Smart material estimation for the engineering, procurement, and construction (EPC) sector by Rimma Dzhusupova, Vasil Shteriyanov, Jan Bosch, Helena Holmström Olsson

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Artificial intelligence prediction the desirable moisture content of dried oyster mushroom (Pleurotus sajor-caju) for enhancing the cellulase-assisted extraction efficiency by Nguyen Thi Ngoc Giang, Nguyen Duy Tan, Ho Thi Ngan Ha, Dao Van Thanh, Le Thi Thuy Diem, Tran Van Khai, Le Thi Diem Mi, Diep Kim Quyen

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Integration of multi-omics profiling reveals an epigenetic-based molecular classification of lung adenocarcinoma: implications for drug sensitivity and immunotherapy response predi... by Ning Wang, Yinan Li, Yaoyao Wang, Wenting Wang

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Prediction of gastric cancer development by serum pepsinogen test and Helicobacter pylori seropositivity in Eastern Asians: a systematic review and meta-analysis. by Teruhiko Terasawa, Hiroshi Nishida, Katsuaki Kato, Isao Miyashiro, Takaki Yoshikawa, Reo Takaku, Chisato Hamashima

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Voxel-level radiomics and deep learning for predicting pathologic complete response in esophageal squamous cell carcinoma after neoadjuvant immunotherapy and chemotherapy by Inigo Bermejo, Jian Zheng, Zhen Zhang, Jian Zeng, Min Fang, Leonard Wee, Andre Dekker, Tianchen Luo, Meng Yan, Haixia Shen, Kaiyi Tao, Jingping Yuan, Dirk De Ruysscher, Wencheng Zhang, Youhua Jiang, Yongling Ji

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Predicting Clinical Outcomes at the Toronto General Hospital Transitional Pain Service via the Manage My Pain App: Machine Learning Approach by James Skoric, Anna M Lomanowska, Tahir Janmohamed, Heather Lumsden-Ruegg, Joel Katz, Hance Clarke, Quazi Abidur Rahman

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Intralesional and perilesional radiomics strategy based on different machine learning for the prediction of international society of urological pathology grade group in prostate ca... by Zhiping Li, Liqin Yang, Ximing Wang, Huijing Xu, Wen Chen, Shuchao Kang, Yasheng Huang, Chang Shu, Feng Cui, Yongsheng Zhang

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Multicenter development of a deep learning radiomics and dosiomics nomogram to predict radiation pneumonia risk in non-small cell lung cancer by Xun Wang, Aiping Zhang, Huipeng Yang, Guqing Zhang, Junli Ma, Shucheng Ye, Shuang Ge

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Trend Analysis and Prediction of Violence Against Women and Children Cases in Jakarta Based on the Victim’s Education Level Using ARIMA and SARIMA Method by Zaqi Kurniawan, Rizka Tiaharyadini, Arief Wibowo, Rusdah

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A Multivariable Probability Density-Based Auto-Reconstruction Bi-LSTM Soft Sensor for Predicting Effluent BOD in Wastewater Treatment Plants by Wenting Li, Yonggang Li, Dong Li, Jiayi Zhou

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Prediction of methylphenidate treatment response for ADHD using conventional and radiomics T1 and DTI features: Secondary analysis of a randomized clinical trial by Mingshi Chen, Zarah van der Pal, Maarten G. Poirot, Anouk Schrantee, Marco Bottelier, Sandra J.J. Kooij, Henk A. Marquering, Liesbeth Reneman, Matthan W.A. Caan

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Selection of Prediction Method of Basic Statistical Work Parameters of N.V. Sklifosovsky Research Institute for Emergency Medicine of the Moscow Healthcare Department by B. L. Kurilin, V. Y. Kisselevskaya-Babinina, N. A. Karasyov, I. V. Kisselevskaya-Babinina, E. V. Kislukhkina, V. A. Vasilyev

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Utilizing Vision Transformers for Predicting Early Response of Brain Metastasis to Magnetic Resonance Imaging-Guided Stage Gamma Knife Radiosurgery Treatment by Simona Ruxandra Volovăț, Diana-Ioana Boboc, Mădălina-Raluca Ostafe, Călin Gheorghe Buzea, Maricel Agop, Lăcrămioara Ochiuz, Dragoș Ioan Rusu, Decebal Vasincu, Monica Iuliana Ungureanu, Cristian Constantin Volovăț

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Predicting responsiveness to fixed-dose methylene blue in adult patients with septic shock using interpretable machine learning: a retrospective study by Shasha Xue, Li Li, Zhuolun Liu, Feng Lyu, Fan Wu, Panxiao Shi, Yongmin Zhang, Lina Zhang, Zhaoxin Qian

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Machine learning and SHAP value interpretation for predicting the response to neoadjuvant chemotherapy and long-term clinical outcomes in Chinese female breast cancer by Quan Yuan, Rongjie Ye, Yao Qian, Hao Yu, Yuexin Zhou, Xiaoqiao Cui, Feng Liu, Ming Niu

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Application of Isokinetic Dynamometry Data in Predicting Gait Deviation Index Using Machine Learning in Stroke Patients: A Cross-Sectional Study by Xiaolei Lu, Chenye Qiao, Hujun Wang, Yingqi Li, Jingxuan Wang, Congxiao Wang, Yingpeng Wang, Shuyan Qie

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Exploring the Role of Peritumoral Edema in Predicting Lung Cancer Subtypes Through T2-FLAIR Digital Subtraction Imaging of Metastatic Brain Tumors by Okan Dilek, Emin Demırel, Zeynel Abidin Tas, Emre Bılgın

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Explainable Machine Learning Predictions for the Benefit From Chemotherapy in Advanced Non‐Small Cell Lung Cancer Without Available Targeted Mutations by Zhao Shuang, Xiong Xingyu, Cheng Yue, Yu Mingjing

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AICpred: Machine Learning-Based Prediction of Potential Anti-Inflammatory Compounds Targeting TLR4-MyD88 Binding Mechanism by Lucindah N. Fry-Nartey, Cyril Akafia, Ursula S. Nkonu, Spencer B. Baiden, Ignatus Nunana Dorvi, Kwasi Agyenkwa-Mawuli, Odame Agyapong, Claude Fiifi Hayford, Michael D. Wilson, Whelton A. Miller, Samuel K. Kwofie

“…The models predicted Baricitinib, Ibrutinib, Nezulcitinib, MCC950, and Acalabrutinib as anti-TLR4 compounds with prediction probability above 0.90. …”
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Enhanced random vector functional link based on artificial protozoa optimizer to predict wear characteristics of Cu-ZrO2 nanocomposites by Mamdouh I. Elamy, Mohamed Abd Elaziz, Mohammed Azmi Al-Betar, A. Fathy, M. Elmahdy

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