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AIMS Mathematics ; 8(6):14449-14474, 2023.
Article in English | Scopus | ID: covidwho-2306628


During the COVID-19 pandemic, identifying face masks with artificial intelligence was a crucial challenge for decision support systems. To address this challenge, we propose a quadratic Diophantine fuzzy decision-making model to rank artificial intelligence techniques for detecting masks, aiming to prevent the global spread of the disease. Our paper introduces the innovative concept of quadratic Diophantine fuzzy sets (QDFSs), which are advanced tools for modeling the uncertainty inherent in a given phenomenon. We investigate the structural properties of QDFSs and demonstrate that they generalize various fuzzy sets. In addition, we introduce essential algebraic operations, set-theoretical operations, and aggregation operators. Finally, we present a numerical case study that applies our proposed algorithms to select a unique face mask detection method and evaluate the effectiveness of our techniques. Our findings demonstrate the viability of our mask identification methodology during the COVID-19 outbreak. © 2023 the Author(s), licensee AIMS Press.

Journal of Clinical Oncology ; 40(16), 2022.
Article in English | EMBASE | ID: covidwho-2009573


Background: Estrogen receptor positive breast cancer (BC) is the most common type of breast cancer in postmenopausal women and aromatase inhibitors (AI) are the endocrine therapy of choice recommended for these patients. Up to 50% of those treated with an AI develop Arthralgia often resulting in poor adherence and decreased quality of life. Methods: This is a single arm longitudinal pilot study aiming to evaluate the safety, feasibility, acceptability and potential efficacy of TaiChi4Joint, a remotelydelivered 12-week Tai Chi intervention designed for the relief of AI-induced joint pain. Women diagnosed with stage 0-III BC who have been receiving an AI for at least 2 months and reporting arthralgia with a ≥ 4 score on a 0-10 scale for joint pain were eligible for study enrollment. Participants were encouraged to join Tai Chi classes delivered over ZOOM three times a week for 12 weeks. Program engagement strategies include the use of a private Facebook study group and cloud for archiving live class recordings. The program utilizes Text messaging and emails with periodic positive quotes and evidence based information on Tai Chi for facilitating community bonding and class attendance. Participants were invited to complete the following assessments online at baseline, 1, 2 and 3 months intervals from study enrollment: Brief Pain Inventory (BPI), Western Ontario and McMaster University Osteoarthritis index (WOMAC), The Australian Canadian Osteoarthritis Hand Index (AUSCAN), Fatigue Symptom Inventory (FSI), Hot Flash Related Daily Interference Scale (HFRDIS), Pittsburg Sleep Quality Index (PSQI) and Center for Epidemiological Studies Depression (CES-D). Results: 55 eligible patients were invited to participate and 39 consented and completed the baseline assessments. 61% (median) Participants attended the classes, with no Tai Chi related adverse events reported. 22 of the 39 participants completed the 3-month follow up assessments with a 56% retention rate. Study participants reported improvement from baseline compared to 3 month as follows: For BPI (P = .000), AUSCAN pain subscale (P =.000), AUSCAN function subscale for 35 patients (P = .000), WOMAC (P = .000), CES-D (P = 0.001), FSI (P = 0.00) and PSQI (P = .000). However HFRDIS improved in 11 patients (P = 0.00) for the other 22 patients (P = 0.154). Conclusions: The COVID-19 global pandemic has resulted in the need to rethink how mind-body therapies can be delivered. This study demonstrated the feasibility, acceptability, and potential efficacy of a Telehealth based Tai Chi intervention for reducing AI-induced arthralgia. The intervention decreased patient reported pain, stiffness and improved sleep quality and depressive symptoms. With our promising findings, larger telehealth based trials of Tai Chi for AI-associated arthralgia are needed.