Search Results - computer 3 diagnosis｜((data algorithms) OR (((descent algorithm) OR (learning algorithms))))* :: K.UTB vyhledávací portál

Deep ensemble learning for Alzheimer's disease classification

by An, Ning, Ding, Huitong, Yang, Jiaoyun, Au, Rhoda, Ang, Ting F.A.
Published in Journal of biomedical informatics (01.05.2020)

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Learning from vertically distributed data across multiple sites: An efficient privacy-preserving algorithm for Cox proportional hazards model with variable selection

by Miao, Guanhong, Yu, Lei, Yang, Jingyun, Bennett, David A., Zhao, Jinying, Wu, Samuel S.
Published in Journal of biomedical informatics (01.01.2024)

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Analyzing the effect of data preprocessing techniques using machine learning algorithms on the diagnosis of COVID‐19

by Erol, Gizemnur, Uzbaş, Betül, Yücelbaş, Cüneyt, Yücelbaş, Şule
Published in Concurrency and computation (25.12.2022)

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Teaching a Machine to Feel Postoperative Pain: Combining High‐Dimensional Clinical Data with Machine Learning Algorithms to Forecast Acute Postoperative Pain

by Tighe, Patrick J., Harle, Christopher A., Hurley, Robert W., Aytug, Haldun, Boezaart, Andre P., Fillingim, Roger B.
Published in Pain medicine (Malden, Mass.) (01.07.2015)

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Determining the most accurate machine learning algorithms for medical diagnosis using the monk' problems database and statistical measurements

by Avuçlu, Emre
Published in Journal of experimental & theoretical artificial intelligence (17.02.2025)

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Deep Learning Algorithms with Demographic Information Help to Detect Tuberculosis in Chest Radiographs in Annual Workers’ Health Examination Data

by Heo, Seok-Jae, Kim, Yangwook, Yun, Sehyun, Lim, Sung-Shil, Kim, Jihyun, Nam, Chung-Mo, Park, Eun-Cheol, Jung, Inkyung, Yoon, Jin-Ha
Published in International journal of environmental research and public health (16.01.2019)

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Non-invasive assessment of NAFLD as systemic disease—A machine learning perspective

by Canbay, Ali, Kälsch, Julia, Neumann, Ursula, Rau, Monika, Hohenester, Simon, Baba, Hideo A., Rust, Christian, Geier, Andreas, Heider, Dominik, Sowa, Jan-Peter
Published in PloS one (26.03.2019)

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FWNNet: Presentation of a New Classifier of Brain Tumor Diagnosis Based on Fuzzy Logic and the Wavelet-Based Neural Network Using Machine-Learning Methods

by Ahmadi, Mohsen, Dashti Ahangar, Fatemeh, Astaraki, Nikoo, Abbasi, Mohammad, Babaei, Behzad
Published in Computational intelligence and neuroscience (2021)

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Performance Analysis of Conventional Machine Learning Algorithms for Identification of Chronic Kidney Disease in Type 1 Diabetes Mellitus Patients

by Chowdhury, Nakib Hayat, Reaz, Mamun Bin Ibne, Haque, Fahmida, Ahmad, Shamim, Ali, Sawal Hamid Md, A Bakar, Ahmad Ashrif, Bhuiyan, Mohammad Arif Sobhan
Published in Diagnostics (Basel) (03.12.2021)

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Effect of Data Scaling Methods on Machine Learning Algorithms and Model Performance

by Ahsan, Md, Mahmud, M., Saha, Pritom, Gupta, Kishor, Siddique, Zahed
Published in Technologies (Basel) (01.09.2021)

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Comparison of machine-learning algorithms to build a predictive model for detecting undiagnosed diabetes - ELSA-Brasil: accuracy study

by Olivera, André Rodrigues, Roesler, Valter, Iochpe, Cirano, Schmidt, Maria Inês, Vigo, Álvaro, Barreto, Sandhi Maria, Duncan, Bruce Bartholow
Published in São Paulo medical journal (01.05.2017)

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Integrating genetics, metabolites, and clinical characteristics in predicting cardiometabolic health outcomes using machine learning algorithms – A systematic review

by Zhu, Xianyu, Ventura, Eduard F., Bansal, Sakshi, Wijeyesekera, Anisha, Vimaleswaran, Karani S.
Published in Computers in biology and medicine (01.03.2025)

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GeneSelectML: a comprehensive way of gene selection for RNA-Seq data via machine learning algorithms

by Dag, Osman, Kasikci, Merve, Ilk, Ozlem, Yesiltepe, Metin
Published in Medical & biological engineering & computing (01.01.2023)

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Exploit fully automatic low-level segmented PET data for training high-level deep learning algorithms for the corresponding CT data

by Gsaxner, Christina, Roth, Peter M., Wallner, Jürgen, Egger, Jan
Published in PloS one (05.03.2019)

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Exploring machine learning algorithms in sickle cell disease patient data: A systematic review

by Machado, Tiago Fernandes, Neto, Francisco das Chagas Barros, Gonçalves, Marilda de Souza, Barbosa, Cynara Gomes, Barreto, Marcos Ennes
Published in PloS one (11.11.2024)

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A Machine Learning Algorithm to Predict Severe Sepsis and Septic Shock: Development, Implementation, and Impact on Clinical Practice

Published in Critical care medicine

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A prospective multicenter validation study of a machine learning algorithm classifier on quantitative electroencephalogram for differentiating between dementia with Lewy bodies and Alzheimer’s dementia

by Suzuki, Yukiko, Suzuki, Maki, Shigenobu, Kazue, Shinosaki, Kazuhiro, Aoki, Yasunori, Kikuchi, Hirokazu, Baba, Toru, Hashimoto, Mamoru, Araki, Toshihiko, Johnsen, Kristinn, Ikeda, Manabu, Mori, Etsuro
Published in PloS one (31.03.2022)

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Biomedical Image Classification in a Big Data Architecture Using Machine Learning Algorithms

by Tchito Tchapga, Christian, Mih, Thomas Attia, Tchagna Kouanou, Aurelle, Fozin Fonzin, Theophile, Kuetche Fogang, Platini, Mezatio, Brice Anicet, Tchiotsop, Daniel
Published in Journal of healthcare engineering (2021)

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