Resultados de búsqueda - Classification algorithms

5.K. Workshop: Innovative methods for population health research: lessons from the European Joint Action InfAct...16th World Congress on Public Health (WCPH2020), (virtual congress...

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Smart Work Injury Management (SWIM) System: Artificial Intelligence in Work Disability Management. por Cheng, Andy S. K., Ng, Peter H. F., Sin, Zackary P. T., Lai, Sun H. S., Law, S. W.

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Multi-class motor imagery EEG classification using collaborative representation-based semi-supervised extreme learning machine. por She, Qingshan, Zou, Jie, Luo, Zhizeng, Nguyen, Thinh, Li, Rihui, Zhang, Yingchun

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Classification of heart sounds based on the combination of the modified frequency wavelet transform and convolutional neural network. por Chen, Yongchao, Wei, Shoushui, Zhang, Yatao

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Convolutional neural network for detection and classification of seizures in clinical data. por Iešmantas, Tomas, Alzbutas, Robertas

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Contour-based lung shape analysis in order to tuberculosis detection: modeling and feature description. por Afzali, Ali, Babapour Mofrad, Farshid, Pouladian, Majid

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EORTC QLU-C10D value sets for Austria, Italy, and Poland. por Gamper, E. M., King, M. T., Norman, R., Efficace, F., Cottone, F., Holzner, B., Kemmler, G.

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Optimal matrix size of chest radiographs for computer-aided detection on lung nodule or mass with deep learning. por Kim, Young-Gon, Lee, Sang Min, Lee, Kyung Hee, Jang, Ryoungwoo, Seo, Joon Beom, Kim, Namkug

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High spatiotemporal resolution dynamic contrast-enhanced MRI improves the image-based discrimination of histopathology risk groups of peripheral zone prostate cancer: a supervised... por Winkel, David J., Breit, Hanns-Christian, Block, Tobias K., Boll, Daniel T., Heye, Tobias J.

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Diagnostic accuracy of CT pulmonary angiography in suspected pulmonary hypertension. por Swift, Andrew J., Dwivedi, Krit, Johns, Chris, Garg, Pankaj, Chin, Matthew, Currie, Ben J, Rothman, Alex MK, Capener, Dave, Shahin, Yousef, Elliot, Charlie A, Charalampopolous, Thanos, Sabroe, Ian, Rajaram, Smitha, Hill, Catherine, Wild, Jim M., Condliffe, Robin, Kiely, David G.

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Automated classification of solid renal masses on contrast-enhanced computed tomography images using convolutional neural network with decision fusion. por Zabihollahy, Fatemeh, Schieda, Nicola, Krishna, Satheesh, Ukwatta, Eranga

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Adding Continuous Vital Sign Information to Static Clinical Data Improves the Prediction of Length of Stay After Intubation: A Data-Driven Machine Learning Approach. por Castiñeira, David, Schlosser, Katherine R., Geva, Alon, Rahmani, Amir R., Fiore, Gaston, Walsh, Brian K., Smallwood, Craig D., Arnold, John H., Santillana, Mauricio

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Importance of phase enhancement for machine learning classification of solid renal masses using texture analysis features at multi-phasic CT. por Schieda, Nicola, Nguyen, Kathleen, Thornhill, Rebecca E., McInnes, Matthew D. F., Wu, Mark, James, Nick

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Characterization of solid renal neoplasms using MRI-based quantitative radiomics features. por Said, Daniela, Hectors, Stefanie J., Wilck, Eric, Rosen, Ally, Stocker, Daniel, Bane, Octavia, Beksaç, Alp Tuna, Lewis, Sara, Badani, Ketan, Taouli, Bachir

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Rage Against the Machine: Advancing the study of aggression ethology via machine learning. por Goodwin, Nastacia L., Nilsson, Simon R.O., Golden, Sam A.

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An Innovative Excited-ACS-IDGWO Algorithm for Optimal Biomedical Data Feature Selection. por Segera, Davies, Mbuthia, Mwangi, Nyete, Abraham

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Predicting Gram-Positive Bacterial Protein Subcellular Location by Using Combined Features. por Li, Feng-Min, Gao, Xiao-Wei

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Next-Generation Radiogenomics Sequencing for Prediction of EGFR and KRAS Mutation Status in NSCLC Patients Using Multimodal Imaging and Machine Learning Algorithms. por Shiri, Isaac, Maleki, Hasan, Hajianfar, Ghasem, Abdollahi, Hamid, Ashrafinia, Saeed, Hatt, Mathieu, Zaidi, Habib, Oveisi, Mehrdad, Rahmim, Arman

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Automated lung cancer diagnosis using three-dimensional convolutional neural networks. por Perez, Gustavo, Arbelaez, Pablo

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A two-stage approach towards protein secondary structure classification. por Ghosh, Kushal Kanti, Ghosh, Soulib, Sen, Sagnik, Sarkar, Ram, Maulik, Ujjwal

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