Learning to suppress tremors: a deep reinforcement learning-enabled soft exoskeleton for Parkinson’s patients by Tamás Endrei, Tamás Endrei, Sándor Földi, Sándor Földi, Ádám Makk, György Cserey, György Cserey

“…We present a deep reinforcement learning-based encoder-actor controller for Parkinson’s tremors in various shoulder and elbow joint axes displayed in dynamic movements.ResultsOur findings suggest that such a control strategy offers a viable solution for tremor suppression in real-world scenarios.DiscussionBy overcoming the limitations of traditional control algorithms, this work takes a new step in adapting biomechanical loading into the everyday life of patients. …”
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Fusion of Personalized Federated Learning (PFL) with Differential Privacy (DP) Learning for Diagnosis of Arrhythmia Disease. by Syed Mohsin Bokhari, Sarmad Sohaib, Muhammad Shafi

“…This paper presents a novel privacy-preserving architecture, a fusion of Federated Learning with Personalized Models and Differential Privacy (FLPMDP), for diagnosing arrhythmia from 12-lead electrocardiogram (ECG) signals. …”
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Transforming dental education: interactive and student-centered learning with team-based learning in the undergraduate program by Teun J. de Vries, Katie L. Crouwel, Erica Vogelzang, A. Isa Levert, Egbert Neels, Amber de Wilde, Pepijn Koopman, Denise E. van Diermen, Geerling E. J. Langenbach, E. Etienne Verheijck

“…Here we describe the implementation of team-based learning (TBL), an effective educational approach for activated learning at a dental school. …”
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Factors affecting first-grade pupils' physical activity during the school day: A pilot study by Dita Culkova, Veronika Dušková

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Advanced Deep Learning and Machine Learning Techniques for MRI Brain Tumor Analysis: A Review by Rim Missaoui, Wided Hechkel, Wajdi Saadaoui, Abdelhamid Helali, Marco Leo

“…In this study, we focus on current advances in medical imaging, particularly magnetic resonance imaging (MRI), and how machine learning (ML) and deep learning (DL) algorithms might be combined with clinical assessments to improve brain tumor diagnosis. …”
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The improvement students learning achievement by applying work based learning combined with teaching factory concept by Hasan Maksum, Wawan Purwanto, Toto Sugiarto, Nuzul Hidayat, Siman Siman, Hanapi Hasan

“…The results indicate that the WBL-TEFA learning model introduced novel elements to the model syntax through the following activity steps: (1) initiation, (2) receiving orders, (3) gathering necessary information, (4) generating and sorting possible solutions, (5) executing orders, (6) quality control, and (7) assessment. …”
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Practical Guide Based on Learning Cycle 5E to Enhance Students’ Cognitive Learning Outcomes by Dwi Safriani Pangestika, Zuhdan Kun Prasetyo

“…The aim of this study was : 1) to describe the feasibility of develop practical guide based on learning cycle 5E and 2) to analyse the improvement of the practical guide based on learning cycle 5E to enhance cognitive learning outcomes of eight graders of junior high school in science lesson. …”
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Comprehensive Investigation of Machine Learning and Deep Learning Networks for Identifying Multispecies Tomato Insect Images by Chittathuru Himala Praharsha, Alwin Poulose, Chetan Badgujar

“…Deep learning applications in agriculture are advancing rapidly, leveraging data-driven learning models to enhance crop yield and nutrition. …”
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Multi-Step Temperature Prognosis of Lithium-Ion Batteries for Real Electric Vehicles Based on a Novel Bidirectional Mamba Network and Sequence Adaptive Correlation by Hongyu Shen, Yuefeng Liu, Qiyan Zhao, Guoyue Xue, Tiange Zhang, Xiuying Tan

“…Next, a prediction method with multiple steps based on the bidirectional Mamba is suggested. …”
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Peyton’s Four-step Method versus See One, Do One, Teach One Method for Acquisition of Ophthalmic Clinical Skills in Undergraduate Medical Students by Nitin Nema, Yashas Goyal, Harshal Gupta, Swapnil Paralikar, Chinmay Shah, Praveen Singh

