An Image Processing Approach for Detection of Prenatal Heart Disease.
Prenatal heart disease, generally known as cardiac problems (CHDs), is a group of ailments that damage the heartbeat and has recently now become top deaths worldwide. It connects a plethora of cardiovascular diseases risks to the urgent in need of accurate, trustworthy, and effective approaches for...
| Publicado en: | BioMed Research International pp. 1 - 15 |
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| Autores principales: | , , , , , , , , |
| Formato: | equations & formulas research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
8/2/2022
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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=158307731&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 158307731 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 23146133 FT2T jtl: BioMed Research International issn: 23146133 maglogo: N pubinfo: dt: 8/2/2022 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 158307731 158307731 158307731 10.1155/2022/2003184 158307731 ppf: 1 ppct: 14 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: An Image Processing Approach for Detection of Prenatal Heart Disease. aug: au: Selvan, Saravana Thangaraj, S. John Justin Samson Isaac, J. Benil, T. Muthulakshmi, K. Almoallim, Hesham S. Ali Alharbi, Sulaiman Kumar, R. R. Thimothy, Sojan Palukaran affil: Faculty of Engineering & Computer Technology, AIMST University, Bedong, Kedah 08100, Malaysia sug: subj: Heart Diseases Diagnosis Image Processing, Computer Assisted Prenatal Diagnosis Methods Fetal Heart Radiography Human Fetus Cardiovascular Risk Factors Risk Assessment Heart Rate, Fetal Sensitivity and Specificity Probability Fetus, conception to birth ab: Prenatal heart disease, generally known as cardiac problems (CHDs), is a group of ailments that damage the heartbeat and has recently now become top deaths worldwide. It connects a plethora of cardiovascular diseases risks to the urgent in need of accurate, trustworthy, and effective approaches for early recognition. Data preprocessing is a common method for evaluating big quantities of information in the medical business. To help clinicians forecast heart problems, investigators utilize a range of data mining algorithms to examine enormous volumes of intricate medical information. The system is predicated on classification models such as NB, KNN, DT, and RF algorithms, so it includes a variety of cardiac disease-related variables. It takes do with an entire dataset from the medical research database of patients with heart disease. The set has 300 instances and 75 attributes. Considering their relevance in establishing the usefulness of alternate approaches, only 15 of the 75 criteria are examined. The purpose of this research is to predict whether or not a person will develop cardiovascular disease. According to the statistics, naïve Bayes classifier has the highest overall accuracy. pubtype: Academic Journal doctype: equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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