Artificial Neural Network Assisted Cancer Risk Prediction of Oral Precancerous Lesions.
The incidence of oral cancer is still increasing. It has become very common in patients with malignant tumors, which has forced medical personnel to continuously explore its treatment methods. What kind of method can effectively and correctly diagnose the disease in the early stage and improve the s...
| Published in: | BioMed Research International pp. 1 - 11 |
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| Main Authors: | , , , , , |
| Format: | algorithm equations & formulas pictorial research tables/charts Journal Article |
| Published: |
Wiley-Blackwell
9/22/2022
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=159271298&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 159271298 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 23146133 FT2T jtl: BioMed Research International issn: 23146133 maglogo: N pubinfo: dt: 9/22/2022 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 159271298 159271298 159271298 10.1155/2022/7352489 159271298 ppf: 1 ppct: 10 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Artificial Neural Network Assisted Cancer Risk Prediction of Oral Precancerous Lesions. aug: au: Chen, Wenao Zeng, Ruijie Jin, Yiyao Sun, Xi Zhou, Zihan Zhu, Chao affil: I.M. Borovsky Institute of Dentistry, I.M. Sechenov First Moscow State Medical University, Moscow 119991, Russia sug: subj: Neural Networks (Computer) Precancerous Conditions Risk Factors Mouth Neoplasms Risk Factors Risk Assessment Prediction Models Early Detection of Cancer Methods Human Algorithms Mouth Neoplasms Prognosis Artificial Intelligence ab: The incidence of oral cancer is still increasing. It has become very common in patients with malignant tumors, which has forced medical personnel to continuously explore its treatment methods. What kind of method can effectively and correctly diagnose the disease in the early stage and improve the survival rate has become one of the research topics that have attracted much attention. Aiming at this problem, it has great research significance for the field of oral precancerous lesions diagnosis. With the in-depth research on oral precancerous diagnosis, the research on artificial neural network (ANN) in medical diagnosis is gradually carried out. Its performance advantage is of great significance to solve the problem of early and correct disease diagnosis. This paper aimed to investigate the application of ANN-assisted cancer risk prediction method in risk prediction of oral precancerous lesions. Through the analysis and research of ANN and oral cancer, the construction of oral cancer risk prediction model was applied to solve the problem of improving the survival rate of oral cancer patients. In this paper, ANN and oral precancerous lesions were analyzed, the performance of the algorithm was experimentally analyzed, and the relevant theoretical formulas were used to explain. The results showed that the method had higher accuracy than traditional forecasting methods. When N = 2 , the output accuracy was above 90%. It can be seen that the algorithm can meet the needs of the diagnosis of high-risk groups of oral cancer lesions, and the diagnosis efficiency and patient survival rate has been greatly improved. pubtype: Academic Journal doctype: algorithm equations & formulas pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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