ECG‐based epileptic seizure prediction: Challenges of current data‐driven models by Sotirios Kalousios, Jens Müller, Hongliu Yang, Matthias Eberlein, Ortrud Uckermann, Gabriele Schackert, Witold H. Polanski, Georg Leonhardt

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Prediction of Metastasis in Paragangliomas and Pheochromocytomas Using Machine Learning Models: Explainability Challenges by Carmen García-Barceló, David Gil, David Tomás, David Bernabeu

“…One of the main issues with paragangliomas and pheochromocytomas is that these tumors have up to a 20% rate of metastatic disease, which cannot be reliably predicted. While machine learning models hold great promise for enhancing predictive accuracy, their often opaque nature limits trust and adoption in critical fields such as healthcare. …”
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Structural Constraints in Current Stomatal Conductance Models Preclude Accurate Prediction of Evapotranspiration by Pushpendra Raghav, Mukesh Kumar, Yanlan Liu

“…In contrast, a ML approach, wherein the model structure is learned from the data, outperforms traditional models, thus highlighting that there still is significant room for improvement in the structure of traditional models for predicting ET. …”
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Development and validation of prediction models for diabetic retinopathy in type 2 diabetes patients. by Shadi Naderyan Feˈli, Mohammad Hassan Emamian, Mehdi Yaseri, Hamid Riazi-Esfahani, Hassan Hashemi, Akbar Fotouhi, Kamran Yazdani

“…<h4>Background and objective</h4>Prediction models enable healthcare providers to perform early risk stratification. …”
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Solar Irradiance Prediction for Zaria Town Using Different Machine Learning Models by Ibrahim Abdulwahab, Sulaiman Haruna Sulaiman, Umar Musa, Ibrahim Abdullahi Shehu, Abdullahi Kakumi Musa, Ismaila Mahmud, Mohammed Musa, Abdullahi Abubakar, Abdulrahman Olaniyan

“…This is done in order to construct and develop a high-efficiency prediction model that uses actual meteorological data to predict daily solar irradiance for the town of Zaria, Nigeria. …”
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Evaluation of different erosion models for predicting guide vane wear in Francis turbine by Rakish Shrestha, Rakish Shrestha, Kushal Shrestha, Kushal Shrestha, Sailesh Chitrakar, Sailesh Chitrakar, Bhola Thapa, Hari Prasad Neopane, Zhongdong Qian, Zhiwei Guo

“…By dividing the CG into sections and comparing the erosion predictions by different erosion models with the actual erosion, Finnie erosion model is found to be the most suitable model for this application. …”
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Comparison of Machine Learning and Deep Learning Models Performance in predicting wind energy by Saswati Rakshit, Anal Ranjan Sengupta

“…This study leverages advanced machine learning (ML) and some other statistical and deep learning based time series forecasting models to enhance the accuracy of wind energy predictions. …”
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Predicting Sentiments in Spotify Comments: A Comparative Analysis of Machine Learning Models by Filipe Augusto Felix de Queiroz, Igor Barbosa Negreiros, Giovana de Souza, Débora Cordeiro de Sousa, Sílvio Fernando Alves Xavier Júnior

“…We compare different statistical modeling and Machine Learning techniques, identifying the ones with the greatest accuracy in predicting sentiments. …”
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A Comprehensive Evaluation of Machine Learning and Deep Learning Models for Churn Prediction by Nabil M. AbdelAziz, Mostafa Bekheet, Ahmad Salah, Nissreen El-Saber, Wafaa T. AbdelMoneim

“…Therefore, this study attempts to analyze the effectiveness of the advanced machine learning and deep learning models for churn prediction in the evaluation of the models’ performance across different sectors. …”
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Machine learning models to predict onset of dementia: A label learning approach by Vijay S. Nori, Christopher A. Hane, William H. Crown, Rhoda Au, William J. Burke, Darshak M. Sanghavi, Paul Bleicher

“…Abstract Introduction The study objective was to build a machine learning model to predict incident mild cognitive impairment, Alzheimer's Disease, and related dementias from structured data using administrative and electronic health record sources. …”
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Prediction of Streamflow of the Anai-Weir Catchment Using Both the SWAT and Mock Models by Mas Mera, Siti Hawa Binti Yusmardi, Junaidi Junaidi

“…This research focuses on predicting the streamflow of the Anai-weir catchment using the SWAT (Soil and Water Assessment Tools) and Mock models. …”
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Predicting in-hospital mortality in ICU patients with lymphoma using machine learning models. by Ling Xu, Guang Tu, Zhonglan Cai, Tianbi Lan

“…Machine learning (ML) models offer a more accurate alternative for predicting outcomes by analyzing large datasets. …”
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Predicting transient response using data-driven models for ball-impact simulations by Ross Pivovar, Fei Chen, Raghunath Katragadda, Vidyasagar Ananthan

“…This study investigates the application of machine learning (ML) models for predicting transient responses in ball-impact elastodynamics simulations. …”
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Prediction models based on machine learning algorithms for COVID-19 severity risk by Hansong Zhang, Ying Wang, Yan Xie, Cuihan Wang, Yuqi Ma, Xin Jin

Subjects: “…Prediction models…”
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Machine Learning Models for Predicting Mortality in Hemodialysis Patients: A Systematic Review by Alexandru Catalin Motofelea, Adelina Mihaescu, Nicu Olariu, Luciana Marc, Lazar Chisavu, Gheorghe Nicusor Pop, Andreea Crintea, Ana Maria Cristina Jura, Viviana Mihaela Ivan, Adrian Apostol, Adalbert Schiller

“…This systematic review and meta-analysis aimed to evaluate and compare the performance of various machine learning (ML) models in predicting mortality among HD patients. …”
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Predicting Dilution in Underground Mines with Stacking Artificial Intelligence Models and Genetic Algorithms by Jorge L. V. Mariz, Tertius S. G. Ferraz, Marinésio P. Lima, Ricardo M. A. Silva, Hyongdoo Jang

“…Furthermore, four stacking models were constructed by aggregating the top-performing base learners, giving rise to ensemble metamodels applied, for the first time, to the task of dilution prediction in underground mining.…”
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Transport models for predicting spontaneous ignition of pressurized hydrogen released into a tube by Gang Luo, Wenping Zhang, Zixuan Yang, Lijing Zhang, Jinfeng Zhang

“…In this paper, OpenFOAM is employed to study three different transport models for predicting spontaneous ignition of pressurized hydrogen released into a tube. …”
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Development and Comparison of Machine Learning and Deep Learning Models for Speech Audiometry Prediction by Jae sung Shin, Jun Ma, Mao Makara, Nak-Jun Sung, Seong Jun Choi, Sung yeup Kim, Min Hong

“…These findings suggest that machine learning models, particularly gradient boosting and XGBoost, outperform deep learning models in SA prediction. …”
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Interpretable machine learning models for survival prediction in prostate cancer bone metastases by Hua Zhang, Bingtian Dong, Jialin Han, Lewen Huang

“…However, existing clinical models lack precision. This study seeks to establish machine learning models to improve survival predictions for PCBM patients. …”
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Performance of deep learning models in predicting the nugent score to diagnose bacterial vaginosis by Naoki Watanabe, Tomohisa Watari, Kenji Akamatsu, Isao Miyatsuka, Yoshihito Otsuka

“…This study aimed to evaluate the performance of deep learning models in predicting the Nugent score to improve diagnostic consistency and accuracy. …”
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