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Open AccessArticle

“PhysIt”—A Diagnosis and Troubleshooting Tool for Physiotherapists in Training

1
Department of Software and Information Systems Engineering, Ben Gurion University, Negev 84105, Israel
2
Computer Science Department, University of Texas at Austin, Austin, TX 78712, USA
*
Author to whom correspondence should be addressed.
Diagnostics 2020, 10(2), 72; https://doi.org/10.3390/diagnostics10020072
Received: 2 January 2020 / Revised: 22 January 2020 / Accepted: 25 January 2020 / Published: 28 January 2020
(This article belongs to the Special Issue Artificial Intelligence in Diagnostics)
Many physiotherapy treatments begin with a diagnosis process. The patient describes symptoms, upon which the physiotherapist decides which tests to perform until a final diagnosis is reached. The relationships between the anatomical components are too complex to keep in mind and the possible actions are abundant. A trainee physiotherapist with little experience naively applies multiple tests to reach the root cause of the symptoms, which is a highly inefficient process. This work proposes to assist students in this challenge by presenting three main contributions: (1) A compilation of the neuromuscular system as components of a system in a Model-Based Diagnosis problem; (2) The PhysIt is an AI-based tool that enables an interactive visualization and diagnosis to assist trainee physiotherapists; and (3) An empirical evaluation that comprehends performance analysis and a user study. The performance analysis is based on evaluation of simulated cases and common scenarios taken from anatomy exams. The user study evaluates the efficacy of the system to assist students in the beginning of the clinical studies. The results show that our system significantly decreases the number of candidate diagnoses, without discarding the correct diagnosis, and that students in their clinical studies find PhysIt helpful in the diagnosis process. View Full-Text
Keywords: model based diagnosis; applications; diagnosis; physiotherapy model based diagnosis; applications; diagnosis; physiotherapy
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MDPI and ACS Style

Mirsky, R.; Hibah, S.; Hadad, M.; Gorenstein, A.; Kalech, M. “PhysIt”—A Diagnosis and Troubleshooting Tool for Physiotherapists in Training. Diagnostics 2020, 10, 72. https://doi.org/10.3390/diagnostics10020072

AMA Style

Mirsky R, Hibah S, Hadad M, Gorenstein A, Kalech M. “PhysIt”—A Diagnosis and Troubleshooting Tool for Physiotherapists in Training. Diagnostics. 2020; 10(2):72. https://doi.org/10.3390/diagnostics10020072

Chicago/Turabian Style

Mirsky, Reuth; Hibah, Shay; Hadad, Moshe; Gorenstein, Ariel; Kalech, Meir. 2020. "“PhysIt”—A Diagnosis and Troubleshooting Tool for Physiotherapists in Training" Diagnostics 10, no. 2: 72. https://doi.org/10.3390/diagnostics10020072

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