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Development of machine learning models to prognosticate chronic shunt-dependent hydrocephalus after aneurysmal subarachnoid hemorrhage
Muscas, Giovanni, Matteuzzi, Tommaso, Becattini, Eleonora, Orlandini, Simone, Battista, Francesca, Laiso, Antonio, Nappini, Sergio, Limbucci, Nicola, Renieri, Leonardo, Carangelo, Biagio R., Mangiafico, Salvatore, Della Puppa, Alessandro
Published in Acta neurochirurgica (01.12.2020)
Published in Acta neurochirurgica (01.12.2020)
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Explainable Machine Learning Models for Colorectal Cancer Prediction Using Clinical Laboratory Data
Li, Rui, Hao, Xiaoyan, Diao, Yanjun, Yang, Liu, Liu, Jiayun
Published in Cancer control (01.01.2025)
Published in Cancer control (01.01.2025)
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Risk and protective factors in Parkinson's disease: a simultaneous and prospective study with classical statistical and novel machine learning models
Gialluisi, Alessandro, De Bartolo, Maria Ilenia, Costanzo, Simona, Belvisi, Daniele, Falciglia, Stefania, Ricci, Moreno, Di Castelnuovo, Augusto, Panzera, Teresa, Donati, Maria Benedetta, Fabbrini, Giovanni, de Gaetano, Giovanni, Berardelli, Alfredo, Iacoviello, Licia
Published in Journal of neurology (01.09.2023)
Published in Journal of neurology (01.09.2023)
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Prediction of Medication-Related Osteonecrosis of the Jaw in Patients Receiving Antiresorptive Therapy Using Machine Learning Models
Warin, Kritsasith, Lochanachit, Sirasit, Pavarangkoon, Praphan, Techapanurak, Engkarat, Somyanonthanakul, Rachasak
Published in Journal of oral and maxillofacial surgery (01.03.2025)
Published in Journal of oral and maxillofacial surgery (01.03.2025)
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Prediction of Chronic Periodontitis Severity Using Machine Learning Models Based On Salivary Bacterial Copy Number
Kim, Eun-Hye, Kim, Seunghoon, Kim, Hyun-Joo, Jeong, Hyoung-oh, Lee, Jaewoong, Jang, Jinho, Joo, Ji-Young, Shin, Yerang, Kang, Jihoon, Park, Ae Kyung, Lee, Ju-Youn, Lee, Semin
Published in Frontiers in cellular and infection microbiology (16.11.2020)
Published in Frontiers in cellular and infection microbiology (16.11.2020)
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Noninvasive diagnosis of significant liver fibrosis in patients with chronic hepatitis B using nomogram and machine learning models
Jiang, Chuan, Xu, Zhenyu, Liu, Jinqing, Li, Ronghua, Chen, Keyu, Peng, Wenting, Xiao, Yueming, Cheng, Da, Fu, Lei, Peng, Shifang
Published in Scientific reports (02.01.2025)
Published in Scientific reports (02.01.2025)
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Understanding and overcoming the technical challenges in using in silico predictions in regulatory decisions of complex toxicological endpoints – A pesticide perspective for regulatory toxicologists with a focus on machine learning models
Burgoon, Lyle D., Kluxen, Felix M., Frericks, Markus
Published in Regulatory toxicology and pharmacology (01.01.2023)
Published in Regulatory toxicology and pharmacology (01.01.2023)
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Predicting Hydration Status Using Machine Learning Models From Physiological and Sweat Biomarkers During Endurance Exercise: A Single Case Study
Wang, Shu, Lafaye, Celine, Saubade, Mathieu, Besson, Cyril, Margarit-Taule, Josep Maria, Gremeaux, Vincent, Liu, Shih-Chii
Published in IEEE journal of biomedical and health informatics (01.09.2022)
Published in IEEE journal of biomedical and health informatics (01.09.2022)
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4646 CT-DERIVED RADIOMICS ANALYSIS OF DIABETIC NEPHROPATHY BY MACHINE LEARNING MODELS
Chung, Eui Seok, Lee, Eun Ji, Yoon, Jongjin, Lee, Haekyung, Kim, Hyoungnae, Noh, Hyunjin, Kwon, Soon Hyo, Jeon, Jin Seok
Published in Nephrology, dialysis, transplantation (14.06.2023)
Published in Nephrology, dialysis, transplantation (14.06.2023)
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Exploring Machine Learning Models for Soil Nutrient Properties Prediction: A Systematic Review
Folorunso, Olusegun, Ojo, Oluwafolake, Busari, Mutiu, Adebayo, Muftau, Joshua, Adejumobi, Folorunso, Daniel, Ugwunna, Charles Okechukwu, Olabanjo, Olufemi, Olabanjo, Olusola
Published in Big data and cognitive computing (01.06.2023)
Published in Big data and cognitive computing (01.06.2023)
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Evaluation of Machine Learning Models for Classifying Upper Extremity Exercises Using Inertial Measurement Unit-Based Kinematic Data
Hua, Andrew, Chaudhari, Pratik, Johnson, Nicole, Quinton, Joshua, Schatz, Bruce, Buchner, David, Hernandez, Manuel E.
Published in IEEE journal of biomedical and health informatics (01.09.2020)
Published in IEEE journal of biomedical and health informatics (01.09.2020)
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The framing of time-dependent machine learning models improves risk estimation among young individuals with acute coronary syndromes
Carvalho, L S F, Nogueira, A C C, Fernandez, M D, Soares, A A M, Rezende, T B, Avila, S E F, Alexim, G, Sposito, A C
Published in European heart journal (09.11.2023)
Published in European heart journal (09.11.2023)
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Development of machine learning models to predict RT-PCR results for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in patients with influenza-like symptoms using only basic clinical data
Langer, Thomas, Favarato, Martina, Giudici, Riccardo, Bassi, Gabriele, Garberi, Roberta, Villa, Fabiana, Gay, Hedwige, Zeduri, Anna, Bragagnolo, Sara, Molteni, Alberto, Beretta, Andrea, Corradin, Matteo, Moreno, Mauro, Vismara, Chiara, Perno, Carlo Federico, Buscema, Massimo, Grossi, Enzo, Fumagalli, Roberto
Published in Scandinavian journal of trauma, resuscitation and emergency medicine (01.12.2020)
Published in Scandinavian journal of trauma, resuscitation and emergency medicine (01.12.2020)
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Training machine learning models to predict 30-day mortality in patients discharged from the emergency department: a retrospective, population-based registry study
Blom, Mathias Carl, Ashfaq, Awais, Sant'Anna, Anita, Anderson, Philip D, Lingman, Markus
Published in BMJ open (01.08.2019)
Published in BMJ open (01.08.2019)
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