Assessing dengue forecasting methods: a comparative study of statistical models and machine learning techniques in Rio de Janeiro, Brazil by Xiang Chen, Paula Moraga

“…Employing a dynamic window approach, various statistical methods and machine learning techniques were used to generate weekly forecasts at several time horizons. …”
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Comparison of machine learning methods for Predicting 3-Year survival in elderly esophageal squamous cancer patients based on oxidative stress by Jin-Biao Xie, Shi-Jie Huang, Tian-Bao Yang, Wu Wang, Bo-Yang Chen, Lianyi Guo

“…Methods This study included elderly patients with ESCC who underwent curative ESCC resection surgery continuously from January 2013 to December 2020 and were stratified into the training and external validation cohorts. …”
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Development and Validation of a Questionnaire to Assess the Level of Salt Intake in the Adult Population of the Russian Federation Using Machine Learning Methods by D. O. Dragunov, A. V. Sokolova, G. P. Arutjunov

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Deep Learning in Medical Imaging: Chronological Evolution, Frameworks, Core Methods, and Recent Advances in Breast Cancer Segmentation (2023–2024) by Youness Riouali, Naoual El Aboudi, Nezha El Bahaoui, Othman Arsalan, Fouad Tijami, Hafid Hachi, Youssef Omor, Rachida Latib, Laila Benhlima

“…The studies reviewed span the period from January 2023 to April 2024, concentrating on the latest deep learning methods proposed for breast cancer segmentation. …”
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Exploring the association between volatile organic compound exposure and chronic kidney disease: evidence from explainable machine learning methods by Liyan Jiang, Hongling Wang, Yang Xiao, Linlin Xu, Huoying Chen

“…Analytical methods included multivariable logistic regression, LASSO regression, and five machine learning models: Logistic Regression (LR), Random Forest (RF), Extreme Gradient Boosting (XGBoost), K-Nearest Neighbors (KNN), and Multilayer Perceptron (MLP). …”
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Learning from electronic prescribing errors: a mixed methods study of junior doctors’ perceptions of training and individualised feedback data by Bryony Dean Franklin, Monsey McLeod, Ann Chu, Arika Kumar, Geraldine Depoorter

“…Objectives To explore the views of junior doctors towards (1) electronic prescribing (EP) training and feedback, (2) readiness for receiving individualised feedback data about EP errors and (3) preferences for receiving and learning from EP feedback.Design Explanatory sequential mixed methods study comprising quantitative survey (phase 1), followed by interviews and focus group discussions (phase 2).Setting Three acute hospitals of a large English National Health Service organisation.Participants 25 of 89 foundation year 1 and 2 doctors completed the phase 1 survey; 5 participated in semi-structured interviews and 7 in a focus group in phase 2.Results Foundation doctors in this mixed methods study reported that current feedback provision on EP errors was lacking or informal, and that existing EP training and resources were underused. …”
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Assessment of ChatGPT-4 in Family Medicine Board Examinations Using Advanced AI Learning and Analytical Methods: Observational Study by Anthony James Goodings, Sten Kajitani, Allison Chhor, Ahmad Albakri, Mila Pastrak, Megha Kodancha, Rowan Ives, Yoo Bin Lee, Kari Kajitani

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Transforming Education: Case-Based Integrated Learning Development and Implementation – A Mixed Methods Study at a Private Medical College by RAHILA ALI, AZAM AFZAL, SARA SHAKIL, AMBER SULTAN, SHAZIA BABAR, JAVERIA REHMAN, MARIB GHULAM RASOOL MALIK, MOHAMMAD SHAHZAIB QADIR, SADAF KHAN, SANA SAEED

“…Introduction: Case-based learning (CBL) is widely used in medical education to bridge theory and practice, but traditional methods often struggle to sustain student engagement and promote critical thinking. …”
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Preparation of land subsidence susceptibility map using machine learning methods based on decision tree (case study: Isfahan–Borkhar) by Negar Ghasemi, Iman Khosravi, Ali Bahrami

