Improvement on Distinguishing ‘B’ and ‘D’ Letter : Direct Instruction Flashcards Intervention for A Slow Learner by Siti Dwita Anjani, Farida Kurniawati

“…Observations during treatment sessions provided qualitative insights into the subject's learning process, highlighting specific challenges and strategies that enhanced performance. …”
Get full text

Cloud and IoT based smart agent-driven simulation of human gait for detecting muscles disorder by Sina Saadati, Abdolah Sepahvand, Mohammadreza Razzazi

“…Additionally, a deep learning-based ensemble framework is proposed to assist in the analysis of the simulation results, offering both accuracy and interpretability. …”
Get full text

Feature Selection with Graph Mining Technology by Thosini Bamunu Mudiyanselage, Yanqing Zhang

“…In this case, they only use wrapper techniques that require a learning algorithm to select features. It is important to note that our experimental results indicates, this proposed simple ranking method performs better than other methods, independent of any particular learning algorithm used.…”
Get full text

Semi-Supervised Hybrid Local Kernel Regression for Soft Sensor Modelling of Rubber-Mixing Process by Haiqing Yu, Jun Ji, Ping Li, Fengjing Shao, Shunyao Wu, Yi Sui, Shujing Li, Fengjiao He, Jinming Liu

“…Meanwhile, traditional global learning algorithms suffer from the outdated samples while online learning algorithms lack practicality since too many labelled samples of current batch are required to build the soft sensor. …”
Get full text

Interpretable DWT-1DCNN-LSTM Network for Power Quality Disturbance Classification by Shuangquan Yang, Tao Shan, Xiaomei Yang

“…Accurate identification of these disturbances is crucial for effective grid management and protection. Although deep learning methods have high accuracy, their lack of interpretability can limit their acceptance in engineering applications. …”
Get full text

The Diagnostic and Predictive Significance of Immune-Related Genes and Immune Characteristics in the Occurrence and Progression of IgA Nephropathy by Jian-Bo Qing, Wen-Zhu Song, Chang-Qun Li, Ya-Feng Li

“…Finally, ssGSEA analysis was performed on the GSE141295 dataset to discover the abnormal inflammation in IgAN. Results. Machine learning (ML) performed excellently in diagnosing IgAN using six DIRGs. …”
Get full text

A pediatric emergency prediction model using natural language process in the pediatric emergency department by Arum Choi, Chohee Kim, Jisu Ryoo, Jangyeong Jeon, Sangyeon Cho, Dongjoon Lee, Junyeong Kim, Changhee Lee, Woori Bae

“…Abstract This study developed a predictive model using deep learning (DL) and natural language processing (NLP) to identify emergency cases in pediatric emergency departments. …”
Get full text

LASSO–MOGAT: a multi-omics graph attention framework for cancer classification by Fadi Alharbi, Aleksandar Vakanski, Murtada K. Elbashir, Mohanad Mohammed

“… The application of machine learning (ML) methods to analyze changes in gene expression patterns has recently emerged as a powerful approach in cancer research, enhancing our understanding of the molecular mechanisms underpinning cancer development and progression. …”
Get full text

Classification-augmented survival estimation (CASE): A novel method for individualized long-term survival prediction with application to liver transplantation. by Hamed Shourabizadeh, Dionne M Aleman, Louis-Martin Rousseau, Katina Zheng, Mamatha Bhat

“…We improve upon traditional survival machine learning approaches through a novel framework called classification-augmented survival estimation (CASE), which treats survival as a classification task that ultimately yields survival curves, beginning with dataset augmentation to improve class imbalance for use with any classification model. …”
Get full text

The Efficiency of Chitosan Against Tert Butylhydroquinone (TBHQ)-Induced Neurobehavioral Changes and Toxicity Effects in Male Rats by Shahad Alahmadi, Mohammed Mufadhe Alanazi, Fawaz Alasmari, Wedad Saeed Al-Qahtani, Gadah Albasher

“…Behavioral tests, including the Morris Water Maze (MWM) as well as Passive Avoidance Learning (PAL) tasks, confirmed memory and learning deficits in the TBHQ group. …”
Get full text

