Resultados de búsqueda - Classification algorithms

Role of land use and land cover in residential exposures to agricultural pesticide models. por Vannier, Clémence, Chevrier, Cécile, Hubert-Moy, Laurence

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AI MSK clinical applications: cartilage and osteoarthritis. por Joseph, Gabby B., McCulloch, Charles E., Sohn, Jae Ho, Pedoia, Valentina, Majumdar, Sharmila, Link, Thomas M.

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Automated detection and segmentation of sclerotic spinal lesions on body CTs using a deep convolutional neural network. por Chang, Connie Y., Buckless, Colleen, Yeh, Kaitlyn J., Torriani, Martin

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Deep learning detection of subtle fractures using staged algorithms to mimic radiologist search pattern. por Ren, Mark, Yi, Paul H.

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Automatic machine learning based on native T1 mapping can identify myocardial fibrosis in patients with hypertrophic cardiomyopathy. por Peng, Wan-Lin, Zhang, Tian-Jing, Shi, Ke, Li, Hai-Xia, Li, Ying, He, Sen, Li, Chen, Xia, Dong, Xia, Chun-Chao, Li, Zhen-Lin

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Interobserver reliability of the Gehweiler classification and treatment strategies of isolated atlas fractures: an internet-based multicenter survey among spine surgeons. por Laubach, Markus, Pishnamaz, Miguel, Scholz, Matti, Spiegl, Ulrich, Sellei, Richard Martin, Herren, Christian, Hildebrand, Frank, Kobbe, Philipp

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Deep CNN with Hybrid Binary Local Search and Particle Swarm Optimizer for Exudates Classification from Fundus Images. por Ramya, J., Rajakumar, M. P., Maheswari, B. Uma

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Machine learning based evaluation of clinical and pretreatment 18F-FDG-PET/CT radiomic features to predict prognosis of cervical cancer patients. por Nakajo, Masatoyo, Jinguji, Megumi, Tani, Atsushi, Yano, Erina, Hoo, Chin Khang, Hirahara, Daisuke, Togami, Shinichi, Kobayashi, Hiroaki, Yoshiura, Takashi

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Combining neuroimaging and behavior to discriminate children with attention deficit-hyperactivity disorder with and without prenatal alcohol exposure. por O'Neill, Joseph, O'Connor, Mary J., Kalender, Guldamla, Ly, Ronald, Ng, Andrea, Dillon, Andrea, Narr, Katherine L., Loo, Sandra K., Alger, Jeffry R., Levitt, Jennifer G.

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Detection of arterial pressure waveform error using machine learning trained algorithms. por Rinehart, Joseph, Tang, Jia, Nam, Jennifer, Sha, Sophie, Mensah, Paulette, Maxwell, Hailey, Calderon, Michael-David, Ma, Michael, Joosten, Alexandre

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Prediction and Risk Assessment Models for Subarachnoid Hemorrhage: A Systematic Review on Case Studies. por Sengupta, Jewel, Alzbutas, Robertas

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EEG-Based Multiword Imagined Speech Classification for Persian Words. por Asghari Bejestani, M. R., Mohammad Khani, Gh. R., Nafisi, V. R., Darakeh, F.

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Diagnostic performance of deep learning models for detecting bone metastasis on whole-body bone scan in prostate cancer. por Han, Sangwon, Oh, Jungsu S., Lee, Jong Jin

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Removing barriers for digital health through organizing ambidexterity in hospitals. por Gleiss, Alexander, Lewandowski, Stefanie

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Classification of electrocardiogram signals with waveform morphological analysis and support vector machines. por Li, Hongqiang, An, Zhixuan, Zuo, Shasha, Zhu, Wei, Cao, Lu, Mu, Yuxin, Song, Wenchao, Mao, Quanhua, Zhang, Zhen, Li, Enbang, García, Juan Daniel Prades

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Pandemic tele-smart: a contactless tele-health system for efficient monitoring of remotely located COVID-19 quarantine wards in India using near-field communication and natural lan... por Balasubramanian, Vishal, Vivekanandhan, Sapthagirivasan, Mahadevan, Venkatesh

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Development of a tissue discrimination electrode embedded surgical needle using vibro-tactile feedback derived from electric impedance spectroscopy. por Kent, Brayden, Rossa, Carlos

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Associating brain imaging phenotypes and genetic in Alzheimer's disease via JSCCA approach with autocorrelation constraints. por Wei, Kai, Kong, Wei, Wang, Shuaiqun

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Cross sectional association between cytomegalovirus seropositivity, inflammation and cognitive impairment in elderly cancer survivors. por Vivek, Sithara, Nelson, Heather Hammond, Prizment, Anna E., Faul, Jessica, Crimmins, Eileen M., Thyagarajan, Bharat

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Gender, activity participation, education levels, and depressive symptoms predict activity participation levels at post-cardiac rehabilitation. por Kim, Young Joo, Swift, Damon L., Houmard, Joseph A., Wu, Qiang, Sears, Samuel F., Paul, Alyssa M.

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