Open Access
·Peer-reviewed·ISSN (Online): 2169-0103·ISSN (Print): 0252-2667
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The Journal of Information and Optimization Sciences (JIOS) is a world leading journal publishing high quality, rigorously peer-reviewed original research in all mathematically-oriented theoretical and applied topics in information sciences, optimization sciences and related areas since 1980. Subjects include but are not limited to:
• Information Sciences
• Optimization Sciences
• Control Theory
• Operational Research
• Decision Sciences
• Information Theory
• Information Technology
• Computer Networks and Communications
• Mathematical Programming
• Modelling and Simulation
• Database Management
• Applications to Engineering Sciences
• Applications to Technology
Issues up to 2022 co-published with and available at:
A novel actuarial science approach for predicting infectious diseases using computed tomography
*J. SeethaCorresponding authorjsvpec@gmail.comMuma College of Business University of South Florida 8350 N. Tamiami Trail Sarasota ; Department of Computer Science and Business Systems Panimalar Engineering CollegeMuma College of Business University of South Florida 8350 N. Tamiami Trail Sarasota Florida, U.S.A.View full profile →
, Bhuvan Unhelkarbunhelkar@usf.eduMuma College of Business University of South Florida 8350 N. Tamiami Trail SarasotaFlorida, 33620, USA0000-0003-1118-3837View full profile →
, S. Siva Shankardrsivashankars@gmail.comDepartment of Computer Science and Engineering KG Reddy College of Engineering and TechnologyHyderabad, Telangana, 500100, India0000-0002-7616-6088View full profile →
, Tulika Chakrabartitulika.chakrabarti@spsu.ac.inDepartment of Chemistry Sir Padampat Singhania UniversityUdaipur, Rajasthan, 313601, lndiaView full profile →
, Prasun Chakrabartidrprasun.cse@gmail.comDepartment of Computer Science and Engineering Sir Padampat Singhania UniversityUdaipur, Rajasthan, 313601, lndia0000-0001-8062-4144View full profile →
, B. Sivaneasansivaneasan@singaporetech.edu.sgSpecialist Adult Educator Engineering Electrical Power Engineering Programme Singapore Institute of TechnologyDepartment of Computer Science and Engineering KG Reddy College of Engineering and Technology Moinabad, Telangana, 500075, IndiaView full profile →
, Martin MargalaMartin.margala@louisiana.eduSchool of Computing and Informatics University of Louisiana at LafayetteLafayette, LA, 70503 (337) 482-6768, 70503 (337) 482-6768View full profile →
* Corresponding author · click or hover a name for details
Amid the COVID-19 pandemic, early and accurate automatic detection is vital. This study presents the AVbADC Algorithm to separate lung areas impacted by COVID-19 in CT scans. Initial results show promising performance, though further improvements are needed. The refined AVbADC model emerges as a valuable tool for prompt COVID-19 case identification. Comparative analysis against existing methods provides insights into its efficacy.
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