Work

Infection detection revolution: Harnessing AI-powered image analysis to combat infectious diseases

Year: 2024

Type: article

Abstract: Infectious diseases wield significant influence on global mortality rates, largely due to the challenge of gauging their severity owing to diverse symptomatology. Each nation grapples with its unique obstacles in combatting these diseases. This study delves into three distinct decision-making methodologies for medical diagnostics employing Neutrosophic Hypersoft Set (NHSS) and Plithogenic Hypersoft Set (PHSS), extensions of the Hypersoft set. It introduces state-of-the-art AI-driven techniques to enhance the precision of medical diagnostics through the analysis of medical imagery. By transforming these images into the aforementioned sets, the analysis becomes more refined, facilitating more accurate diagnoses. The study advocates various courses of action, including isolation, home or specialized center quarantine, or hospitalization for further treatment. The novelty in this study utilizes cutting-edge AI methods to enhance medical imaging, transforming them into accurate diagnostic tools, marking a significant change in how infectious diseases are addressed. By combining machine learning and pattern recognition, it offers the potential to overhaul healthcare worldwide, facilitating accurate diagnoses and customized treatment plans, ultimately reducing the global burden of infectious diseases on mortality rates.

Source: PLoS ONE

DOI: 10.1371/journal.pone.0307437

Authors: Muhammad Ahsan, Robertas Damaševičius

Institution: Vytautas Magnus University

Language: English

Topic: Fuzzy and Soft Set Theory

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $2,290