Class Incremental Learning With Large Domain Shift by Kamin Lee, Hyoeun Kim, Geunjae Choi, Hyejeong Jeon, Nojun Kwak

“…We address an important and practical problem facing deep-learning-based image classification: class incremental learning with a large domain shift. …”
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SBOA: A Novel Heuristic Optimization Algorithm by Qi Diao, Apri Junaidi, WengHowe Chan, Azland Mohd Zain Zain, Hao long Yang

“… A new human-based heuristic optimization method, named the Snooker-Based Optimization Algorithm (SBOA), is introduced in this study. …”
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Predicting abatacept retention using machine learning by Rieke Alten, Claire Behar, Pierre Merckaert, Ebenezer Afari, Virginie Vannier-Moreau, Anael Ohayon, Sean E. Connolly, Aurélie Najm, Pierre-Antoine Juge, Gengyuan Liu, Angshu Rai, Yedid Elbez, Karissa Lozenski

“…Abstract Background The incorporation of machine learning is becoming more prevalent in the clinical setting. …”
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Impact of serum calcium levels on the occurrence of sepsis and prognosis in hospitalized patients with concomitant psoriasis: a retrospective study based on the MIMIC-IV database by Xiaolong Zheng, Qianjin Su, Yedi Wang, Xuefeng Geng

“…Machine learning techniques, along with logistic regression, Cox regression, group-based trajectory modeling (GBTM), and mediation analysis, were employed to assess the influence of serum calcium levels and other clinical indicators on the occurrence of sepsis and all-cause mortality.ResultsSerum calcium exhibits a significant inverse correlation with the occurrence of sepsis [odds ratio (OR) =0.351, 95% CI: 0.265-0.463, P<0.001]. …”
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Linking Electrocardiogram and Echocardiogram: Comparing Classical Machine Learning and Deep Learning Neural Networks for the Detection of Regional Wall Motion Abnormalities by Shantanu M. Joshi, Hana R. Shaik, Shivam Rai Sharma, Philip Strong, Uma Srivatsa, Imo Ebong, Hyoyoung Jeong, Chen-Nee Chuah, Lihong Mo

“…Our study aimed to predict RWMA using both classical machine learning (ML) methods and a one-dimensional convolutional neural network (1D CNN) model on the 12-lead ECG data from 3,750 unique patients provided by the Nightingale Open Science platform. …”
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Prenatal detection of congenital heart defects using the deep learning-based image and video analysis: protocol for Clinical Artificial Intelligence in Fetal Echocardiography (CAIF... by Aris Papageorghiou, Aris T Papageorghiou, David Black, Lawrence Impey, Rachel Craik, Alison Noble, Rahul Ahuja, Christina Aye, Christos Ioannou, Beverly Tsai-Goodman, Kevin Roman, Anupama Nair, Jessica Farmer, J Alison Noble, Makrina Savvidou, Bernadette Brent, Julene Carvalho, Olga Patey, Netzahualcoyotl Hernandez-Cruz, Elena D’Alberti, Bojana Salovic, Theophilus Adu-Bredu, Ilaria Bo, Angelo Cavallaro, FabricioDa SivaCosta, Emma Eccleston, Joanne Everingham, CristianeDe FreitasPaganoti, Eleni Fotaki, Tyrrell Hatch, Joanna Kellett, Karina Lopes, Sally Mahler, Risa Miyazaki Sankar, Divyanshu Mishra, Jennifer Norville, Olivia Nunn, Lola Oshodi, Stavros Polyviou, Lorjah Rajah, Daifenir Rodriguezde LaCruz, Katja Shipp, Bethany Shobbrook, Sophie Tooth, Dimuthu Weerasuriya, Qianye Yang, Yingyu Yang

“…Research has shown that deep learning-based or more general artificial intelligence (AI) models can support the detection of fetal CHDs more rapidly than humans performing ultrasound scan. …”
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Develoment of The Computer Simulation of Oscillation in Physics Learning by Y Sumardi, A F Amalia, U N Prabowo

“…This research aimed to develop the computer simulation of oscillation in physics learning by using MATLAB. The use of simulations within teaching process had a positive impact on students’ being able to predict and explain the phenomena. …”
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Prediction of particulate matter PM2.5 level in the air of Islamabad, Pakistan by using machine learning and deep learning approaches by Muhammad Waqas, Shahid Noor Jan, Basir Ullah, Afed Ullah Khan, Ateeq Ur Rauf, Bakht Niaz Khan