“…Conclusion: Peyton’s four-step model was found to be superior to the traditional SODOTO method.…”
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From Binary to Multi-Class Classification: A Two-Step Hybrid CNN-ViT Model for Chest Disease Classification Based on X-Ray Images by Yousra Hadhoud, Tahar Mekhaznia, Akram Bennour, Mohamed Amroune, Neesrin Ali Kurdi, Abdulaziz Hadi Aborujilah, Mohammed Al-Sarem

“…Methods: We designed a two-step hybrid model that integrates the ResNet-50 CNN with the ViT-b16 architecture. …”
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Survey of Deep Learning and Machine Learning Approaches for Major Depressive Disorder Detection Using EEG Data by Sumathi Balakrishnan, Raja Kumar Murugesan, Eng Lye Lim, Amna Faisal, Humaira Ashraf

“…Recent advances in electroencephalogram (EEG) analysis have combined physiological markers with machine learning (ML) and deep learning (DL) techniques, offering objective, noninvasive alternatives for MDD detection. …”
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Predictive model for customer satisfaction analytics in E-commerce sector using machine learning and deep learning by Hoanh-Su Le, Thao-Vy Huynh Do, Minh Hoang Nguyen, Hoang-Anh Tran, Thanh-Thuy Thi Pham, Nhung Thi Nguyen, Van-Ho Nguyen

“…This paper introduces a two-step predictive framework merging deep learning and traditional machine learning to analyze Vietnamese e-commerce reviews. …”
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Federated Learning Enhanced MLP–LSTM Modeling in an Integrated Deep Learning Pipeline for Stock Market Prediction by Jayaraman Kumarappan, Elakkiya Rajasekar, Subramaniyaswamy Vairavasundaram, Ketan Kotecha, Ambarish Kulkarni

“…The research intends to use the LSTM networks extensively that are proficient in spatial dependence capturing and integrate them with the collaborative learning framework of Federated Learning in an endeavor to augment the predictive competency. …”
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Evaluating Deep Learning Architectures for Breast Tumor Classification and Ultrasound Image Detection Using Transfer Learning by Christopher Kormpos, Fotios Zantalis, Stylianos Katsoulis, Grigorios Koulouras

“…The intersection of medical image classification and deep learning has garnered increasing research interest, particularly in the context of breast tumor detection using ultrasound images. …”
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IMPROVING PREDICTION OF DEPRESSION AN ANALYTICAL COMPARISON BETWEEN HYBRID AI, MACHINE LEARNING AND DEEP LEARNING APPROACHES by Kanchapogu Naga Raju, Sachi Nandan Mohanty

“…This research includes an original comparative evaluation of machine learning (ML) and deep learning (DL) tactics, further developing through the building of integrated artificial intelligence frameworks. …”
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Context-aware implicit neural representations to compress Earth systems model data by Farinaz Mostajeran, Nikhil M. Pawar, Jonathan M. Villarreal, Salah A. Faroughi

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Learning Arabic Reading Skills Based on E-Learning Using SIKULI during the Covid-19 Pandemic by Budi Santoso Wibowo, Widiya Yul, Riko Andrian

“…Abstract This paper explores the steps for learning Arabic reading skills based on e-Learning using SIKULI and the advantages and disadvantages of e-Learning. …”
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When does policy learning lead to policy change? Exploring the causal chain from learning to change by Sandra Plümer

“…Yet, there is still uncertainty about the conditions under which learning actually leads to change. This article clarifies the causal chain from policy learning to policy change in two steps. …”
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TECHNOLOGIES-SUPPORTED COLLABORATIVE PROBLEM-SOLVING LEARNING MODEL FOR FOREIGN LANGUAGE LEARNING BASED ON CASES AND PROJECTS by Aisyiah Al Adawiyah, Akbar Syamsul Arifin

“…Purpose—This research aims to develop standardized learning steps by applying technology to enhance student interactivity, improve learners’ communication skills, and address challenges of student engagement in foreign language learning. …”
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