THE IMPACT OF ARTIFICIAL INTELLIGENCE ON HEALTHCARE WITH SPECIAL REFERENCE TO COVID-19 PANDEMIC: A SEARCH

Abstract

Through the emergency of COVID-19, AI in healthcare has been thought to play a main role in data management and statistics, for instance, in the prediction of epidemic trends and helping in drug discovery. This article discusses the role of artificial intelligence technologies in both specific and general areas with the main focus on how AI impacted the future outlook of public health interventions. AI has arisen as a super big tool in understanding epidemic trends and forecasts by interpreting the huge amount of data and modern machine learning algorithms. With the help of multitudinous data sources, including epidemiological data and social media trends, AI algorithms anticipate disease distribution, reproduction rates, and hotspot recognition with unequalled precision. Furthermore, AI modelling is involved in predicting healthcare resource demands and the investigation of contamination control efforts in order to ascertain the efficiency of these plans thereby informing the officials on the right actions to take concerning resource planning and management. Not only that, but AI also has really changed pharmacology by speeding up the research of future compounds for treating the virus. AI helps drastically cut down the process of drug screening by employing techniques such as virtual screening, molecular modelling, and drug repurposing, which, in turn, reduces the cost and time needed to discover and validate the drug candidates. Machine learning algorithms study molecular structures and suggest possible drug-target interactions which as a result promote the repurposing of FDA-approved drugs. These AI-based solutions have resulted in the discovery of potential drugs which then directed the pharmaceutical industry's response that has completely changed the way of dealing with infectious diseases. In sum, the findings highlight the incredible potential of AI in mitigating world health issues and engaging future public health approaches. Collaboration between science, industry, and public health institutions allows for this potential for AI development and to improve situations when there are new health threats.