A new method for determining factors Influencing productivity of deep coalbed methane vertical cluster wells by HUANG Li, XIONG Xianyue, WANG Feng, SUN Xiongwei, ZHANG Yixin, ZHAO Longmei, SHI Shi, ZHANG Wen, ZHAO Haoyang, JI Liang, DENG Lin

“…This method centered on the initial meter gas production index and integrated multiple machine-learning algorithms. …”
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Teaching and Learning Resilience and Adjuvant Lessons from the COVID-19 Crisis: A Reflective Practitioner’s Perspective by Gilbert Motsaathebe

“…In terms of the method, the study draws on the author’s teaching experience and student feedback using an interpretative framework based on Driscoll’s What Model of reflection and insights from Resilience Theory and Reflective Practice. …”
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A machine learning model for predicting anatomical response to Anti-VEGF therapy in diabetic macular edema by Wenrui Lu, Kunhong Xiao, Xuemei Zhang, Yuqing Wang, Wenbin Chen, Xierong Wang, Yunxi Ye, Yan Lou, Li Li

“…PurposeTo develop a machine learning model to predict anatomical response to anti-VEGF therapy in patients with diabetic macular edema (DME).MethodsThis retrospective study included patients with DME who underwent intravitreal anti-VEGF treatment between January 2023 and February 2025. …”
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Digital learning resource use among Swedish medical students: insights from a nationwide survey by Martin F. Bjurström, Emma Lundkvist, Louise W. Sturesson, Ola Borgquist, Robin Lundén, Malin Jonsson Fagerlund, Miklós Lipcsey, Thomas Kander

“…Conclusions Medical students extensively use digital resources, with perceived large positive learning effects and benefits. Several background factors influence usage patterns. …”
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Predictive machine-learning model for screening iron deficiency without anaemia: a retrospective cohort study by Girish N Nadkarni, Orly Efros, Eyal Klang, Shelly Soffer, Gili Kenet, Aya Mudrik, Renana Robinson

“…Objectives This study aimed to develop and validate a machine-learning (ML) model to predict iron deficiency without anaemia (IDWA) using routinely collected electronic health record (EHR) data. …”
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Instrument performance management in vocational music education: Relationship between self-efficacy perception and learning approaches by Ajda Aylin Can

“…The study also determined that learning approaches varied based on gender, academic grade, and voluntary selection of instruments. …”
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Optimal Feature Selection and Classification for Parkinson’s Disease Using Deep Learning and Dynamic Bag of Features Optimization by Aarti, Swathi Gowroju, Mst Ismat Ara Begum, A. S. M. Sanwar Hosen

“…Convolutional Neural Networks are used to extract distinctive visual characteristics from numerous graphomotor sample representations generated by both PD and control participants. The proposed method presents an optimal feature selection technique based on Deep Learning (DL) and the Dynamic Bag of Features Optimization Technique (DBOFOT). …”
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Distributed Decision Making for Electromagnetic Radiation Source Localization Using Multi-Agent Deep Reinforcement Learning by Jiteng Chen, Zehui Zhang, Dan Fan, Chaoqun Hou, Yue Zhang, Teng Hou, Xiangni Zou, Jun Zhao

“…To address these challenges, we propose the Multi-UAV Reconnaissance Proximal Policy Optimization (MURPPO) algorithm based on a distributed reinforcement learning framework, which utilizes an independent decision making mechanism and collaborative positioning method with multiple UAVs to achieve high-precision detection and localization of radiation sources. …”
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AI Under Attack: Metric-Driven Analysis of Cybersecurity Threats in Deep Learning Models for Healthcare Applications by Sarfraz Brohi, Qurat-ul-ain Mastoi

“…In this paper, we provide a comprehensive analysis of key attack vectors, including adversarial attacks, such as the gradient-based Fast Gradient Sign Method (FGSM), evasion attacks (perturbation-based), and data poisoning, which threaten the reliability of DL models, with a specific focus on breast cancer detection. …”
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Impact of Subjective and Objective Green Space Characteristics on Mental Health Benefits: An Explainable Machine Learning Approach by Ke LI, Yipei MAO, Yongjun LI

