Retraction Notice: Medical Diagnosis of Lung Diseases Using Data Mining Techniques from Iris Images: A Retrospective Controlled Study

• Published in: 2022 13th Asian Control Conference (ASCC) p. 1
• Main Authors: Choi, Seong-Hwan, Park, Miso S., Park, Seong-Il, Yoo, Ho-Ryong, Park, Hyun-Jung
• Format: Conference Proceeding
• Language: English
• Published: ACA 04-05-2022
• ISSN: 2770-8373
• DOI: 10.23919/ASCC56756.2022.10207764

The study of structural and pigment changes in the iris concerning specific iris compartments is known as iridology. The authors looked into the relationship between connective tissue density in the lung region of the iris and patients with lung disorders in this study. From 2019 to 2021, we collected iris images from 375 patients who visited Korean Medicine clinics and hospitals in Daejeon. According to their medical records, the patients were divided into two groups: the lung disease group and the control group. Two iridology experts independently examined the patients' iris images and identified lacunas, crypts, and pigment spots. The Kohen's kappa values between the two researchers were 0.76 for lacunas, 0.73 for crypts, and 0.74 for pigment spots. There were 16 (27 percent) lacunae, 27 (45 percent) crypts, and 7 (12 percent) pigment spots among the 60 lung disease group patients. Meanwhile, 70 (22 percent) of the 315 patients in the control group had lacunae, 83 (26 percent) had crypts, and 33 (10 percent) had pigment spots. Patients with lung disease had a higher percentage of lacunae, crypts, and pigment spots in the lung region of the iris than the control group. The difference was only significant for the crypts, according to the Chi-square test. In clinical iridology, people with low tissue density in the lung area of the iris are often classified as Taeeumin, and they are susceptible to lung disease. A follow-up study is required in this area.