Predicting vector distribution in Europe: at what sample size are species distribution models reliable? by Lianne Mitchel, Lianne Mitchel, Guy Hendrickx, Ewan T. MacLeod, Cedric Marsboom, Cedric Marsboom

“…IntroductionSpecies distribution models can predict the spatial distribution of vector-borne diseases by forming associations between known vector distribution and environmental variables. …”
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External Validation of Persistent Severe Acute Kidney Injury Prediction With Machine Learning Model by Simone Zappalà, PhD, Francesca Alfieri, MS, Andrea Ancona, PhD, Antonio M. Dell’Anna, MD, Kianoush B. Kashani, MD, MS

“…The performance of the PersEA model, a boosted tree algorithm fed by hourly patient data via electronic health records to provide real-time psAKI predictions, was evaluated using specific metrics that penalize late alarms. …”
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Development, deployment, and feature interpretability of a three-class prediction model for pulmonary diseases by Zhenyu Cao, Gang Xu, Yuan Gao, Jianying Xu, Fengjuan Tian, Hengfeng Shi, Dengfa Yang, Zongyu Xie, Jian Wang

“…Abstract Purpose To develop a high-performance machine learning model for predicting and interpreting features of pulmonary diseases. …”
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Models based on dietary nutrients predicting all-cause and cardiovascular mortality in people with diabetes by Fang Wang, Yukang Mao, Jinyu Sun, Jiaming Yang, Li Xiao, Qingxia Huang, Chenchen Wei, Zhongshan Gou, Kerui Zhang

“…The least absolute shrinkage and selection operator (LASSO) regression and random forest (RF) algorithm were applied to identify key mortality-related dietary factors, which were subsequently incorporated into risk prediction nomogram models. …”
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Predicting pediatric patient rehabilitation outcomes after spinal deformity surgery with artificial intelligence by Wenqi Shi, Felipe O. Giuste, Yuanda Zhu, Ben J. Tamo, Micky C. Nnamdi, Andrew Hornback, Ashley M. Carpenter, Coleman Hilton, Henry J. Iwinski, J. Michael Wattenbarger, May D. Wang

“…Moreover, we enable responsible AI by calibrating model confidence for human intervention and mitigating health disparities for algorithm fairness. Results The best prediction model achieves an area under receiver operating curve (AUROC) performance of 0.86, 0.85, and 0.83 for individual SRS-22R question response prediction over three-time horizons from pre-operation to 6-month, 1-year, and 2-year post-operation, respectively. …”
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Toward generalizable prediction of antibody thermostability using machine learning on sequence and structure features by Ameya Harmalkar, Roshan Rao, Yuxuan Richard Xie, Jonas Honer, Wibke Deisting, Jonas Anlahr, Anja Hoenig, Julia Czwikla, Eva Sienz-Widmann, Doris Rau, Austin J. Rice, Timothy P. Riley, Danqing Li, Hannah B. Catterall, Christine E. Tinberg, Jeffrey J. Gray, Kathy Y. Wei

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Prediction of soil chemical properties using multispectral satellite images and wavelet transforms methods by Chaitanya B. Pande, Sunil A. Kadam, Rajesh Jayaraman, Sunil Gorantiwar, Mukund Shinde

“…In this study, the neural network wavelet model was used to predicted values related to soil chemical properties in the semi-arid region. …”
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Interpretable Machine Learning for Legume Yield Prediction Using Satellite Remote Sensing Data by Theodoros Petropoulos, Lefteris Benos, Remigio Berruto, Gabriele Miserendino, Vasso Marinoudi, Patrizia Busato, Chrysostomos Zisis, Dionysis Bochtis

“…Accurate crop yield prediction is vital towards optimizing agricultural productivity. …”
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Emerging and Pioneering AI Technologies in Aesthetic Dermatology: Sketching a Path Toward Personalized, Predictive, and Proactive Care by Diala Haykal

“…Objectives: Artificial intelligence (AI) is transforming aesthetic dermatology, introducing new opportunities for personalized, predictive, and adaptive approaches in skin diagnostics, treatment planning, and patient management. …”
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Explainable machine learning models predicting the risk of social isolation in older adults: a prospective cohort study by Mingfei Jiang, Xiaoran Li, YongLu

