Survivability Prognosis for Lung Cancer Patients at Different Severity Stages by a Risk Factor-Based Bayesian Network Modeling.
Lung cancer is a major reason of mortalities. Estimating the survivability for this disease has become a key issue to families, hospitals, and countries. A conditional Gaussian Bayesian network model was presented in this study. This model considered 15 risk factors to predict the survivability of a...
| Published in: | Journal of Medical Systems Vol. 44; no. 3; pp. 1 - 12 |
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| Main Authors: | , , , |
| Format: | algorithm equations & formulas research tables/charts Journal Article |
| Published: |
Springer Nature
Mar2020
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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=142023377&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 142023377 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01485598 4N0 jtl: Journal of Medical Systems issn: 01485598 maglogo: N pubinfo: dt: Mar2020 vid: 44 iid: 3 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 142023377 142023377 142023377 10.1007/s10916-020-1537-5 142023377 ppf: 1 ppct: 11 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Survivability Prognosis for Lung Cancer Patients at Different Severity Stages by a Risk Factor-Based Bayesian Network Modeling. aug: au: Wang, Kung-Jeng Chen, Jyun-Lin Chen, Kun-Huang Wang, Kung-Min affil: Department of Industrial Management, National Taiwan University of Science and Technology, No.43, Sec. 4, Keelung Rd., Da'an Dist., 106, Taipei, Taiwan, People's Republic of China sug: subj: Lung Neoplasms Prognosis Cancer Patients Psychosocial Factors Neoplasm Staging Severity of Illness Probability Risk Assessment Models, Statistical Neoplasms by Site Human Survival Analysis Lung Neoplasms Risk Factors Descriptive Statistics Comparative Studies Retrospective Design Record Review Prospective Studies Health Care Costs Economic Aspects of Illness National Health Information Network Resource Databases Lung Neoplasms Therapy Chemotherapy, Cancer Male Female Sex Factors Environment Comorbidity Length of Stay Help Seeking Behavior Chronic Disease Odds Ratio Cancer Care Facilities Health Resource Utilization Age Factors Geographic Factors Residence Characteristics Time Factors Funding Source Male Female ab: Lung cancer is a major reason of mortalities. Estimating the survivability for this disease has become a key issue to families, hospitals, and countries. A conditional Gaussian Bayesian network model was presented in this study. This model considered 15 risk factors to predict the survivability of a lung cancer patient at 4 severity stages. We surveyed 1075 patients. The presented model is constructed by using the demographic, diagnosed-based, and prior-utilization variables. The proposed model for the survivability prognosis at different four stages performed R2 of 93.57%, 86.83%, 67.22%, and 52.94%, respectively. The model predicted the lung cancer survivability with high accuracy compared with the reported models. Our model also shows that it reached the ceiling of an ideal Bayesian network. pubtype: Academic Journal doctype: algorithm equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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