Medical Decision-Making with the Help of Quantum Computing and Machine Learning: An In-Depth Analysis

Abstract

The use of quantum computing (QC) and machine learning (ML) is on the rise in medical decision-making. These technologies can analyse large datasets, enhance diagnoses, and make personalised therapies possible. In many real-world applications, QC is still behind classical computing, even if it has the potential to speed up optimisation, drug discovery, and genetic research as hardware capabilities improve. The fields of medical imaging, predictive modelling, and decision assistance have all seen substantial success using ML. Their coming together, especially with quantum machine learning (QML), opens doors to better therapeutic results and more efficient processing of high-dimensional healthcare data in the future. Future directions for quantum-enhanced ML in medical decision-making are outlined in this paper, which also covers the fundamental ideas, important uses, and difficulties of these technologies in healthcare, as well as their potential synergy in solving clinical issues.