TRIPOD statement: a preliminary pre-post analysis of reporting and methods of prediction models by Gary S Collins, Karel G M Moons, Lotty Hooft, Ewout W Steyerberg, Pauline Heus, Merel van Diepen, Friedo W Dekker, Amir H Zamanipoor Najafabadi, Chava L Ramspek, Wilco C Peul

“…Objectives To assess the difference in completeness of reporting and methodological conduct of published prediction models before and after publication of the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) statement.Methods In the seven general medicine journals with the highest impact factor, we compared the completeness of the reporting and the quality of the methodology of prediction model studies published between 2012 and 2014 (pre-TRIPOD) with studies published between 2016 and 2017 (post-TRIPOD). …”
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Artificial Neural Network and Ensemble Models for Flood Prediction in North-Central Region of Nigeria by Sikiru Abdulganiyu Siyanbola, Aisha Olabisi Sowemimo, Zaid Habibu, Timothy Ebuka Eberechukwu

Subjects: “…flood prediction…”
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GS-DTA: integrating graph and sequence models for predicting drug-target binding affinity by Junwei Luo, Ziguang Zhu, Zhenhan Xu, Chuanle Xiao, Jingjing Wei, Jiquan Shen

“…Results In this paper, we propose a new method, called GS-DTA, for predicting DTA based on graph and sequence models. GS-DTA takes simplified molecular input line input system (SMILES) of the drug and the protein amino acid sequence as input. …”
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Comparison of regression based functions and ANN models for predicting the compressive strength of geopolymer mortars by Atchadeou Yranawa Katatchambo, Şinasi Bingöl

“…For the MARS, TreeNet and RF models, the TreeNet model produced the best prediction, while for the ANN_5 and ANN_10 models, the ANN_5 model produced the best prediction. …”
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A Comparative Analysis of Deep Learning Models for Prediction of Microsatellite Instability in Colorectal Cancer by Ziynet Pamuk, Hüseyin Erikçi

“…This study proposes a deep learning-based model for predicting microsatellite instability (MSI) in colorectal cancer using hematoxylin and eosin (H&E)-stained histopathological tissue slides. …”
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Comparison of 7 artificial intelligence models in predicting venous thromboembolism in COVID-19 patients by Indika Rajakaruna, Mohammad Hossein Amirhosseini, Mike Makris, Mike Laffan, Yang Li, Deepa J. Arachchillage

“…Background: An artificial intelligence (AI) approach can be used to predict venous thromboembolism (VTE). Objectives: To compare different AI models in predicting VTE using data from patients with COVID-19. …”
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Prediction rotary drilling penetration rate in lateritic soils using machine learning models by Eugène Gatchouessi Kamdem, Franck Ferry Kamgue Tiam, Luc Leroy Mambou Ngueyep, Olivier Wounabaissa, Hugues Richard Lembo Nnomo, Abraham Kanmogne

“…The present paper investigated an accurate machine learning model for the penetration rates (ROP) prediction in lateritic soil covers layers. …”
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Utilizing patient data: A tutorial on predicting second cancer with machine learning models by Hossein Sadeghi, Fatemeh Seif, Erfan Hatamabadi Farahani, Soraya Khanmohammadi, Shahla Nahidinezhad

“…To instruct and assess ML models for predicting the occurrence of SC based on patient data, the paper utilizes a dataset consisting of instances and attributes. …”
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Comparative analysis of empirical and deep learning models for ionospheric sporadic E layer prediction by BingKun Yu, PengHao Tian, XiangHui Xue, Christopher J. Scott, HaiLun Ye, JianFei Wu, Wen Yi, TingDi Chen, XianKang Dou

“…In this study, we present Es predictions made by an empirical model and by a deep learning model, and analyze their differences comprehensively by comparing the model predictions to satellite RO measurements and ground-based ionosonde observations. …”
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The Use of Momentum-Inspired Features in Pre-Game Prediction Models for the Sport of Ice Hockey by Noel Jordan T.P., Fonseca Vinicius Prado da, Soares Amilcar

“…We show that with the use of SVM and logistic regression these momentum- based features have more predictive power than traditional frequency-based features in a pre-game prediction model which only uses each team’s three most recent games to assess team quality. …”
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Performance Evaluation of Numerical Weather Prediction Models in Forecasting Rainfall Events in Kerala, India by V. Nitha, S. K. Pramada, N. S. Praseed, Venkataramana Sridhar

Subjects: “…Numerical Weather Prediction (NWP) models…”
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Machine learning models for predicting survival in lung cancer patients undergoing microwave ablation by Yufan Liu, Zihang Wang, Xiaowen Cao, Miaoyan Liu, Lou Zhong

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A comparative study of explainable machine learning models with Shapley values for diabetes prediction by Keona Pang

“…Over the years, numerous machine learning models have been developed, leading to successful applications across various fields. …”
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Establishment of interpretable cytotoxicity prediction models using machine learning analysis of transcriptome features by You Wu, Ke Tang, Chunzheng Wang, Hao Song, Fanfan Zhou, Ying Guo

“…In summary, the models established in this research exhibit superior capacity to those of previous studies; these models enable accurate high-safety substance screening via cytotoxicity prediction across cell lines. …”
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Correction: Time series models for prediction of leptospirosis in different climate zones in Sri Lanka. by PLOS ONE Staff

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Evaluation of multiple machine learning models predicting the results of hybrid imaging in primary hyperparathyroidism by Anna Drynda, Jacek Podlewski, Karolina Kucharczyk, Grzegorz Sokołowski, Anna Sowa-Staszczak, Alicja Hubalewska-Dydejczyk, Małgorzata Trofimiuk- Müldner

“…Random forest (RF) exhibited higher sensitivity (62.7%), but lower specificity (74.2%) and accuracy (68.6%). Other models demonstrated subpar performance. CONCLUSIONS: Logistic regression and RF models were the most effective in predicting radiotracer uptake in pre-operative hybrid imaging of the parathyroids, suggesting their suitability as the foundation for software to be used in clinical settings. …”
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Systematic review of risk prediction models for arteriovenous fistula dysfunction in maintenance hemodialysis patients by Shiyan Yao, Guannan Ma, Yongze Dong, Mengjiao Zhao, Luchen Chen, Wenhao Qi, Huajuan Shen

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Construction of mathematical models to predict M25 and M10 coke quality indices by E. N. Stepanov, A. N. Smirnov, D. I. Alekseev

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Development and validation of prediction models for death within 6 months after cardiac arrest by Jianping Lu, Jianping Lu, Yuqi Zeng, Yuqi Zeng, Nan Lin, Qinyong Ye, Qinyong Ye

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Comparative analysis of supervised learning models for effluent quality prediction in wastewater treatment plants. by Liu Bo-Qi, Zhou Ding-Jie, Zhao Yang, Shi Long-Yu

“…Nevertheless, the findings provide valuable insights into selecting effective machine learning models for effluent quality prediction, supporting data-driven decision-making in wastewater management and advancing intelligent process optimization in WWTP.…”
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