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Les récentes avancées en traitement et analyse du signal ont permis de créer de nouvelles manières d’instrumenter l'observation et l'analyse des événements scolaires, et donc de recueillir de nouveaux types de preuve des pratiques d'enseignement[...]Article
Taiki Miyazawa ; Yoichi Hiratsuka ; Masako Toda ; Nozomu Hatakeyama ; Hitoshi Ozawa ; Chizumi Abe ; Ting-Yu Cheng ; Yuji Matsushima ; Yoshifumi Miyawaki ; Kinya Ashida ; Jun Iimura ; Tomohiro Tsuda ; Hiroto Bushita ; Kazuichi Tomonobu ; Satoshi Ohta ; Hsuan Chung ; Yusuke Omae ; Takayuki Yamamoto ; Makoto Morinaga ; Hiroshi Ochi ; Hajime Nakada ; Kazuhiro Otsuka ; Teruo Miyazawa |In the late 2010s, artificial intelligence (AI) technologies became complementary to the research areas of food science and nutrition. This review aims to summarize these technological advances by systematically describing the following: the use[...]Article
Objective To assess the utility of applying natural language processing (NLP) to electronic health records (EHRs) to identify individuals with chronic mobility disability. Design We used EHRs from the Research Patient Data Repository, whi[...]Article
Objective To develop and validate a short form of the Fugl-Meyer Assessment of Upper Extremity Scale (FMA-UE) using a machine learning approach (FMA-UE-ML). In addition, scores of items not included in the FMA-UE-ML were predicted. Design Second[...]Article
Shih-Chieh Lee ; Inga Wang ; Gong-Hong Lin ; Pei-Chi Li ; Ya-Chen Lee ; Chia-Yeh Chou ; Chien-Yu Huang ; Ching-Lin Hsieh |Importance: Several short forms of the Stroke Impact Scale Version 3.0 (SIS 3.0) have been proposed in order to decrease its administration time of about 20 min. However, none of the short-form scores are comparable to those of the original meas[...]Article
Cet article décrit les défis en matière de responsabilité pouvant survenir lorsque l’on fait appel à un robot chirurgien disposant d’une capacité d’auto-apprentissage, qui agit de manière totalement autonome avec la même liberté diagnostique et [...]Article
Le Machine Learning est un sous-domaine de l’intelligence artificielle. Initialement défini comme un algorithme apprenant à exécuter une tâche de façon automatique, à partir d’une base de données, sans être programmé a priori pour y parvenir et [...]Article
L’intelligence artificielle (IA) fait de grand progrès au service de la médecine en général et des maladies métaboliques en particulier. L’apprentissage automatique, grâce notamment aux réseaux de neurones et la démultiplication des données mass[...]Article
A working knowledge of Artificial Neural Networks is rapidly becoming critical for navigating the modern world. Although the last few years have seen an explosion of the use of these tools in research, and there are many do-it-yourself articles [...]Article
Objective To summarize the progress toward the National Institutes of Health (NIH) Research Plan on Rehabilitation goals and the methods by which tracking occurred. Design Each grant award was manually coded by NIH staff for research plan[...]Chapitre de livre
T. Chauveau | 2021Recent studies proposed that understanding the connection between emotional states, pain and bodily sensations might help in the understanding of chronic pain conditions. In the targeted article, the authors developed a mobile platform dedicated[...]Article
Objectives: A confluence of recent developments in cloud computing, real-time web audio and machine learning psychometric function estimation has made wide dissemination of sophisticated turn-key audiometric assessments possible. The authors hav[...]Article
Objectives: Hearing loss is the most common sensory loss in humans and carries an enhanced risk of depression. No prior studies have attempted a contemporary machine learning approach to predict depression using subjective and objective hearing [...]Article
Emilie Cardon ; Laure Jacquemin ; Martin Schecklmann ; Berthold Langguth ; Griet Mertens ; Olivier Vanderveken ; Marc J.W. Lammers ; Paul Van de Heyning ; Vincent Van Rompaey ; Annick Gilles |Objectives: Transcranial direct current stimulation (tDCS) of the right dorsolateral prefrontal cortex has been hypothesized to reduce tinnitus severity by modifying cortical activity in brain regions associated with the perception of tinnitus. [...]Article
Using Machine Learning to Develop a Short-Form Measure Assessing 5 Functions in Patients With Stroke
Gong-Hong Lin ; Chih-Ying Li ; Ching-Fan Sheu ; Chien-Yu Huang ; Shih-Chieh Lee ; Yu-Hui Huang ; Ching-Lin Hsieh |Objective This study aimed to develop and validate a machine learning-based short measure to assess 5 functions (the ML-5F) (activities of daily living [ADL], balance, upper extremity [UE] and lower extremity [LE] motor function, and mobility) [...]
