A novel artificial intelligence approach to detect the breast cancer using KNNet technique with EPM gene profiling.

Joshi, Shubham; Natteshan, N V S; Rastogi, Ravi; Sampathkumar, A; Pandimurugan, V; Sountharrajan, S

Joshi, Shubham; Natteshan, N V S; Rastogi, Ravi; Sampathkumar, A; Pandimurugan, V; Sountharrajan, S.

Afiliação

Joshi S; Department of Computer Science Engineering, Symbiosis Institute of Technology, Symbiosis International (Deemed) University, Pune, India.
Natteshan NVS; School of Computing, Kalasalingam Academy of Research and Education, Krishnan Koil, TN, India.
Rastogi R; Department of CSE, Koneru Lakshmaiah Education Foundation, Vaddeswaram, AP, India.
Sampathkumar A; Department of Applied Cybernetics, Faculty of Science, University of Hradec Kralove, Hradec Kralove, Czech Republic. sampathkumar.arumugam@uhk.cz.
Pandimurugan V; School of Computing, Department of Networking and Communications, SRMIST, Kattankulathur Campus, Chennai, 603203, India.
Sountharrajan S; Department of Computer Science and Engineering, Amrita School of Computing, Amrita Vishwa Vidyapeetham, Chennai, India.

Funct Integr Genomics ; 23(4): 302, 2023 Sep 18.

Article em En | MEDLINE | ID: mdl-37721631

Assuntos

Neoplasias da Mama; Neoplasias Pulmonares; Feminino; Humanos; Neoplasias da Mama/diagnóstico; Neoplasias da Mama/genética; Inteligência Artificial; Algoritmos; Carcinogênese

Palavras-chave

Gene profiling; KNNet-EPM; Neural network; RNN-OCSA; Tumor genesis

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias da Mama / Neoplasias Pulmonares Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Female / Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article

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