“…Abstract Introduction This study aimed to develop a machine learning system to predict social isolation risk in older adults. Methods Data from a sample of 6588 older adults in China were analyzed using information from China Health and Retirement Longitudinal Study from 2015 to 2018. …”
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Development and validation of a decision tree model for prediction of insomnia risk among ischemic stroke convalescence patients by Xuefeng Sun, Zilin Wang, Yuqing Song, Deyu Cong, Shu Sun, Xinye Zhang, Ye Zhang, Hongshi Zhang

“…While the interaction of clinical, psychological, and social factors remains unclear, developing a predictive model system is urgently needed. Currently, few studies have established insomnia risk prediction models. …”
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A deep learning model to predict Ki-67 positivity in oral squamous cell carcinoma by Francesco Martino, Gennaro Ilardi, Silvia Varricchio, Daniela Russo, Rosa Maria Di Crescenzo, Stefania Staibano, Francesco Merolla

“…Aside from classification, detection, and segmentation models, predictive models are gaining traction since they can impact diagnostic processes and laboratory activity, lowering consumable usage and turnaround time. …”
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Robust Path Tracking Control with Lateral Dynamics Optimization: A Focus on Sideslip Reduction and Yaw Rate Stability Using Linear Quadratic Regulator and Genetic Algorithms by Karrar Y. A. Al-bayati, Ali Mahmood, Róbert Szabolcsi

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Enhancing cybersecurity via attribute reduction with deep learning model for false data injection attack recognition by Faheed A.F. Alrslani, Manal Abdullah Alohali, Mohammed Aljebreen, Hamed Alqahtani, Asma Alshuhail, Menwa Alshammeri, Wafa Sulaiman Almukadi

“…The ARDL-FDIAR technique uses Z-score normalization to scale the input data. The attribute reduction process gets invoked using the modified Lemrus optimization algorithm (MLOA) to choose optimal feature sets. …”
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A Distribution Network Expansion Project Classification Model Based on Data Augmentation and Dimensionality Reduction Method by Xin ZHOU, Jingxing LIN, Zhiwei XIE, Zheng ZHANG, Ruduo LIANG, Zuhong OU

“…Based on the data of a distribution network expansion project of a power supply bureau, the simulation results show that the classification accuracy of the algorithm used in this paper is better than other algorithms. …”
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A novel approach for the effective prediction of cardiovascular disease using applied artificial intelligence techniques by Azka Mir, Attique Ur Rehman, Tahir Muhammad Ali, Sabeen Javaid, Maram Fahaad Almufareh, Mamoona Humayun, Momina Shaheen

“…Methods In this paper, we have utilized machine learning algorithms to predict cardiovascular disease on the basis of symptoms such as chest pain, age and blood pressure. …”
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A similarity-based multi-objective test optimization technique using search algorithm by Amir Sohail Habib, Saif Ur Rehman Khan, Shahid Hussain, Naseem Ibrahim, Habib un Nisa, Abdullah Yousafzai

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A Genetic Algorithm Approach to Adaptive Learning: Enhancing Learner Satisfaction and Performance by Anju Kalwar, Deepika Shekhawat, Sandeep Joshi, Amit Kumar Bairwa

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Preliminary Evaluation of an Advanced Ventilation-Control Algorithm to Optimise Microclimate in a Commercial Broiler House by Kehinde Favour Daniel, Lak-yeong Choi, Se-yeon Lee, Chae-rin Lee, Ji-yeon Park, Jinseon Park, Se-woon Hong

“…This study aims to improve the microclimate conditions in a mechanically ventilated broiler house by proposing and evaluating a ventilation-control algorithm based on heat-energy balance analysis. The new algorithm is designed to optimise the ventilation-rate requirement and thereby improve control of the indoor temperature. …”
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Method for assessing testing difficulty in educational sphere by A. S. Sigov, V. Ya. Tsvetkov, I. E. Rogov

Subjects: “…algorithm…”
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