Predicting the possibility of COVID-19 infection using fuzzy logic system

Diagnosing COVID-19 in a fast and efficient manner is an ongoing problem. Currently, the methods of detection involve physical tests. Physical tests have the disadvantage that they require either test kits or medical equipment. This paper outlines the design of a type-2 fuzzy logic system that can help provide a preliminary diagnosis by computing the possibility that a patient is suffering from COVID-19 based on their external symptoms. It uses input information that can be gleaned without need for medical procedures. Both statistical data and the knowledge base were garnered from publicly available databases and datasets. The fuzzy logic system implemented here is functional, but it is fairly inaccurate and illustrates that more information, both symptomatic and epidemiological is needed, to predict COVID-19 infections through an expert system. Copyright © 2021 Inderscience Enterprises Ltd.

Could Interventional Radiological Therapies Offer a Safer Alternative as We Emerge from COVID-19 Pandemic?

The ongoing SARS-CoV-2 (COVID-19) pandemic poses a major risk to health care delivery all around the world and also poses significant risks to the public and health care workers (HCWs). Surgical procedures, particularly elective procedures, have been cancelled or deferred due to increased risks associated with surgery and anesthesia both to the patient and the HCWs as well as to allocate resources to treat infected patients. This is particularly true for patients with comorbidities and cancer. As countries emerge from this pandemic, a phased return to conventional surgical procedures is being proposed, with emphasis on procedures performed in ambulatory settings and avoiding endotracheal intubation, where possible. Interventional radiological (IR) procedures offer a unique advantage in this setting, as these procedures are often performed with local or regional anesthesia with shorter hospital stay. In this brief communication, we outline the current opinion on surgical risks and guidelines and suggest areas where interventional therapies may offer an advantage to the multidisciplinary team and patient. Copyright © 2020 American Medical Association. All rights reserved.