Development and evaluation of customized software to automatically align macula and optic disc centered scanning laser ophthalmoscope fundus images by M. Elena Martinez-Perez, Franziska G. Rauscher, Pingping Zhao, Tobias Elze

“…Both methods were independently developed by different subgroups of authors of this study using a training dataset of 18,047 eyes from a population-based study. …”
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An Intraoperative Ultrasound Evaluation of Axillary Lymph Nodes: Cassandra Predictive Models in Patients with Breast Cancer—A Multicentric Study by Simona Parisi, Francesco Saverio Lucido, Federico Maria Mongardini, Roberto Ruggiero, Francesca Fisone, Salvatore Tolone, Antonio Santoriello, Francesco Iovino, Domenico Parmeggiani, David Vagni, Loredana Cerbara, Ludovico Docimo, Claudio Gambardella

“…In the second tier, if there was a mix of the results (SWES > 137 kPa and RI > 1.55 or SWES < 137 kPa and RI < 1.55), the algorithm in Model B was applied. The model demonstrated an overall prediction accuracy of 90.2% in the training set, 87.5% in the validation set, and 88.9% across the entire dataset. …”
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Evaluating Deep Learning and Machine Learning Models in Federated Learning for Credit Card Fraud Detection: A Comparative Study by Sener ALI

“…This study evaluates machine learning and deep learning algorithms for credit card fraud detection within a federated learning framework. …”
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Grading evaluation method for inter-turn short circuit of permanent magnet traction motor based on deep Gaussian processes by DAI Jisheng, HU Dean, XU Hailong, ZHU Wenlong, LIAO Qishu

“…Then, a doubly stochastic deep Gaussian processes (DSDGP) method was adopted to fuse and train the extracted features, achieving online grading evaluation of inter-turn short circuit degradation in permanent magnet traction motors. …”
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Berg Balance Scale Scoring System for Balance Evaluation by Leveraging Attention-Based Deep Learning with Wearable IMU Sensors by Zhangli Lu, Huiying Zhou, Honghao Lyu, Haiteng Wu, Shaohua Tian, Geng Yang

“…The Berg Balance Scale (BBS) is a widely used clinical tool for balance evaluation. However, its dependence on trained therapists for subjective, time-consuming assessments limits its scalability. …”
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Task based evaluation of sparse view CT reconstruction techniques for intracranial hemorrhage diagnosis using an AI observer model by Matthew Tivnan, Irene Désirée Kikkert, Dufan Wu, Kai Yang, Jelmer M. Wolterink, Quanzheng Li, Rajiv Gupta

“…Deep Learning Reconstruction (DLR) offers potential improvements, but task-based evaluations of DLR in sparse-view CT remain limited. …”
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Machine learning-based prediction of short- and long-term mortality for shared decision-making in older hip fracture patients: the Dutch Hip Fracture Audit algorithms in 74,396 cas... by Hidde Dijkstra, Cathleen S Parsons, Hanne-Eva VAN Bremen, Hanna C Willems, Anne A H De Hond, Barbara C van Munster, Job N Doornberg, Jacobien H F Oosterhoff

“…Predictive variables were selected based on the literature and/or clinical relevance. 6 ML algorithms, including logistic regression, were trained with internal cross-validation and evaluated on discrimination (c-statistic), sensitivity, specificity, calibration, and interpretability. …”
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Sensor-free, Camera-only: Low-cost multi-angle CPR skill assessments method based on computer vision by Longxin Liu, Cen Wu, Jiafeng Liu, Jiayi Yu, Meng Bi, Hong Yu

“…We propose the LCSG-YOLO model, an enhanced version of the YOLO11 algorithm, coupled with the Kalman-Hungarian-Confidence-Temporal (KCHT) matching algorithm. …”
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Distribution of University Admission Quotas: Problems of Competitive Selection Process by L. M. Nurieva, S. G. Kiselev

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State of Charge Estimation for Li-Ion Batteries: An Edge-Based Data-Driven Approach by Sesidhar Dvsr, Chandrashekhar Badachi, Chandrashekar Nagawaram, Panduranga Chary Kondoju, C. Dhanamjayulu, Innocent Kamwa

