An Improved Artificial Neural Network Model for Effective Diabetes Prediction by Muhammad Mazhar Bukhari, Bader Fahad Alkhamees, Saddam Hussain, Abdu Gumaei, Adel Assiri, Syed Sajid Ullah

“…This result confirms the model’s effectiveness and efficiency in predicting diabetes disease from the required data attributes.…”
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A mathematical model to predict the requirement for multiple Z plasties by Ellur Sunderraj

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Sign Language Prediction Model using Convolution Neural Network. by Rebeccah Ndungi, Samuel Karuga

“…The model was trained and tested on various matrices where we achieved an accuracy score of a 99% value when run on epoch of 10, the log loss metric returning a value of 0 meaning that it predicts the actual hand gesture images. …”
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Prediction, Explanation, and Control: The Use of Mental Models in Dynamic Environments by Roman Tikhonov, Simon DeDeo

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ELDP: Extended Link Duration Prediction Model for Vehicular Networks by Xiufeng Wang, Chunmeng Wang, Gang Cui, Qing Yang, Xuehai Zhang

“…Considering these factors, we propose the extended link duration prediction (ELDP) model which allows a vehicle to accurately estimate how long it will be connected to another vehicle. …”
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Risk prediction models for breast cancer: a systematic review by Jiang Li, He Li, Jie He, Ni Li, Yadi Zheng, Zheng Wu, Maomao Cao

“…Objectives To systematically review and critically appraise published studies of risk prediction models for breast cancer in the general population without breast cancer, and provide evidence for future research in the field.Design Systematic review using the Prediction model study Risk Of Bias Assessment Tool (PROBAST) framework.Data sources PubMed, the Cochrane Library and Embase were searched from inception to 16 December 2021.Eligibility criteria We included studies reporting multivariable models to estimate the individualised risk of developing female breast cancer among different ethnic groups. …”
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Evaluation and Optimization of Prediction Models for Crop Yield in Plant Factory by Yaoqi Peng, Yudong Zheng, Zengwei Zheng, Yong He

“…By incorporating crop yield data, a comparative analysis of 28 prediction models was performed, assessing performance metrics such as MSE, RMSE, MAE, MAPE, R², prediction speed, training time, and model size. …”
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A Model of the Smooth Pursuit Eye Movement with Prediction and Learning by Davide Zambrano, Egidio Falotico, Luigi Manfredi, Cecilia Laschi

“…This paper presents a model of smooth pursuit based on prediction and learning. …”
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Disease-Specific Risk Models for Predicting Dementia: An Umbrella Review by Eugene Yee Hing Tang, Jacob Brain, Serena Sabatini, Eduwin Pakpahan, Louise Robinson, Maha Alshahrani, Aliya Naheed, Mario Siervo, Blossom Christa Maree Stephan

“…However, while numerous models have been developed to predict dementia, they are often not tailored to disease-specific groups. …”
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Pathogenic Factors of Bacterial Vaginitis and Construction of Nomogram Prediction Model by Xuqing Chen, Jing Li, Nanxiang Lei, Hui Liang

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A Radiomic Model for Gliomas Grade and Patient Survival Prediction by Ahmad Chaddad, Pingyue Jia, Yan Hu, Yousef Katib, Reem Kateb, Tareef Sahal Daqqaq

“…In this study, we propose a radiomic model for the non-invasive prediction of brain tumor grade and patient survival outcomes. …”
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Liner Wear Prediction Using Bayesian Regression Models and Clustering by Jacob Van Den Broek, Melinda Hodkiewicz, Adriano Polpo

“…Notably, Model 2 predicts remaining useful life within 95% credible intervals and identifies anomalous sensor performance. …”
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Diagnostic prediction model for levodopa-induced dyskinesia in Parkinson’s disease by Bruno Lopes SANTOS-LOBATO, Artur F. SCHUMACHER-SCHUH, Carlos R. M. RIEDER, Mara H. HUTZ, Vanderci BORGES, Henrique Ballalai FERRAZ, Ignacio F. MATA, Cyrus P. ZABETIAN, Vitor TUMAS

“…We developed two diagnostic prediction models with reasonable accuracy, but we suggest that the clinical prediction model be used. …”
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An optimized informer model design for electric vehicle SOC prediction by Xin Xie, Feng Huang, Yefeng Long, Youyuan Peng, Wenjuan Zhou

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Reasoning language models for more transparent prediction of suicide risk by Roy H Perlis, Thomas H McCoy

“…The corresponding c-statistic was 0.64 (0.63–0.65), modestly poorer than the GPT4o model (0.67 (0.66–0.68)). In chain-of-thought reasoning, topics including Substance Abuse, Surgical Procedure, and Age-related Comorbidities were associated with correct predictions, while Fall-related Injury was associated with incorrect prediction.Conclusions Application of a reasoning model using local, consumer-grade hardware only modestly diminished performance in stratifying suicide risk.Clinical implications Smaller models can yield more secure, scalable and transparent risk prediction.…”
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Risk prediction models for diabetic retinopathy: a systematic review by Hui Huang, Yingmin Wu, Hejiang Ye, Jiaoyang Li, Ling Chen, Xuan Huang

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Regression models for productivity prediction in cactus pear cv. Gigante by Bruno V. C. Guimarães, Sérgio L. R. Donato, Ignacio Aspiazú, Alcinei M. Azevedo, Abner J. de Carvalho

“…ABSTRACT The understanding of plant behavior and its reflexes on yield is essential for rural planning; thus, the biomathematical models are promising in the yield prediction of cactus pear cv. …”
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Ada-GCNLSTM: An adaptive urban crime spatiotemporal prediction model by Miaoxuan Shan, Chunlin Ye, Peng Chen, Shufan Peng

“…Additionally, the inherent randomness and volatility of crime data at the spatiotemporal level introduce noise, which can mislead prediction models. While many effective spatiotemporal crime prediction methods have been proposed, most overlook this issue, reducing their ability to generalize. …”
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Benchmarking shoreline prediction models over multi-decadal timescales by Yongjing Mao, Giovanni Coco, Sean Vitousek, Jose A. A. Antolinez, Georgios Azorakos, Masayuki Banno, Clément Bouvier, Karin R. Bryan, Laura Cagigal, Kit Calcraft, Bruno Castelle, Xinyu Chen, Maurizio D’Anna, Lucas de Freitas Pereira, Iñaki de Santiago, Aditya N. Deshmukh, Bixuan Dong, Ahmed Elghandour, Amirmahdi Gohari, Eduardo Gomez-de la Peña, Mitchell D. Harley, Michael Ibrahim, Déborah Idier, Camilo Jaramillo Cardona, Changbin Lim, Ivana Mingo, Julian O’Grady, Daniel Pais, Oxana Repina, Arthur Robinet, Dano Roelvink, Joshua Simmons, Erdinc Sogut, Katie Wilson, Kristen D. Splinter

“…The outcomes from this collaborative benchmarking competition critically review the present state-of-the-art in shoreline change prediction as well as reveal model limitations, facilitate improvements, and offer insights for advancing shoreline-prediction capabilities.…”
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Research on network traffic prediction based on Bi-GRU model by Xu Haibing, Guo Jiuming

“…At the same time, in order to improve the accuracy of some time periods, the training samples are classified into date classes, and a separate network model is generated for each type of date. It can greatly improve the accuracy of prediction and improve the lag of prediction. …”
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