Predicting cardiotoxicity in drug development: A deep learning approach by Kaifeng Liu, Huizi Cui, Xiangyu Yu, Wannan Li, Weiwei Han

“…We used four types of molecular fingerprints and descriptors combined with machine learning and deep learning algorithms, including Gaussian naive Bayes (NB), random forest (RF), support vector machine (SVM), K-nearest neighbors (KNN), eXtreme gradient boosting (XGBoost), and Transformer models, to build predictive models. …”
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Predictive direct control strategy of unified power quality conditioner based on power angle control by Guifeng Wang, Zewen Wu, Zhan Liu

“…This approach simplifies the controller structure and alleviates the control algorithm’s complexity. Based on a detailed analysis of the PAC mechanism, an instantaneous power angle determination method is proposed based on the reactive power equalization technique, and a predictive direct control strategy given the current generation mechanism is constructed for the series and shunt sides of the UPQC, considering the active power balance of the UPQC system and the principle of constant load fundamental voltage amplitude. …”
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Machine Learning and Multilayer Perceptron-Based Customized Predictive Models for Individual Processes in Food Factories by Byunghyun Lim, Dongju Kim, Woojin Cho, Jae-Hoi Gu

“…Additionally, it proposes a customized predictive model employing four machine learning algorithms—linear regression, decision tree, random forest, and k-nearest neighbor—as well as two deep learning algorithms: long short-term memory and multi-layer perceptron. …”
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Prediction of Airline Ticket Price Using Machine Learning Method by Hüseyin Korkmaz

“…This paper aims to predict ticket prices based on airline flight data using ML algorithms and to compare the performance of ML algorithms. …”
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Protein structure prediction via deep learning: an in-depth review by Yajie Meng, Zhuang Zhang, Chang Zhou, Xianfang Tang, Xinrong Hu, Geng Tian, Jialiang Yang, Yuhua Yao, Yuhua Yao, Yuhua Yao

“…The application of deep learning algorithms in protein structure prediction has greatly influenced drug discovery and development. …”
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Early gestational diabetes mellitus risk predictor using neural network with NearMiss by Min Zhao, Xiaojie Su, Lihong Huang

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Sizing and Characterization of Load Curves of Distribution Transformers Using Clustering and Predictive Machine Learning Models by Pedro Torres-Bermeo, Kevin López-Eugenio, Carolina Del-Valle-Soto, Guillermo Palacios-Navarro, José Varela-Aldás

“…The results show that DTW with K-means provides the best segmentation, with a cross-correlation similarity of 0.9552 and a temporal consistency index of 0.9642. For predictive modeling, supervised algorithms were tested, where Random Forest achieved the highest accuracy in predicting the corresponding load curve type for each transformer (0.78), and the SVR model provided the best performance in predicting the maximum load, explaining 90% of the load variability (R² = 0.90). …”
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A predictive analytics approach with Bayesian-optimized gentle boosting ensemble models for diabetes diagnosis by Behnaz Motamedi, Balázs Villányi

“…Nevertheless, enhancing boosting algorithms to achieve superior predictive accuracy continues to be a difficult task. …”
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The urban heat Island effect: A review on predictive approaches using artificial intelligence models by Ali Najah Ahmed, Nouar AlDahoul, Nurhanani A. Aziz, Y.F. Huang, Mohsen Sherif, Ahmed El-Shafie

“…While conventional ML algorithms remain widely used, DL and hybrid models have shown superior performance in predictive accuracy. …”
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Machine learning predictive performance in road accident severity: A case study from Thailand by Ittirit Mohamad, Sajjakaj JomnonKwao, Vatanavongs Ratanavaraha

“…This study evaluates the predictive performance of multiple supervised machine learning algorithms in classifying accident severity, addressing the gap in prior research that lacks a comparative analysis of multiple models trained on large-scale crash data. …”
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Predictive Energy Management for Docker Containers in Cloud Computing: A Time Series Analysis Approach by Abdulmohsen Algarni, Iqrar Shah, Ali Imran Jehangiri, Mohammed Alaa Ala'Anzy, Zulfiqar Ahmad

“…In this study, we employ three time series analysis algorithms—AR, ARIMA, and ETS—to predict the energy usage of Docker containers over the next hour. …”
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Interpretable machine learning for predicting isolated basal septal hypertrophy. by Lei Gao, Boyan Tian, Qiqi Jia, Xingyu He, Guannan Zhao, Yueheng Wang

“…However, no predictive models for BSH have been developed using machine learning algorithms.…”
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Employing Machine Learning-Based Predictive Analytical Approaches to Classify Autism Spectrum Disorder Types by Muhammad Kashif Hanif, Naba Ashraf, Muhammad Umer Sarwar, Deleli Mesay Adinew, Reehan Yaqoob

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Predictive biomarkers and molecular subtypes in DLBCL: insights from PCD gene expression and machine learning by Tiantian He, Jie Geng, Chuandong Hou, Hongyi Li, Hong Zhang, Peng Zhao, Peifeng He, Xuechun Lu

“…Additionally, 12 machine learning algorithms were employed to construct predictive models for DLBCL, with performance evaluated using AUC and F-score metrics. …”
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Beyond accuracy: a framework for evaluating algorithmic bias and performance, applied to automated sleep scoring by Michal Bechny, Luigi Fiorillo, Julia van der Meer, Markus Schmidt, Claudio Bassetti, Athina Tzovara, Francesca Faraci

“…Despite these biases, we illustrate that both algorithms maintain non-inferior performance in the risk assessment of sleep apnea based on prediction-derived markers, highlighting the potential and clinical utility of algorithmic insights.…”
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Classifying Divorce Cases in Iranian Judiciary Courts Using Machine Learning: A Predictive Perspective by Elham Tabrizi, Mohadeseh Farzammehr

“…Using data collected between 2011 and 2018 and various machine learning algorithms, the study evaluates the performance of predictive models through a rigorous 10-fold cross-validation process. …”
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Assessment of Machine Learning Methods for Concrete Compressive Strength Prediction by Oluwafemi Omotayo, Chinwuba Arum, Catherine Ikumapayi

“…The study considered a wide range of literature data and examined the efficiency of boosted algorithms in predicting the strength of ordinary Portland cement concrete. …”
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Linear Model and Gradient Feature Elimination Algorithm Based on Seasonal Decomposition for Time Series Forecasting by Sheng-Tzong Cheng, Ya-Jin Lyu, Yi-Hong Lin

“…However, while deep learning models offer high predictive accuracy, their lack of interpretability often undermines decision-makers’ trust. …”
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Enhanced Model Predictive Control Using State Variable Feedback for Steady-State Error Cancellation by Marcos Andreu, Jaime Rohten, José Espinoza, José Silva, Esteban Pulido, Lesyani Leon

“…The rapid dynamic responses of predictive control algorithms are widely acknowledged. …”
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Predictive models based on machine learning to analyze the adoption of digital payments in Latin America and the Caribbean by Jiang Wagner Mamani Lopez, Antonio Víctor Morales Gonzales, Pedro Pablo Chambi Condori

“…The performance of the Random Forest, LightGBM, XGBoost, and CatBoost algorithms was compared, with the optimal hyperparameter combination identified through Bayesian optimization. …”
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