Deep learning can predict cardiovascular events from liver imaging by Gregory Patrick Veldhuizen, Tim Lenz, Didem Cifci, Marko van Treeck, Jan Clusmann, Yazhou Chen, Carolin V. Schneider, Tom Luedde, Peter W. de Leeuw, Ali El-Armouche, Daniel Truhn, Jakob Nikolas Kather

“…Unlike traditional methods, no manual feature selection was required, minimizing bias. Performance was assessed via fivefold cross validation, where predicted risk scores were compared against actual cardiovascular outcomes. …”
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Group Forward–Backward Orthogonal Matching Pursuit for General Convex Smooth Functions by Zhongxing Peng, Gengzhong Zheng, Wei Huang

“…This paper introduces the Group Forward–Backward Orthogonal Matching Pursuit (Group-FoBa-OMP) algorithm, a novel approach for sparse feature selection. The core innovations of this algorithm include (1) an integrated backward elimination process to correct earlier misidentified groups; (2) a versatile convex smooth model that generalizes previous research; (3) the strategic use of gradient information to expedite the group selection phase; and (4) a theoretical validation of its performance in terms of support set recovery, variable estimation accuracy, and objective function optimization. …”
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A novel random forest-based approach for the non-destructive and explainable estimation of ammonia and chlorophyll in fresh-cut rocket leaves by Stefano Polimena, Gianvito Pio, Maria Cefola, Michela Palumbo, Michelangelo Ceci, Giovanni Attolico

“…Moreover, a specific analysis of the explainability of the predictions showed that the learned models are based on reasonable features, empowering their acceptance in real-world applications.…”
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Advanced Object Detection in Low-Light Conditions: Enhancements to YOLOv7 Framework by Dewei Zhao, Faming Shao, Sheng Zhang, Li Yang, Heng Zhang, Shaodong Liu, Qiang Liu

“…Cross-layer connection structures are established to reinforce critical information, enhancing feature representation. We use brightness-adjusted data augmentation and a novel bounding box loss function to improve detection performance. …”
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An automatic generalized Gaussian mixture-based approach for accurate brain tumor segmentation in magnetic resonance imaging analysis by Khalil Ibrahim Lairedj, Zouaoui Chama, Amina Bagdaoui, Samia Larguech, Serge Dzo Mawuefa Afenyiveh, Younes Menni

“…Image segmentation is crucial in medical science for feature extraction, analysis, and interpretation, especially brain tumor segmentation, which is challenging. …”
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A survey on deep learning-based lidar place recognition by Weizhong Jiang, Shubin Si, Hanzhang Xue, Yiming Nie, Zhipeng Xiao, Qi Zhu, Liang Xiao

“…It presents a coarse-to-fine classification framework to systematically categorize and review existing methods, based on two dimensions: input data structure and model architecture. Furthermore, this paper summarizes commonly used datasets and performance evaluation metrics, along with performance comparisons of representative methods. …”
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Harnessing InSAR and Machine Learning for Geotectonic Unit-Specific Landslide Susceptibility Mapping: The Case of Western Greece by Stavroula Alatza, Alexis Apostolakis, Constantinos Loupasakis, Charalampos Kontoes, Martha Kokkalidou, Nikolaos S. Bartsotas, Georgios Christopoulos

“…The gradient-boosted decision tree was employed in the landslide susceptibility mapping. The model was trained on three geotectonic units and five prefectures of Western Greece and performed well in predicting landslide events. …”
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A New Method for Solving Supervised Data Classification Problems by Parvaneh Shabanzadeh, Rubiyah Yusof

“…To improve classification performance and efficiency in generating classification model, a new feature selection algorithm based on techniques of convex programming is suggested. …”
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Implementasi Sistem Reminder Jadwal pada eLearning Moodle Berbasis API Menggunakan Framework Flutter by M. Yudha Putra, Dwi Ely Kurniawan

“…The development methodology employed is the waterfall model, while testing utilizes black-box testing and Firebase Test Lab. …”
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Enhancing Water Bodies Detection in the Highland and Coastal Zones Through Multisensor Spectral Data Fusion and Deep Learning by Xiaofei Han, Nazih Y. Rebouh, Yasmeen Ahmed, Muhammad Nasar Ahmad, Zainab Tahir, Yahia Said, Ishfaq Gujree

“…Both models were assessed using standard performance metrics, including precision, recall, <italic>F</italic>1-score, and intersection over union (IoU). …”
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A nomogram for predicting 3-year total weight loss percentage following LSG: insights from visceral adipose tissue inflammatory methylation sites by Zhehong Li, Liang Wang, Zheng Wang, Qiqige Wuyun, Buhe Amin, Dongbo Lian, Guangzhong Xu, Nengwei Zhang, Dezhong Wang