“…This research aims to clarify the internal relationships between objective and subjective green space characteristics and different mental health benefits (emotional restoration, cognitive enhancement, and stress relief) through explainable machine learning models.MethodsA mental health perception restoration experiment was carried out in two green spaces (Yanziji Park and Xiamafang Park) in Nanjing, with 56 participants engaged in two-hour free activities in the green spaces. …”
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Dinosaurs in 2D Animation: An Innovative Learning Strategy to Improve Natural History Comprehension Skills in Indonesia by Jimmy Pratama, Diny Anggriani Adnas, Carlos Pingsen Pratama

“…This research aims to develop 2D animation-based learning media about dinosaurs to enrich students' understanding of natural history. …”
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Examining the effects of organizational readiness dimensions and extrinsic motivation on the continuance intention to use e-learning innovations by Ashraf Ahmed Fadelelmoula

“…The model postulated these dimensions as direct determinants of the e-learning innovations continuance intention. A structured questionnaire-based survey was conducted to empirically assess the developed model. …”
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The Effectiveness of Baamboozle Game as a Learning Media for Flat Geometry in Improving Students' Problem-Solving Skills by Hilda, Fitria Dwi Prasetyaningtyas

“…The results showed that the Baamboozle game was highly feasible for use in learning, based on expert validation with high scores and positive student feedback. …”
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Transforming EFL students' engagement: How AI-enhanced environments bridge emotional health challenges like depression and anxiety by Huili Yang, Yanping Rui

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Penerapan Technology-Enhanced Learning dalam Pengembangan Pendidikan Agama Islam pada Anak Usia Dini by Sulastri Sulastri, Ismail Ismail

“…Based on Richard E. Mayer's theory of cognitive multimedia, the use of media such as images and videos can help reduce cognitive load and facilitate the learning process. …”
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THE EFFECTIVENESS OF A PROPOSED COUNSELLING PROGRAM FOR INCREASING THE LEVEL OF SELF-REGULATED LEARNING AMONG UNIVERSITY STUDENTS by Khalid Mustafa, Zhakaw Ahmed

“… This study aims to develop a proposed counseling program to enhance self-regulated learning among university students and to examine the program’s effectiveness within the experimental group based on gender, through a comparison of pre-test and post-test scores. …”
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DFL-TORO: A One-Shot Demonstration Framework for Learning Time-Optimal Robotic Manufacturing Tasks by Alireza Barekatain, Hamed Habibi, Holger Voos

“…This paper presents DFL-TORO, a novel Demonstration Framework for Learning Time-Optimal Robotic tasks via One-shot kinesthetic demonstration. …”
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Transforming label-efficient decoding of healthcare wearables with self-supervised learning and “embedded” medical domain expertise by Xiao Gu, Zhangdaihong Liu, Jinpei Han, Jianing Qiu, Wenfei Fang, Lei Lu, Lei Clifton, Yuan-Ting Zhang, David A. Clifton

“…We introduce a framework that integrates clinically meaningful features—such as heart rate variability from electrocardiograms (ECGs)—into the contrastive learning process. These features guide the formation of more relevant positive pairs through nearest-neighbor matching and promote global structure through clustering-based prototype representations. …”
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Distinguishing glioblastoma from brain metastasis; a systematic review and meta-analysis on the performance of machine learning by Mohammad Amin Habibi, Reza Omid, Shafaq Asgarzade, Sadaf Derakhshandeh, Ali Soltani Farsani, Zohreh Tajabadi

“…Method The search was conducted from inception to 1 June, 2023, in PubMed/Medline, Embase, Scopus, and Web of Science to find out the studies investigated the performance of ML-based algorithm for differentiation of glioblastoma and metastatic brain tumor. …”
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SkinEHDLF a hybrid deep learning approach for accurate skin cancer classification in complex systems by Umesh Kumar Lilhore, Yogesh Kumar Sharma, Sarita Simaiya, Roobaea Alroobaea, Abdullah M. Baqasah, Majed Alsafyani, Afnan Alhazmi

“…This study introduces SkinEHDLF, an innovative deep-learning model that enhances skin cancer classification. …”
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