Development of a clinical-radiological nomogram for predicting severe postoperative peritumoral brain edema following intracranial meningioma resection by Chen Bo, Geng Ao, Lu Siyuan, Lu Siyuan, Wu Ting, Wang Dianjun, Zhao Nan, Shan Xiuhong, Deng Yan, Sun Eryi

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Modeling the Dynamic Variability of Sub‐Relativistic Outer Radiation Belt Electron Fluxes Using Machine Learning by Donglai Ma, Xiangning Chu, Jacob Bortnik, Seth G. Claudepierre, W. Kent Tobiska, Alfredo Cruz, S. Dave Bouwer, Joseph F. Fennell, J. Bernard Blake

Subjects: “…machine learning…”
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Beyond the icebox: modern strategies in organ preservation for transplantation by Kidus Haile Yemaneberhan, Minseok Kang, Jun Hwan Jang, Jin Hee Kim, Kyeong Sik Kim, Ho Bum Park, Dongho Choi

Subjects: “…organ transplantation; machine perfusion; cryopreservation; nanobiotechnology…”
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Evaluation of machine learning models for the prediction of Alzheimer's: In search of the best performance by Michael Cabanillas-Carbonell, Joselyn Zapata-Paulini

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Prediction and unsupervised clustering of fertility intention among migrant workers based on machine learning: a cross-sectional survey from Henan, China by Xinghong Guo, Mingze Ma, Yiyang Chen, Zhaoyang Fang, Jingru Liu, Shuming Yan, Yifei Feng, Xinya Cheng, Jian Wu, Beizhu Ye

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Diagnosis of traumatic liver injury on computed tomography using machine learning algorithms and radiomics features: The role of artificial intelligence for rapid diagnosis in emer... by Hanieh Alimiri Dehbaghi, Karim Khoshgard, Hamid Sharini, Samira Jafari Khairabadi

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An Examination of SuperDARN Backscatter Modes Using Machine Learning Guided by Ray‐Tracing by B. S. R. Kunduri, J. B. H. Baker, J. M. Ruohoniemi, E. G. Thomas, S. G. Shepherd

Subjects: “…Machine learning…”
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Application of the Different Machine Learning Algorithms to Predict Dry Matter Intake in Feedlot Cattle by Hayati Köknaroğlu, Özgür Koşkan, Malik Ergin

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Interpretable machine learning and radiomics in hip MRI diagnostics: comparing ONFH and OA predictions to experts by Tariq Alkhatatbeh, Ahmad Alkhatatbeh, Qin Guo, Jiechen Chen, Jidong Song, Xingru Qin, Wang Wei

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Comment on “Prediction of the SYM‐H Index Using a Bayesian Deep Learning Method With Uncertainty Quantification” by Abduallah et al. (2024) by Armando Collado‐Villaverde, Pablo Muñoz, Consuelo Cid

Subjects: “…machine learning…”
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Machine Learning-Driven Resilient Modulus Prediction for Flexible Pavements Across Mountainous and Other Regions by Rauf Ayesha, Asif Usama, Javed Muhammad Faisal

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Interpretable machine learning model for predicting clinically significant prostate cancer: integrating intratumoral and peritumoral radiomics with clinical and metabolic features by Wenjun Zhao, Mengyan Hou, Juan Wang, Dan Song, Yongchao Niu

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Machine learning analysis of rivaroxaban solubility in mixed solvents for application in pharmaceutical crystallization by Mohammed Alqarni, Ali Alqarni

Subjects: “…Machine learning…”
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A survey on key technologies of privacy protection for machine learning by Zishan LIU, Qiang CHENG, Bo LV

Subjects: “…machine learning…”
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Rating pome fruit quality traits using deep learning and image processing by Nhan H. Nguyen, Joseph Michaud, Rene Mogollon, Huiting Zhang, Heidi Hargarten, Rachel Leisso, Carolina A. Torres, Loren Honaas, Stephen Ficklin

Subjects: “…machine learning…”
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Application of artificial intelligence technology in the field of security vulnerability by Hongyu SUN, Yuan HE, Jice WANG, Ying DONG, Lipeng ZHU, He WANG, Yuqing ZHANG

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Developing a rapid screening tool for high-risk ICU patients of sepsis: integrating electronic medical records with machine learning methods for mortality prediction in hospitalize... by Songchang Shi, Lihui Zhang, Shujuan Zhang, Jinyang Shi, Donghuang Hong, Siqi Wu, Xiaobin Pan, Wei Lin

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DETEC-ADHD: A Data-Driven Web App for Early ADHD Detection Using Machine Learning and Electroencephalography by Ismael Santarrosa-López, Giner Alor-Hernández, Maritza Bustos-López, Jonathan Hernández-Capistrán, Laura Nely Sánchez-Morales, José Luis Sánchez-Cervantes, Humberto Marín-Vega

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Metabolic Syndrome Prediction Using Machine Learning Models with Genetic and Clinical Information from a Nonobese Healthy Population by Eun Kyung Choe, Hwanseok Rhee, Seungjae Lee, Eunsoon Shin, Seung-Won Oh, Jong-Eun Lee, Seung Ho Choi

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Machine Learning-Based Modeling of Celeration for Predicting Red-Light Violations by Mahmoud Masoud

Subjects: “…Machine learning…”
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