“…Using remote sensing techniques, particularly radar interferometry (InSAR), this study investigates subsidence rates over the 2019–2023 period. Advanced machine learning methods, namely Decision Tree (DT), Random Forest (RF), and Extreme Gradient Boosting (XGBoost) are employed to develop a susceptibility map divided into five probability classes: very high, high, medium, low, and very low. …”
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Fine-tuning optimization of poly lactic acid impact strength with variation of plasticizer using simple supervised machine learning methods by Jaka Fajar Fatriansyah, Elvi Kustiyah, Siti Norasmah Surip, Andreas Federico, Agrin Febrian Pradana, Aniek Sri Handayani, Mariatti Jaafar, Donanta Dhaneswara

“…Three machine learning (ML) methods were used to fine-tune and optimize the impact strength of polylactic acid (PLA) with different plasticizers: KNN (K-nearest neighbors), SVR (Support Vector Regression), and ANN (artificial neural networks). …”
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Tumor tissue-of-origin classification using miRNA-mRNA-lncRNA interaction networks and machine learning methods by Ankita Lawarde, Ankita Lawarde, Masuma Khatun, Prakash Lingasamy, Prakash Lingasamy, Andres Salumets, Andres Salumets, Andres Salumets, Vijayachitra Modhukur, Vijayachitra Modhukur

“…Despite their established influence on tumor progression and therapeutic resistance, the application of miRNA interaction networks for tumor tissue-of-origin (TOO) classification remains underexplored.MethodsWe developed a machine learning (ML) framework that integrates miRNA-mRNA-lncRNA interaction networks to classify tumors by their tissue of origin. …”
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Improving Pairs Trading Strategies Using Two-Stage Deep Learning Methods and Analyses of Time (In)variant Inputs for Trading Performance by Wei-Lun Kuo, Wei-Che Chang, Tian-Shyr Dai, Ying-Ping Chen, Hao-Han Chang

“…This paper develops a two-stage deep learning method to improve the investment performance of a PTS. …”
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Non-destructive Weight Prediction Model of Spherical Fruits and Vegetables using U-Net Image Segmentation and Machine Learning Methods by Halil Kayra, Savaş Koç

“…Prediction of body weight in animals and plants has been done by humans using many different methods and observations from the past to the present. …”
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Design of BCC/FCC dual-solid solution refractory high-entropy alloys through CALPHAD, machine learning and experimental methods by Longjun He, Chaoyue Wang, Mina Zhang, Jinghao Li, Tianlun Chen, Xianglin Zhou

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Prediction of Clavien Dindo Classification ≥ Grade III Complications After Epithelial Ovarian Cancer Surgery Using Machine Learning Methods by Aysun Alci, Fatih Ikiz, Necim Yalcin, Mustafa Gokkaya, Gulsum Ekin Sari, Isin Ureyen, Tayfun Toptas

“…The aim of this single-centre, retrospective study was to determine the best method for predicting Clavien–Dindo grade ≥ III complications using machine learning techniques. …”
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In-depth investigation of contributing factors of fatal/severe-injury crashes at highway merging areas using machine learning classification methods by Nischal Bhattarai, Ciyun Lin, Yibin Zhang, Hongchao Liu

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A Comprehensive Model for Quantifying, Predicting, and Evaluating Ship Emissions in Port Areas Using Novel Metrics and Machine Learning Methods by Filip Bojić, Anita Gudelj, Rino Bošnjak

“…In the second module, the Multivariate Adaptive Regression Splines (MARS) machine learning method is adapted to predict emissions in varying operational scenarios. …”
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Deep-Learning Methods for Defect Inspection of Plated Through Holes With Clustering-Based Auto-Labeling and GAN-Based Model Training by Chang-Yeh Hsieh, Ling-Shen Tseng, Yi-Han Chen, Chiung-Hui Tsai, Chih-Hung Wu

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Alzheimer’s Prediction Methods with Harris Hawks Optimization (HHO) and Deep Learning-Based Approach Using an MLP-LSTM Hybrid Network by Raheleh Ghadami, Javad Rahebi

“…Early diagnosis is essential for timely medical intervention, with MRI medical imaging serving as a primary diagnostic tool. Machine learning (ML) and deep learning (DL) methods are increasingly utilized to analyze these images, but accurately distinguishing between healthy and diseased states remains a challenge. …”
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Perspectives, preparedness and challenges of the abrupt transition of emergency online learning to traditional methods in higher education of Bangladesh in the post-pandemic era by Bithi Mojumder, Md. Jasim Uddin, Kamol Dey

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