculate the joint angles for the hip, knee, and ankle joints.

Riasat Islam, Mohamed Bennasar, Kevin Nicholas, Kate Button, Simon Holland, Paul Mulholland, Blaine Price, Mohammad Al-Amri

JMIR Mhealth Uhealth 2020;8(6):e17872


Continuous Digital Monitoring of Walking Speed in Frail Elderly Patients: Noninterventional Validation Study and Longitudinal Clinical Trial

Continuous Digital Monitoring of Walking Speed in Frail Elderly Patients: Noninterventional Validation Study and Longitudinal Clinical Trial

However, progress on interpretation via advanced analytics is undermined by a lack of algorithms with validated accuracy and performance in disease populations [6], and most clinical trials still focus exclusively on established performance tests.ObjectivesAge-related

Arne Mueller, Holger Alfons Hoefling, Amir Muaremi, Jens Praestgaard, Lorcan C. Walsh, Ola Bunte, Roland Martin Huber, Julian  Fürmetz, Alexander Martin Keppler, Matthias Schieker, Wolfgang Böcker, Ronenn Roubenoff, Sophie Brachat, Daniel S. Rooks, Ieuan Clay

JMIR Mhealth Uhealth 2019;7(11):e15191


Wearable Sensors Reveal Menses-Driven Changes in Physiology and Enable Prediction of the Fertile Window: Observational Study

Wearable Sensors Reveal Menses-Driven Changes in Physiology and Enable Prediction of the Fertile Window: Observational Study

Finally, in keeping with previous research and best practices for maximizing fertility prediction algorithms [6,40-43], we also excluded data from 14 women who reported measurements and synchronized their bracelet with the cellphone app less than 80% of days

Brianna Mae Goodale, Mohaned Shilaih, Lisa Falco, Franziska Dammeier, Györgyi Hamvas, Brigitte Leeners

J Med Internet Res 2019;21(4):e13404


A Human-Algorithm Integration System for Hip Fracture Detection on Plain Radiography: System Development and Validation Study

A Human-Algorithm Integration System for Hip Fracture Detection on Plain Radiography: System Development and Validation Study

Numerous applications of DL in medicine, such as computer-aided diagnosis, have been studied [3-9].Several studies have shown the possibility of using algorithms trained with a large amount of data to aid in appropriate triage, accurately predicting outcomes

Chi-Tung Cheng, Chih-Chi Chen, Fu-Jen Cheng, Huan-Wu Chen, Yi-Siang Su, Chun-Nan Yeh, I-Fang Chung, Chien-Hung Liao

JMIR Med Inform 2020;8(11):e19416


Nontraditional Electrocardiogram and Algorithms for Inconspicuous In-Home Monitoring: Comparative Study

Nontraditional Electrocardiogram and Algorithms for Inconspicuous In-Home Monitoring: Comparative Study

The effectiveness of these algorithms is demonstrated using a nonstandard, dry electrode–based ECG integrated into a toilet seat for inconspicuous in-home monitoring.

Nicholas J Conn, Karl Q Schwarz, David A Borkholder

JMIR Mhealth Uhealth 2018;6(5):e120