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. …”
Get full text

A multi-data fusion deep learning model for prognostic prediction in upper tract urothelial carcinoma by Hongdi Sun, Siping Chen, Yongxing Bao, Fengyan You, Honghui Zhu, Xin Yao, Lianguo Chen, Lianguo Chen, Jiangwei Miao, Fanggui Shao, Fanggui Shao, Xiaomin Gao, Binwei Lin

“…The model’s prognostic performance was compared with two unimodal models—ImageNet (CT-based) and ClinicalNet (clinical data-based)—and traditional clinical parameters including pathological T stage. …”
Get full text

Predictive Modeling of Acute Respiratory Distress Syndrome Using Machine Learning: Systematic Review and Meta-Analysis by Jinxi Yang, Siyao Zeng, Shanpeng Cui, Junbo Zheng, Hongliang Wang

“…The findings will provide evidence-based insights to support the development of more accurate and effective ARDS prediction tools. …”
Get full text

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). …”
Get full text

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. …”
Get full text

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. …”
Get full text

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. …”
Get full text

Predicting pediatric age from chest X-rays using deep learning: a novel approach by Maolin Li, Jiang Zhao, Huanhuan Liu, Biao Jin, Xuee Cui, Dengbin Wang

“…Materials and methods We developed a ResNet-based deep neural network model enhanced with Coordinate Attention mechanism to predict pediatric age from chest X-rays. …”
Get full text

Learning teamworking and non-technical skills: a pilot study of a postgraduate course at the University of Florence by Veronica Verde, Yari Bardacci, Lorenzo Ballerini, Samuele Baldassini Rodriguez, Chiara Balestri, Paolo Iovino, Simone Belli, Stefano Bambi

“…In healthcare systems, NTS exert positive effects on patients’ safety and healthcare professionals’ efficiency. …”
Get full text

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. …”
Get full text

Single-cell and machine learning approaches uncover intrinsic immune-evasion genes in the prognosis of hepatocellular carcinoma by Jiani Wang, Xiaopeng Chen, Donghao Wu, Changchang Jia, Qinghai Lian, Yuhang Pan, Jiumei Yang

“…To address these issues, single-cell technology and machine learning methods have emerged as a promising approach to identify genes associated with immune escape in HCC. …”
Get full text

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. …”
Get full text

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. …”
Get full text

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. …”
Get full text

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. …”
Get full text

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. …”
Get full text

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. …”
Get full text

BeatProfiler: Multimodal In Vitro Analysis of Cardiac Function Enables Machine Learning Classification of Diseases and Drugs by Youngbin Kim, Kunlun Wang, Roberta I. Lock, Trevor R. Nash, Sharon Fleischer, Bryan Z. Wang, Barry M. Fine, Gordana Vunjak-Novakovic

“…To accurately classify between these biological signals, we apply feature-based ML and deep learning models (temporal convolutional-bidirectional long short-term memory model or TCN-BiLSTM). …”
Get full text

Inclusive Excellence in Practice: Integrating Equitable, Consequential Learning and an Inclusive Climate in Higher Education Classrooms and Institutions by Susannah Davis, Susan Nolen, Milo Koretsky

“…The I2 Framework posits that DEIJ and learning goals need to be addressed simultaneously and at multiple, intersecting organizational levels. …”
Get full text

An Automated Framework for Lane Closure Detection on Highway Using Connected Vehicle Data and Machine Learning Models by Ashutosh Dumka, Raghupathi Kandiboina, Aparna Joshi, Skylar Knickerbocker, Neal Hawkins, Anuj Sharma

“…Lane closures on highways present significant challenges, including traffic disruptions, increased crash risks, and economic losses. The traditional methods, which use primarily manual reporting or sensor-based methods, can be error-prone, inefficient, and costly. …”
Get full text