A Survey on Machine Learning and Internet of Medical Things-Based Approaches for Handling COVID-19: Meta-Analysis.

Early diagnosis, prioritization, screening, clustering, and tracking of patients with COVID-19, and production of drugs and vaccines are some of the applications that have made it necessary to use a new style of technology to involve, manage, and deal with this epidemic. Strategies backed by artificial intelligence (A.I.) and the Internet of Things (IoT) have been undeniably effective to understand how the virus works and prevent it from spreading. Accordingly, the main aim of this survey is to critically review the ML, IoT, and the integration of IoT and ML-based techniques in the applications related to COVID-19, from the diagnosis of the disease to the prediction of its outbreak. According to the main findings, IoT provided a prompt and efficient approach to tracking the disease spread. On the other hand, most of the studies developed by ML-based techniques aimed at the detection and handling of challenges associated with the COVID-19 pandemic. Among different approaches, Convolutional Neural Network (CNN), Support Vector Machine, Genetic CNN, and pre-trained CNN, followed by ResNet have demonstrated the best performances compared to other methods.

Impact of the COVID-19 pandemic on the stage and the type of surgical treatment of laryngeal cancer.

PURPOSE: Changes in the entire health care system during COVID-19 epidemic have affected the management of patients with head and neck cancer and posed several clinical challenges for ENT surgeons. Therefore, the present study aimed to investigate the effect of COVID-19 on the stage and the type of surgical treatments used in laryngeal cancer (including total laryngectomy, supracricoid partial laryngectomy (SCPL) and transoral laser microsurgery (TLM)) and also to compare the results of April 2020 to April 2021 with the previous year. MATERIALS AND METHODS: This cross-sectional study was performed on all patients with a diagnosis of laryngeal cancer who underwent surgery in the tertiary care center from April 2020 to April 2021 and the year before the pandemic in the same time. Demographic, cancer stage, and treatment data of all patients were recorded and analysis in two groups. RESULTS: Patients referred at the time of the virus outbreak; 111 were male and 5 were female, and in the group of patients referred before COVID-19, 90 were male and 12 were female. The type of surgical treatment of laryngeal cancer, mean time elapsed from sampling to surgery, stage of disease and mean tumor volume was statistically significant differences in patients before and during the outbreak. CONCLUSION: Patients who referred for diagnosis and treatment at the time of COVID-19 outbreak had more advanced stages of the disease and also the tumor volume was higher in them than patients who had referred before the outbreak. It is necessary to provide new solutions, education and treatment management for patients with laryngeal cancer in such pandemics.