Applications of Neural Network-Based Plan-Cancer Method for Primary Diagnosis of Mesothelioma Cancer.
"Malignant mesothelioma (MM)" is an uncommon although fatal form of cancer. The proper MM diagnosis is crucial for efficient therapy and has significant medicolegal implications. Asbestos is a carcinogenic material that poses a health risk to humans. One of the most severe types of cancer induced by...
| Publicado en: | BioMed Research International Vol. 2023; pp. 1 - 11 |
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| Autores principales: | , , , , , , |
| Formato: | pictorial research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
2/4/2023
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=161758527&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 161758527 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 23146133 FT2T jtl: BioMed Research International issn: 23146133 maglogo: N pubinfo: dt: 2/4/2023 vid: 2023 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 161758527 161758527 161758527 10.1155/2023/3164166 161758527 ppf: 1 ppct: 10 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Applications of Neural Network-Based Plan-Cancer Method for Primary Diagnosis of Mesothelioma Cancer. aug: au: Kapila, Dhiraj Panwar, Sarika Raja, M. K. Mohan Maruga Mondal, Tamal Rafi, Shaik Mohammad Singh, Suryabhan Pratap Kumar, Bhupendra affil: Department of Computer Science & Engineering, Lovely Professional University, Phagwara, Punjab, India sug: subj: Neural Networks (Computer) Mobile Applications Mesothelioma, Malignant Diagnosis Mesothelioma Pathology Cancer Patients Artificial Intelligence Methods Human Asbestos Analysis Dyspnea Symptoms Early Diagnosis Algorithms Machine Learning Methods Deep Learning Methods Carcinogens, Environmental Data Analysis Software ab: "Malignant mesothelioma (MM)" is an uncommon although fatal form of cancer. The proper MM diagnosis is crucial for efficient therapy and has significant medicolegal implications. Asbestos is a carcinogenic material that poses a health risk to humans. One of the most severe types of cancer induced by asbestos is "malignant mesothelioma." Prolonged shortness of breath and continuous pain are the most typical symptoms of the condition. The importance of early treatment and diagnosis cannot be overstated. The combination "epithelial/mesenchymal appearance of MM," however, makes a definite diagnosis difficult. This study is aimed at developing a deep learning system for medical diagnosis MM automatically. Otherwise, the sickness might cause patients to succumb to death in a short amount of time. Various forms of artificial intelligence algorithms for successful "Malignant Mesothelioma illness" identification are explored in this research. In relation to the concept of traditional machine learning, the techniques support "Vector Machine, Neural Network, and Decision Tree" are chosen. SPSS has been used to analyze the result regarding the applications of Neural Network helps to diagnose MM. pubtype: Academic Journal doctype: pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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