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3 articles for “Modeling for COVID-19”
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Advancements in Drug Design Technology and Its Impact on COVID-19 Treatment
Abstract: The deadly coronavirus disease 19 (COVID-19) pandemic has recently spread, raising concerns about global health. The search for novel therapeutic compounds is made more necessary by the persistent problem of the absence of licensed medications or vaccinations. By saving money and time, computer-aided drug design has sped up the process of finding and developing new drugs. The structured-based and ligand-based drug discovery subcategories of computer-aided drug design (CADD) are the …
Published in International Journal of Virus Studies · Vol. 1, Issue 1, 2024 · pp. 1–15 Read article
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State of the Art: A Pandemic Big HealthCare Analytics Solution: Image Data Classification Using Quantum MAML
Abstract: The modern age is facing many pandemic healthcare problems, e.g., covid 19, infections, inflammations, and many more, leading to critical, deadly situations. Survival rate can be increased with proper diagnosis of such data. We have proposed one of the implementations based on a medical image dataset for classification using deep reinforcement learning (RL) with quantum computing. Deep RL is the combination of DL (deep learning), generative adversarial network (GAN), and …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 2, 2024 · pp. 1–9 Read article
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ArcGIS Applications in COVID-19 Spatial Epidemiology: A Comprehensive Systematic Review
Abstract: Addressing complicated community health concerns frequently necessitates the establishment of health practices. Professionals who study community health using information technology require a thorough framework. Health care professionals and authorities have had the ability to comprehend health-related geographical data and make timely judgments in different situations. In the field of epidemic disease prevention, including a viral spread model into a GIS is a popular issue. As a result, a GIS as …
Published in Journal of Remote Sensing & GIS · Vol. 16, Issue 2, 2025 · pp. 17–25 Read article