Περίληψη:
Feasibility-reliability control of Telemedicine Systems (TS) integrated with Multimedia Systems (MS) and Artificial intelligence (AI) for remote e-Multidisciplinary Oncology Conference in Breast Cancer. Material and Methods: Forty (n1=40) patients suffering from breast surgical oncology malignant (n2=32) and non-malignant (n3=8) diseases classified to seven categories: Nipple Discharge, Dominant Breast Mass, Occult Breast Lesion, Early Breast Carcinoma, Advanced Breast Carcinoma, Recurrent Breast Carcinoma) and treated clinically with the standard diagnostic (Mammography, US, MRI, Cytology, Pathology, BRCA1/2 Mutation Predisposition and Breast Cancer Risk Analysis) surgical, auxiliary therapeutic methods. Then clinical decisions compared to those proposed remotely by the virtual AI supported e-Oncology Conference for each patient. Results: In four (n4=4) out of forty patients (TS, MS and AI) supported decision making and surgical treatment proposal including postoperative Radiotherapy proposal was not as clear as expected. Non-output answer for non-malignant breast pathologies (n3=8) was accurately indicated by (MS and AI). Mean accuracy of (TS, MS and AI) for: 1.Surgical Operative Planning including Rad=94.1%, 2.Chem=96.8%, 3.Horm=96.7% [In 95%, (Confidence interval: 85-99%)]. Conclusion: High feasibility-reliability of the virtual AI supported e-Multidisciplinary Oncology Conference for remote decision making and surgical planning and for optimum outcomes in Breast Cancer treatment makes it a clinical necessity especially for the periphery of Hellas. © 2022 The authors and IOS Press.
Συγγραφείς:
Mammas, C.S.
Mamma, A.S.
Papaxoinis, G.
Georgiou, I.
Λέξεις-κλειδιά:
Cytology; Decision making; Diagnosis; Diseases; Multimedia systems; Pathology; Risk analysis; Risk assessment; Surgery, Breast Cancer; Breast carcinomas; Breast surgery; Classifieds; Decisions makings; E-multidisciplinary oncology conference; Patient's suffering; Tele-cytology; Telemedicine systems; Teleradiology, Oncology, artificial intelligence; breast tumor; female; human; reproducibility; technology; tumor recurrence, Artificial Intelligence; Breast Neoplasms; Female; Humans; Neoplasm Recurrence, Local; Reproducibility of Results; Technology