“…This study focused on predicting PM2.5 in the air of Islamabad, capital of Pakistan by using machine learning and deep learning models. Materials and methods: Two machine learning models (Decision Tree and Random Forest) and four deep learning models including Multi-Layer Neural Network (MLNN), Long Short-Term Memory (LSTM), Recurrent Neural Network (RNN), Gated Recurrent Unit (GRU) are used in the study. …”
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Whole-Body 3D Pose Estimation Based on Body Mass Distribution and Center of Gravity Constraints by Fan Wei, Guanghua Xu, Qingqiang Wu, Penglin Qin, Leijun Pan, Yihua Zhao

“…The method maps the pose to the center of gravity position using the anatomical mass ratio of the human body and computes the segment-level center of gravity using the moment synthesis method. …”
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Examining predictors of perceived usefulness of learning management system from the perspectives of distance learning students: an application of the information success model by Amjid Khan, Arshad Hussain Afridi, Muhammad Kamal Khan, Pervaiz Ahmad

“…These empirical results have proved that online and distance learning (ODL) students in Pakistan are adopting web-based integrated systems and/or LMS to fulfill their educational and learning needs. …”
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Development and interpretation of machine learning-based prognostic models for predicting high-risk prognostic pathological components in pulmonary nodules: integrating clinical fe... by Dingxin Wang, Jianhao Qiu, Rongyang Li, Hui Tian

“…Lasso regression was utilized in order to identify key features, and a machine learning prediction model was constructed based on the screened key features. …”
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How do residents perceive urban parks? A cross-geographic comparison based on online reviews by Lijuan Yang, Qiuhong Wu

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Self-talk (positive and negative) and its relationship to Athletic Fears withen the advanced players of Mosul City Center club’s by هشام محمد علي السيدية أ.د ثامر محمود ذنون

“…Designing an advisory program based on positive self-talk to reduce the degree of sports concerns among the advanced players in the Mosul City Centre clubs. …”
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Intra- and peri-tumoral radiomics based on dynamic contrast-enhanced MRI for prediction of benign disease in BI-RADS 4 breast lesions: a multicentre study by Yalan Hu, Zhenhai Cai, Nijiati Aierken, Yueqi Liu, Nan Shao, Yawei Shi, Mengmeng Zhang, Yangling Hu, Xiaoling Zhang, Ying Lin

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Image-Based Detection and Classification of Malaria Parasites and Leukocytes with Quality Assessment of Romanowsky-Stained Blood Smears by Jhonathan Sora-Cardenas, Wendy M. Fong-Amaris, Cesar A. Salazar-Centeno, Alejandro Castañeda, Oscar D. Martínez-Bernal, Daniel R. Suárez, Carol Martínez

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DSMF-Net: A One-Stage SAR Ship Detection Network Based on Deformable Strip Convolution and Multiscale Feature Refinement and Fusion by Xingyu Liu, Jun Pan, Rong Hu, Wenli Huang, Jiawei Lin, Jiarui Hu

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YOLOv9-Based Human Face Detection and Counting Under Human-Animal Faces, Complex Imaging Environments, and Image Qualities by Sivaranjini Perikamana Narayanan, M. Sabarimalai Manikandan, Linga Reddy Cenkeramaddi

“…Evaluation results demonstrate that the YOLOv9-based face counting outperforms most of the state-of-the-art face detection and people counting methods with a mean absolute error (MAE) of 3.36 and root mean square error (RMSE) of 22.38. …”
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JEDAN: Joint Euclidean Distance and Autoencoder Network for Robust Out-of-Distribution Detection in Radar-Based Hand Gesture Recognition by Muhammad Ghufran Janjua, Kevin Kaiser, Thomas Stadelmayer, Stephan Schoenfeldt, Vadim Issakov

“…To the best of our knowledge, this is the first OOD detection architecture specifically tailored for radar-based gesture recognition that integrates the strengths of Euclidean distance-based layer and reconstruction-based OOD methods in a unified framework, paving the way for more robust real-world applications.…”
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MFAFNet: Multi-Scale Feature Adaptive Fusion Network Based on DeepLab V3+ for Cloud and Cloud Shadow Segmentation by Yijia Feng, Zhiyong Fan, Ying Yan, Zhengdong Jiang, Shuai Zhang

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Identification and validation of tissue-based gene biomarkers for acute intestinal graft-versus-host disease(AIGVHD) by Hong Chen, Hong Chen, Hong Chen, Hong Chen, Hong Chen, Hong Chen, Liyu Fu, Liyu Fu, Liying Liu, Liying Liu, Yunyan He, Yunyan He, Yunyan He, Yunyan He, Yunyan He

“…The primary aim of the present study is to identify tissue-based gene biomarkers pertinent to AIGVHD, thereby facilitating early diagnosis and exploration of potential therapeutic targets.MethodThe dataset was obtained from the GEO database. …”
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