Human crime activity recognition and shooting weapon detection in video frames using the contour approximation algorithm, and FastDTW classifier by Y. V. K. Durga Bhavani, V. B. Pagi

“…The classifier evaluates the similarity between training and test vectors for Human Activity Recognition (HAR) and categorizes the crime. …”
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Design and application research of traditional Chinese medicine teaching resource recommendation system based on multivariate data mining driven algorithm by Wei Zhang, Yaqing Liu, Qiang Zhang, Xiaomin Chen

“…Teachers are able to optimize teaching content and evaluation; Managers can achieve scientific decision-making and quality monitoring, ultimately promote educational equity, activate characteristic resources, and promote the digital transformation of traditional Chinese medicine education and the improvement of the quality of talent training.…”
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Using machine learning algorithms to predict risk factors of heart failure after complete mesocolic excision in colorectal cancer patients by Yuan Liu, Yuankun Liu, Yu Zhang, Pengpeng Zhang, Jiaheng Xie, Ning Zhao, Yi Xie, Chao Cheng, Songyun Zhao

“…The k-fold cross-validation method, ROC curve, calibration curve, decision curve analysis (DCA), and external validation were employed for comprehensive model evaluation. The XGBoost algorithm exhibited superior performance compared to the other three prediction models. …”
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A novel decision algorithm for the innovation and optimization in university labor education courses using fuzzy information involving multiple experts by Hailun Liu

“…Several organizations plan to train their labor through training programs, workshops, and courses. …”
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Sentiment Analysis of User Reviews of the KitaLulus Application on Google Play Store using the Support Vector Machine (SVM) Algorithm by Ahmad Syaifudin Agil Rafsanjani, Diana Laily Fithri, Supriyono Supriyono

“…The research process includes collecting 1,000 user reviews through web scraping, text preprocessing, rating-based labeling, data transformation using TF-IDF, splitting the dataset into 80% training and 20% testing, applying SMOTE, training the SVM model, and evaluating its performance. …”
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An evaluation methodology for machine learning-based tandem mass spectra similarity prediction by Michael Strobel, Alberto Gil-de-la-Fuente, Mohammad Reza Zare Shahneh, Yasin El Abiead, Roman Bushuiev, Anton Bushuiev, Tomáš Pluskal, Mingxun Wang

“…Machine learning (ML) approaches have emerged as a promising technique to predict structural similarity from MS/MS that may surpass the current state-of-the-art algorithmic methods. However, the comparison between these different ML methods remains a challenge because there is a lack of standardization to benchmark, evaluate, and compare MS/MS similarity methods, and there are no methods that address data leakage between training and test data in order to analyze model generalizability. …”
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Development of a prediction model for chemotherapy and immunotherapy response in esophageal squamous cell carcinoma patients using machine learning algorithms by CHEN Jincheng, ZHANG Xiaoqin, LIU Jie

“…Five-fold cross-validation was conducted on the training set, and the performance of the prediction models was evaluated on the testing set using receiver operating characteristic (ROC) curve and the F1 score. …”
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Integration of ground-based and remote sensing data with deep learning algorithms for mapping habitats in Natura 2000 protected oak forests by Lucia Čahojová, Ivan Jarolímek, Barbora Klímová, Michal Kollár, Michaela Michalková, Karol Mikula, Aneta A. Ožvat, Denisa Slabejová, Mária Šibíková

“…A dataset was selected for the training of a deep learning algorithm called the Natural Numerical Network on the basis of the analysis results. …”
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Data Collection for Automatic Depression Identification in Spanish Speakers Using Deep Learning Algorithms: Protocol for a Case-Control Study by Luis F Brenes, Luis A Trejo, Jose Antonio Cantoral-Ceballos, Daniela Aguilar-De León, Fresia Paloma Hernández-Moreno

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A Two-Level Rule-Mining Approach to Classify Breast Cancer Patterns Using Adaptive Directed Mutation and Genetic Algorithm by Hui-Ching Wu, Ming-Hseng Tseng

