Association of Rare Disease Diagnosis and Its Treatment Using Artificial Intelligence – A Review

Abstract

Rare disease (RD) diagnosis and treatment have been dramatically revolutionized by machine learning (ML)and artificial intelligence (AI), which assess complex data patterns and boost decision-making. Deep learning is also called machine learning that employs neural networks and image analysis to analyze high-dimensional data, resulting in faster and more accurate diagnostics. Personalized medicine, disease monitoring, and diagnostic accuracy are all advanced by AI technology, such as genomics tools, supervised and unsupervised learning models, and prediction algorithms. RD research has been limited by a lack of data, however, methodologies like data augmentation and transfer learning assist in overcoming this. AI helps doctors find mutations, forecast how an illness will grow, and create specialized therapies. Finding biomarkers, evaluating treatment outcomes, and streamlining clinical trials, also speed up drug discovery. However, for AI integration to be successful, high-quality data and flexible algorithms are essential. It is anticipated that future developments will enhance precision medicine, optimize treatment plans, and improve early diagnosis, all of which will improve patient outcomes and RD management.

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