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Liver Disease Classification using the NAIVE BAYES by Vitra Nurhalisa, Ika Nur Fajri

“…The Bernoulli Naive Bayes model was then trained and evaluated using a confusion matrix and ROC-AUC analysis. …”
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Hybrid Machine Learning Model for Predicting Shear Strength of Rock Joints by Daxing Lei, Yaoping Zhang, Zhigang Lu, Hang Lin, Yifan Chen

“…To address these challenges, this study proposes a hybrid ML model that integrates a multilayer perceptron (MLP) with the slime mold algorithm (SMA), termed the SMA-MLP model. While MLP exhibits strong nonlinear mapping capability, SMA enhances its training process through global optimization and parameter tuning, thereby improving predictive accuracy and robustness. …”
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Artificial intelligence-assisted identification of condensing osteitis and idiopathic osteosclerosis on panoramic radiographs by Ibrahim Burak Yuksel, Amin Boudesh, Masoud Ghanbarzadehchaleshtori, Sumeyye Celik Ozsoy, Serkan Bahrilli, Reza Mohammadi, Ali Altindag

“…All images were standardized to a resolution of 640 × 640 pixels and segregated into training (70%), validation (15%), and testing (15%) subsets. …”
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Artificial intelligence-based assessment of surgical skills in laparoscopic right hemicolectomy for colon cancer by WEI Pengyu, GAO Jiale, JI Maotong, TAN Yuanyuan, YAO Hongwei

“…With the rapid advancement of artificial intelligence (AI) technologies (particularly breakthroughs in computer vision and deep learning algorithms), a revolutionary technical foundation has been established for developing objective and precise automated surgical evaluation systems. …”
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Potential of random forest machine learning algorithm for geological mapping using PALSAR and Sentinel-2A remote sensing data: A case study of Tsagaan-uul area, southern Mongolia by Munkhsuren Badrakh, Narantsetseg Tserendash, Erdenejargal Choindonjamts, Gáspár Albert

“…Geological mapping in remote and geologically complex regions can be substantially improved by integrating remote sensing data with machine learning algorithms. This study evaluates the effectiveness of the Random Forest algorithm for geological mapping in the Tsagaan-uul area of the Khatanbulag ancient massif, Mongolia, a region characterized by limited accessibility and sparse field data. …”
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Educational Technologies in Modern Higher Education Institutions (Analysis of Russian and Foreign Research and Practice) by N. V. Bordovskaia, E. A. Koshkina, N. A. Bochkina

“…It has been established that Russian authors are still more oriented towards describing the characteristics and algorithms of predominantly traditional educational technologies and their applicability, evaluating their effectiveness through influencing students’ professional and personal development and competent communication. …”
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Evaluation of Machine Learning Applications for the Complex Near-Critical Phase Behavior Modelling of CO₂–Hydrocarbon Systems by Daulet Magzymov, Meruyert Makhatova, Zhasulan Dairov, Murat Syzdykov

“…The objective of this study was to evaluate the capability of machine learning models to accurately predict complex near-critical phase behavior in CO₂–hydrocarbon systems, which are crucial for enhanced oil recovery and carbon storage applications. …”
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Evaluating accountability, transparency, and bias in AI-assisted healthcare decision- making: a qualitative study of healthcare professionals’ perspectives in the UK by Saoudi CE Nouis, Victoria Uren, Srushti Jariwala

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Statistical Evaluation of Smartphone-Based Automated Grading System for Ocular Redness Associated with Dry Eye Disease and Implications for Clinical Trials by Rodriguez JD, Hamm A, Bensinger E, Kerti SJ, Gomes PJ, Ousler III GW, Gupta P, De Moraes CG, Abelson MB

“…Expert graded scores were within one unit of the mean grade in over 85% cases, ensuring consistency and optimal training set for the predictive model. Models incorporating both features outperformed those using only redness, reducing MAE by 5– 6%. …”
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Machine learning model for classifying high school students’ academic performance in mathematics amidst the COVID-19 context by Gisella Luisa Elena Maquen-Niño, Moisés Alvin Miguel_Flores, Leysi Yarely Aurich_Mio, Ivan Adrianzén Olano, Percy Edwin De la Cruz Vélez de Villa, Diana Mercedes Castro Cárdenas

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