Search Results - Random forest algorithms

Using artificial intelligence-based models to predict the risk of mucormycosis among COVID-19 survivors: An experience from a public hospital in India. by Syed-Abdul, Shabbir, Babu, A. Shoban, Bellamkonda, Raja Shekhar, Itumalla, Ramaiah, Acharyulu, GVRK, Krishnamurthy, Surya, Ramana, Y. Venkat Santosh, Mogilicharla, Naresh, Malwade, Shwetambara, Li, Yu-Chuan, Li, Yu-Chuan Jack

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Neonatal Adverse Events' Trigger Tool Setup With Random Forest. by Feng, Kun, Zhang, Li MM, He, Huayun N, You, Xueqin MM, Zhang, Qiannan MM, Wei, Hong, Hua, Ziyu

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Machine learning-based in-hospital mortality prediction models for patients with acute coronary syndrome. by Ke, Jun, Chen, Yiwei, Wang, Xiaoping, Wu, Zhiyong, Zhang, Qiongyao, Lian, Yangpeng, Chen, Feng

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A Machine Learning-Based Holistic Approach to Predict the Clinical Course of Patients within the Alzheimer's Disease Spectrum. by Massetti, Noemi, Russo, Mirella, Franciotti, Raffaella, Nardini, Davide, Mandolini, Giorgio Maria, Granzotto, Alberto, Bomba, Manuela, Delli Pizzi, Stefano, Mosca, Alessandra, Scherer, Reinhold, Onofrj, Marco, Sensi, Stefano L.

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Learning dynamic treatment strategies for coronary heart diseases by artificial intelligence: real-world data-driven study. by Guo, Haihong, Li, Jiao, Liu, Hongyan, He, Jun

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Performance Analysis of Machine Learning and Deep Learning Architectures on Early Stroke Detection Using Carotid Artery Ultrasound Images. by Latha, S., Muthu, P., Lai, Khin Wee, Khalil, Azira, Dhanalakshmi, Samiappan

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Utility of mass spectrometry and artificial intelligence for differentiating primary lung adenocarcinoma and colorectal metastatic pulmonary tumor. by Shigeeda, Wataru, Yosihimura, Ryuichi, Fujita, Yuji, Saiki, Hidekazu, Deguchi, Hiroyuki, Tomoyasu, Makoto, Kudo, Satoshi, Kaneko, Yuka, Kanno, Hironaga, Inoue, Yoshihiro, Saito, Hajime

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A learning approach towards metre-based classification of similar Hindi poems using proposed two-level data transformation. by Naaz, Komal, Singh, Niraj Kumar

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Prediction of robotic neurorehabilitation functional ambulatory outcome in patients with neurological disorders. by Kuo, Chao-Yang, Liu, Chia-Wei, Lai, Chien-Hung, Kang, Jiunn-Horng, Tseng, Sung-Hui, Su, Emily Chia-Yu

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Exploring machine learning to predict depressive relapses of bipolar disorder patients. by Rotenberg, Luisa de Siqueira, Borges-Júnior, Renato Gomes, Lafer, Beny, Salvini, Rogerio, Dias, Rodrigo da Silva

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Use of machine learning to transform complex standardized nursing care plan data into meaningful research variables: a palliative care exemplar. by Macieira, Tamara G R, Yao, Yingwei, Keenan, Gail M

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Discrimination of Patients with Prostate Cancer from Healthy Persons Using a Set of Single Nucleotide Polymorphisms. by Omrani, Mir Davood, Mohammad-Rahimi, Hossein, Basiri, Abbas, Fallahian, Milad, Noroozi, Rezvan, Taheri, Mohammad, Ghafouri-Fard, Soudeh

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Models for Predicting Sentinel and Non-sentinel Lymph Nodes Based on Pre-operative Ultrasonic Breast Imaging to Optimize Axillary Strategies. by Liu, Dongmei, Li, Xia, Lan, Yujia, Zhang, Lei, Wu, Tong, Cui, Hao, Li, Ziyao, Sun, Ping, Tian, Peng, Tian, Jiawei

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Factors associated with surgeon recommendation for additional cast immobilization of a CT-verified nondisplaced scaphoid waist fracture. by Bulstra, Anne Eva J., Crijns, Tom J., Janssen, Stein J., Buijze, Geert A., Ring, David, Jaarsma, Ruurd L., Kerkhoffs, Gino M. M. J., Obdeijn, Miryam C., Doornberg, Job N., The Science of Variation Group, Peters, A., Spoor, A. B., Shrivastava, Abhay, Chauhan, Aakash, Shafritz, Adam, Ilyas, Asif M., Vochteloo, Anne J. H., Powell, Andrew John, Castillo, Alberto Pérez, Godoy-Santos, Alexandre Leme

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Imaging- based prediction of histological clot composition from admission CT imaging. by Hanning, Uta, Sporns, Peter B., Psychogios, Marios N., Jeibmann, Astrid, Minnerup, Jens, Gelderblom, Mathias, Schulte, Karolin, Nawabi, Jawed, Broocks, Gabriel, Meyer, Lukas, Krähling, Hermann, Brehm, Alex, Wildgruber, Moritz, Fiehler, Jens, Kniep, Helge

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Random survival forests for dynamic predictions of a time-to-event outcome using a longitudinal biomarker. by Pickett, Kaci L, Suresh, Krithika, Campbell, Kristen R, Davis, Scott, Juarez-Colunga, Elizabeth

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A Machine Learning Algorithm to Identify Patients at Risk of Unplanned Subsequent Surgery After Intramedullary Nailing for Tibial Shaft Fractures.

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Machine Learning Technique Reveals Prognostic Factors of Vibrant Soundbridge for Conductive or Mixed Hearing Loss Patients. by Koyama, Hajime, Mori, Anjin, Nagatomi, Daisuke, Fujita, Takeshi, Saito, Kazuya, Osaki, Yasuhiro, Yamasoba, Tatsuya, Doi, Katsumi

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Predictors of Receiving a Prosthesis for Adults With Above-Knee Amputations in a Well-Defined Population. by Mundell, Benjamin F., Kremers, Hilal Maradit, Visscher, Sue, Hoppe, Kurtis M., Kaufman, Kenton R.

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Meta-lasso: new insight on infection prediction after minimally invasive surgery. by Cheng, Yuejia, Tang, Qinhua, Li, Xiang, Ma, Liyan, Yuan, Junyi, Hou, Xumin

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