“…A nomogram was subsequently developed using these hub methylation sites. The model's performance was assessed through receiver operating characteristic (ROC) curve analysis with bootstrap resampling, calibration curves, decision curve analysis (DCA), and clinical impact curves (CIC). …”
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Ganoderma Disease in Oil Palm Trees Using Hyperspectral Imaging and Machine Learning by Chee Seng Kwang, Siti Fatimah Abdul Razak, Sumendra Yogarayan, M. Z. Adli Zahisham, Tze Huey Tam, M. K. Anuar Mohd Noor, Haryati Abidin

“…Future research will focus on collecting more data, incorporating temporal information for disease stage classification, and implementing a more robust machine learning (ML) model for performance enhancement. Overall, this research shows the great potential of hyperspectral imaging for accurate detection of Ganodermadisease in oil palm plantations.   …”
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PlutoNet: An efficient polyp segmentation network with modified partial decoder and decoder consistency training by Tugberk Erol, Duygu Sarikaya

“…Ablation studies and experiments are performed which show that PlutoNet performs significantly better than the state‐of‐the‐art models, particularly on unseen datasets.…”
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Hierarchical Swin Transformer Ensemble with Explainable AI for Robust and Decentralized Breast Cancer Diagnosis by Md. Redwan Ahmed, Hamdadur Rahman, Zishad Hossain Limon, Md Ismail Hossain Siddiqui, Mahbub Alam Khan, Al Shahriar Uddin Khondakar Pranta, Rezaul Haque, S M Masfequier Rahman Swapno, Young-Im Cho, Mohamed S. Abdallah

“…The model exhibits strong generalization and performs exceptionally well across five benchmark datasets—BreakHis, BUSI, INbreast, CBIS-DDSM, and a Combined dataset—achieving an F1 score of 99.34% on BreakHis, a PR AUC of 98.89% on INbreast, and a Matthews Correlation Coefficient (MCC) of 99.61% on the Combined dataset. …”
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TuSegNet: A Transformer-Based and Attention-Enhanced Architecture for Brain Tumor Segmentation by Mir Nafiul Nagib, Rahat Pervez, Afsana Alam Nova, Hadiur Rahman Nabil, Zeyar Aung, M. F. Mridha

“…Ablation studies validate the importance of ASPP and attention mechanisms, while comparative analysis demonstrates outstanding performance over existing SOTA models such as Swin UNet and TransUNet. …”
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UniText: A Unified Framework for Chinese Text Detection, Recognition, and Restoration in Ancient Document and Inscription Images by Lu Shen, Zewei Wu, Xiaoyuan Huang, Boliang Zhang, Su-Kit Tang, Jorge Henriques, Silvia Mirri

“…UniText operates at the character level and processes full-page inputs, making it robust to multi-scale, multi-oriented, and noise-corrupted text. The model adopts a multi-task architecture that integrates spatial localization, semantic recognition, and visual restoration through stroke-aware supervision and multi-scale feature aggregation. …”
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Characterization of microbiota signatures in Iberian pig strains using machine learning algorithms by Lamiae Azouggagh, Noelia Ibáñez-Escriche, Marina Martínez-Álvaro, Luis Varona, Joaquim Casellas, Sara Negro, Cristina Casto-Rebollo

“…ML models, particularly CB and RF, as well as SVM in certain scenarios, combined with a feature selection process, effectively classified genetic groups based on microbiome data and identified key microbial taxa. …”
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Whole genome resequencing reveals genetic diversity, population structure, and selection signatures in local duck breeds by Pengwei Ren, Yongdong Peng, Liu Yang, Muhammad Zahoor Khan, Yadi Jing, Chao Qi, Zhansheng Liu, Shuer Zhang, Nenzhu Zheng, Meixia Zhang, Xiang Liu, Zhiming Zhu, Mingxia Zhu

“…After comparing with meat duck breeds (BJ, CV, ML), we identified several potential functional genes (notably TP63, BMP3, and ACACA) associated with key economic traits, including growth and development, muscle quality, reproductive performance, and disease resistance. Using top 60 feature selected SNPs, the random forest classification model successfully identified different breeds of ducks under the study with 96.2% accuracy. …”
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ES-UNet: efficient 3D medical image segmentation with enhanced skip connections in 3D UNet by Minyoung Park, Seungtaek Oh, Junyoung Park, Taikyeong Jeong, Sungwook Yu

“…The model builds upon the full-scale skip connection design of UNet3+ by integrating channel attention modules into each encoder-to-decoder path and incorporating full-scale deep supervision to enhance multi-resolution feature learning. …”
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Daily-Scale Fire Risk Assessment for Eastern Mongolian Grasslands by Integrating Multi-Source Remote Sensing and Machine Learning by Risu Na, Byambakhuu Gantumur, Wala Du, Sainbuyan Bayarsaikhan, Yu Shan, Qier Mu, Yuhai Bao, Nyamaa Tegshjargal, Battsengel Vandansambuu

“…Model performance was enhanced using Bayesian hyperparameter optimization via Optuna. …”
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