Design and Evaluation of a Leader–Follower Isomorphic Vascular Interventional Surgical Robot by Pengfei Chen, Yutang Wang, Dapeng Tian

“…Subsequently, the cumulative sum (CUSUM) method was used to evaluate the learning curve of the robot system, demonstrating that both operators could master the operation method within 10 trials. …”
Get full text

Using Artificial Intelligence to Analyze Nature of Science Themes: Einstein and Eddington Documentary Film Example by Yusuf Kartal, Munise Seckin-Kapucu

“…In a technology and media-oriented environment, text-processing algorithms and various artificial learning approaches are crucial and continue to develop. …”
Get full text

SaliencyMix+: Noise-Minimized Image Mixing Method With Saliency Map in Data Augmentation by Hajeong Lee, Zhixiong Jin, Jiyoung Woo, Byeongjoon Noh

“…Data augmentation is vital in deep learning for enhancing model robustness by artificially expanding training datasets. …”
Get full text

The use of artificial intelligence in induced pluripotent stem cell-based technology over 10-year period: A systematic scoping review. by Quan Duy Vo, Yukihiro Saito, Toshihiro Ida, Kazufumi Nakamura, Shinsuke Yuasa

“…The integration of artificial intelligence (AI), especially machine learning (ML) and deep learning (DL), has played a pivotal role in refining iPSC classification, monitoring cell functionality, and conducting genetic analysis. …”
Get full text

An Ecolevel Estimation Method of Individual Driver Performance Based on Driving Simulator Experiment by Yiping Wu, Xiaohua Zhao, Ying Yao, Jian Rong

“…Because of obvious advantage in mining hidden relationship, machine learning was adopted to explore the complicated relationship between driver performance and vehicle fuel consumption and thus to predict the ecolevel of individual driver performance in this study. …”
Get full text

Factors Associated with Women’s Chronic Disease Management: Associations of Healthcare Frustrations, Physician Support, and Self-Care Needs by Matthew Lee Smith, Marcia G. Ory, SangNam Ahn, Toni P. Miles

“…Women who were non-White (OR=2.26, P=0.049) were more likely to need help learning how to better manage their health. Those who had some college education or more (OR=0.55, P=0.044) and lower healthcare-related frustrations (OR=0.44, P=0.017) and perceived to have more physician support (OR=0.49, P=0.033) were less likely to need help learning how to better manage their health. …”
Get full text

Project Approach to the Implementation of Individual Educational Paths in Modern University by Yu. V. Daneykin, O. E. Kalpinskaya, N. G. Fedotova

“…The awareness of individualization of learning is determined by the project approach, while the individual educational path becomes more conscious and logical for the student, provoking his (her) educational needs and providing the need for the development of certain competencies. …”
Get full text

Automatic Detection of Cracks in Cracked Tooth Based on Binary Classification Convolutional Neural Networks by Juncheng Guo, Yuyan Wu, Lizhi Chen, Guanghua Ge, Yadong Tang, Wenlong Wang

“…By comparing validation accuracy under seven different learning rates, 10−5 is chosen as the best learning rate for the following testing process. …”
Get full text

Fish oocyte morphology detection using neural networks: a comparison of YOLO architectures by Yanna Leidy Ketley Fernandes Cruz, Ewaldo Eder Carvalho Santana, Isa Rosete Araujo Nascimento, Antonio Fhillipi Maciel Silva, Raimunda Nonata Fortes Carvalho Neta, José Ribamar de Souza Torres-Junior

“…With the development of deep learning techniques, automatic object detection has become an important mechanism for this task. …”
Get full text

Unlocking precision medicine: clinical applications of integrating health records, genetics, and immunology through artificial intelligence by Yi-Ming Chen, Tzu-Hung Hsiao, Ching-Heng Lin, Yang C. Fann

“…Deep learning techniques have significantly advanced variant calling, pathogenicity prediction, splicing analysis, and MHC-peptide binding predictions in genetics. …”
Get full text