“…For physicians to understand the classification and decision rules and to evaluate their results, it is preferable to use white box approaches to develop prediction models. …”
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Fine-Grained Classification of Pressure Ulcers and Incontinence-Associated Dermatitis Using Multimodal Deep Learning: Algorithm Development and Validation Study by Alexander Brehmer, Constantin Seibold, Jan Egger, Khalid Majjouti, Michaela Tapp-Herrenbrück, Hannah Pinnekamp, Vanessa Priester, Michael Aleithe, Uli Fischer, Bernadette Hosters, Jens Kleesiek

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Development of a prediction model for acute respiratory distress syndrome in ICU patients with acute pancreatitis based on machine learning algorithms by REN Xia*，LIU Luojie，ZHA Junjie，YE Ye，XU Xiaodan，YE Hongwei，ZHANG Yan

“…"Objective To develop and validate a predictive model based on machine learning algorithms to assess the risk of acute respiratory distress syndrome（ARDS）in patients with acute pancreatitis（AP）admitted to the intensive care unit（ICU）. …”
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Long-term prediction of wind speed in La Serena City (Chile) using hybrid neural network-particle swarm algorithm by Juan A Lazzús, Ignacio Salfate

“…Several neural network architectures were studied, and the optimum architecture was determined by adding neurons in systematic form and evaluating the root mean square error (RMSE) during the learning process. …”
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Decision Tree for Determining Hospital Treatment for Covid-19 Patients Based on Hematology Parameters Using the C5.0 Algorithm by Joko Riyono, Christina Eni Pujiastuti, Supriyadi Supriyadi, Dody Prayitno, Aina Latifa Riyana Putri

“…Performance evaluated using the Confusion Matrix method produces an accuracy value of 78% which is considered quite good, where testing with the C5.0 Algorithm uses a training and testing data ratio of 40:60. …”
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Comparative Analysis of Machine Learning Algorithms for Potential Evapotranspiration Estimation Using Limited Data at a High-Altitude Mediterranean Forest by Stefanos Stefanidis, Konstantinos Ioannou, Nikolaos Proutsos, Ilias Karmiris, Panagiotis Stefanidis

“…Accurate estimation of potential evapotranspiration (PET) is of paramount importance for water resource management, especially in Mediterranean mountainous environments that are often data-scarce and highly sensitive to climate variability. This study evaluates the performance of four machine learning (ML) regression algorithms—Support Vector Regression (SVR), Random Forest Regression (RFR), Gradient Boosting Regression (GBR), and K-Nearest Neighbors (KNN)—in predicting daily PET using limited meteorological data from a high-altitude in Central Greece. …”
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The dosimetric impacts of ct-based deep learning autocontouring algorithm for prostate cancer radiotherapy planning dosimetric accuracy of DirectORGANS by Serap Çatlı Dinç, Aybala Nur Üçgül, Hüseyin Bora, Ertuğrul Şentürk

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Optimizing water demand in citrus orchards: a novel model using evolutionary algorithms on Sentinel-1 time series data by Emilio-José Cabello-Franco, Daniel Antón, Emilio Ramírez-Juidias, Francisco Perea-Torres

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Deep Learning-Based Real-Time 6D Pose Estimation and Multi-Mode Tracking Algorithms for Citrus-Harvesting Robots by Hyun-Jung Hwang, Jae-Hoon Cho, Yong-Tae Kim

“…Additionally, we present methods for training an EfficientPose-based model for 6D pose estimation and ripeness classification, and an algorithm for determining the optimal harvest sequence among multiple fruits. …”
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Extreme gradient and boosting algorithm for improved bias-correction and downscaling of CMIP6 GCM data across indian river basin by Chandni Thakur, Venkatesh Budamala, KS Kasiviswanathan, Claudia Teutschbein, Bankaru-Swamy Soundharajan

“…Additionally, both methods were evaluated across different seasons, including monsoon, pre-monsoon, and post-monsoon. …”
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Improve carbon dioxide emission prediction in the Asia and Oceania (OECD): nature-inspired optimisation algorithms versus conventional machine learning by Loke Kok Foong, Vojtech Blazek, Lukas Prokop, Stanislav Misak, Farruh Atamurotov, Nima Khalilpoor

“…Through comprehensive experimentation, the study evaluates the performance of each combination, revealing varying effectiveness levels. …”
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