Quantum Computing in Biomedical Intelligence
Abstract
The medical field is essential in developing models for predictions, and there is an extensive amount of information on numerous diseases globally. Machine learning (ML) is critical for discovering and utilizing these data in healthcare. The development of secure healthcare information systems is an emerging issue, with quantum computing (QC) serving as an essential resource for handling health-related information. This information can be utilized to determine the fastest drug-forming procedures and safe mechanisms of drugs for diseases, thus improving healthcare effectiveness. It examines the usage of QC along with ML to improve prediction models for disease diagnosis and drug discovery. Quantum computing can speed up the development of drugs by optimizing simulations of molecules and lowering study time and expenses. It demonstrates QC's potential to transform biomedical studies and healthcare, providing considerable increases in diagnostic accuracy, medication modification, and overall outcomes for patients. By demonstrating its capacity to manage enormous, complicated datasets, provide quicker and more accurate evaluation, and transform personalized medicine and early detection of diseases, to demonstrate the possibilities of QC in healthcare investigation.
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