{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,20]],"date-time":"2026-08-20T13:22:02Z","timestamp":1787232122330,"version":"build-2736575974"},"reference-count":20,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2022,12,15]],"date-time":"2022-12-15T00:00:00Z","timestamp":1671062400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Diagnostics"],"abstract":"<jats:p>The quantitative prediction of the SYNTAX score for cardiovascular artery disease patients using the inverse problem algorithm (IPA) technique in artificial intelligence was explored in this study. A 29-term semi-empirical formula was defined according to seven risk factors: (1) age, (2) mean arterial pressure, (3) body surface area, (4) pre-prandial blood glucose, (5) low-density-lipoprotein cholesterol, (6) Troponin I, and (7) C-reactive protein. Then, the formula was computed via the STATISTICA 7.0 program to obtain a compromised solution for a 405-patient dataset with a specific loss function [actual-predicted]2 as low as 3.177, whereas 0.0 implies a 100% match between the prediction and observation via \u201cthe lower, the better\u201d principle. The IPA technique first created a data matrix [405 \u00d7 29] from the included patients\u2019 data and then attempted to derive a compromised solution of the column matrix of 29-term coefficients [29 \u00d7 1]. The correlation coefficient, r2, of the regression line for the actual versus predicted SYNTAX score was 0.8958, showing a high coincidence among the dataset. The follow-up verification based on another 105 patients\u2019 data from the same group also had a high correlation coefficient of r2 = 0.8304. Nevertheless, the verified group\u2019s low derived average AT (agreement) (ATavg = 0.308 \u00b1 0.193) also revealed a slight deviation between the theoretical prediction from the STATISTICA 7.0 program and the grades assigned by clinical cardiologists or interventionists. The predicted SYNTAX scores were compared with earlier reported findings based on a single-factor statistical analysis or scanned images obtained by sonography or cardiac catheterization. Cardiologists can obtain the SYNTAX score from the semi-empirical formula for an instant referral before performing a cardiac examination.<\/jats:p>","DOI":"10.3390\/diagnostics12123180","type":"journal-article","created":{"date-parts":[[2022,12,16]],"date-time":"2022-12-16T02:16:41Z","timestamp":1671157001000},"page":"3180","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Quantitative Prediction of SYNTAX Score for Cardiovascular Artery Disease Patients via the Inverse Problem Algorithm Technique as Artificial Intelligence Assessment in Diagnostics"],"prefix":"10.3390","volume":"12","author":[{"given":"Meng-Chiung","family":"Lin","sequence":"first","affiliation":[{"name":"Department of Biological Science and Technology, National Yang Ming Chiao Tung University, Hsinchu 10041, Taiwan"},{"name":"Division of Gastroenterology, Department of Internal Medicine, Taichung Armed Forces General Hospital, Taichung 40044, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vincent S.","family":"Tseng","sequence":"additional","affiliation":[{"name":"Department of Computer Science, National Yang Ming Chiao Tung University, Hsinchu 10041, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chih-Sheng","family":"Lin","sequence":"additional","affiliation":[{"name":"Department of Radiology, BenQ Medical Center, The Affiliated BenQ Hospital of the Nanjing Medical University, Nanjing 210000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shao-Wen","family":"Chiu","sequence":"additional","affiliation":[{"name":"Department of Pet Business Management, Taipei University of Marine Technology, Taipei 10001, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9485-4722","authenticated-orcid":false,"given":"Lung-Kwang","family":"Pan","sequence":"additional","affiliation":[{"name":"Department of Medical Imaging and Radiological Science, Central Taiwan University of Science and Technology, Taichung 40044, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lung-Fa","family":"Pan","sequence":"additional","affiliation":[{"name":"Department of Medical Imaging and Radiological Science, Central Taiwan University of Science and Technology, Taichung 40044, Taiwan"},{"name":"Department of Cardiology, Taichung Armed Forces General Hospital, Taichung 40044, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,12,15]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"99","DOI":"10.4103\/1995-705X.151081","article-title":"The SYNTAX score can predict major adverse cardiac events following percutaneous coronary intervention","volume":"15","author":"Alidoosti","year":"2014","journal-title":"Hear. 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