Machine Learning Radiomics for Predicting Response to MR-Guided Radiotherapy in Unresectable Hepatocellular Carcinoma: A Multicenter Cohort Study by Su K, Liu X, Zeng YC, Xu J, Li H, Wang H, Du S, Wang H, Yue J, Yin Y, Li Z

“…The machine learning radiomics model developed in this study could accurately predict the response of radiotherapy-treated inoperable HCC.Keywords: machine learning models, radiomics, radiotherapy, hepatocellular carcinoma…”
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A designed predictive modelling strategy based on data decomposition and machine learning to forecast solar radiation by Mumtaz Ali, Ramendra Prasad, Salman Alamery, Aitazaz Ahsan Farooque

“…The results generated at test sites in Queensland State, Australia that have high solar energy potential confirm that the RLMD-RF method can produce quality predictions of weekly solar radiation against the benchmarking comparison models. …”
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Physiological and Anthropometric Factors Associated With Spine Loading Estimates From Imaging‐Based Subject‐Specific Musculoskeletal Models by Brett T. Allaire, Fjola Johannesdottir, Mary L. Bouxsein, Dennis E. Anderson

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A Comparative Analysis of Machine Learning Models for Predicting EFL Student Language Performance in Smart Learning Environments by Banchakarn Sameephet, Wirapong Chansanam, Mahboubeh Rakhshandehroo, Chawin Srisawat, Kittichai Nilubol, Arnon Jannok, Bhirawit Satthamnuwong, Kornwipa Poonpon

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Machine learning models in enhancing prediction of health-related indices among older adults: A scoping review by Raoof Nopour

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Exploring the predictive “psycho-biomarkers” for checkpoint immunotherapy in cancer by Qian Zuo, Jieting Chen, Jieting Chen, Xi Xiao, Yan Dai, Liushan Chen, Liushan Chen, Yuqi Liang, Yingchao Wu, Junfeng Huang, Rutao Cui, Rui Xu, Qianjun Chen, Qianjun Chen, Qianjun Chen, Qianjun Chen

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Optimizing Power Forecasting Models with Customized Features for Academic and Industrial Buildings by David Cabezuelo, Izar Lopez-Ramirez, June Urkizu, Ander Goikoetxea

Subjects: “…power consumption prediction…”
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Investigating Enhanced Cooling Load Estimation through Hybrid LSSVR Models by Ali Hassan, Hamza Rashid

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Platelet transfusion response in critically ill patients with thrombocytopenia: a retrospective study and predictive nomogram in a general ICU population by Hanyu Ge, Yanqing Liu, Tongyu Li, Rui Lv, Jieyi Wang, Wei You, Danni Song, Shilin Hu, Feng Zhao, Heng Fan, Dingfeng Lv

“…Clinical and laboratory variables were analyzed using a generalized linear mixed-effects model (GLMM), with the results visualized through a nomogram. …”
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Risk Factors and Predictive Model for Ischemic Complications in Endovascular Treatment of Intracranial Aneurysms: Insights From a Large Patient Cohort by Jianwen Jia, Zeping Jin, Mirzat Turhon, Yixin Lin, Xinjian Yang, Yang Wang, Yunpeng Liu

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Evaluation of Artificial Neural Network Model for Predicting Nitrogen Oxides (NOₓ) Concentration by Muhammad Farrih Mahabbataka Arsyada, Raras Tyasnurita

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Model for predicting metabolic activity in athletes based on biochemical blood test analysis by Victoria A. Zaborova, Evgenii I. Balakin, Ksenia A. Yurku, Olga E. Aprishko, Vasiliy I. Pustovoyt

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Predicting lung nodules malignancy by M. Jacob, J. Romano, D. Araújo, J.M. Pereira, I. Ramos, V. Hespanhol

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An antibody developability triaging pipeline exploiting protein language models by James Sweet-Jones, Andrew C.R. Martin

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Human-Aware Control for Physically Interacting Robots by Reza Sharif Razavian

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Novel prognostic scoring models for hepatitis B virus-related acute-on-chronic liver failure: A comparison with classical models by Hongyan Guo, Fengling Fang, Lin Lin, Zhaopei Guo, Lu Lai, Yue Shi, Tianbin Chen, Ruimin Lai, Qishui Ou, Ya Fu

“…Logistic regression and nomogram models were used to construct three novel predictive models. …”
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Predicting tilling and seeding operation times in grain production: A comparison of machine learning and mechanistic models by Luca Scheurer, Tobias Zimpel, Joerg Leukel

“…The aim of this study was to evaluate the prediction performance of ML models for these operation times by using readily available tractor and operations data rather than dynamic environmental data. …”
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The PIEE Cycle: A Structured Framework for Red Teaming Large Language Models in Clinical Decision-Making by Maissa Trabilsy, Srinivasagam Prabha, Cesar A. Gomez-Cabello, Syed Ali Haider, Ariana Genovese, Sahar Borna, Nadia Wood, Narayanan Gopala, Cui Tao, Antonio J. Forte

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Prediction of Diabetes in Middle-Aged Adults: A Machine Learning Approach by Gideon Addo, Bismark Amponsah Yeboah, Michael Obuobi, Raphael Doh-Nani, Seidu Mohammed, David Kojo Amakye

Subjects: “…diabetes prediction; diabetes symptoms; machine learning models; middle-aged adults; predictive performance metrics…”
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Predicting post-hospital lethality in males and females with acute coronary syndrome by R. T. Saygitov, M. G. Glezer, D. P. Sementsov, I. N. Sokolova, N. A. Malygina

“…This predicted risk gives a chance to divide patients into risk groups - with minimal (lethality < 1 %) to maximal (lethality > 30 %) risk, as well as to predict possible time of death. …”
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