AI-Driven Innovations for Genetic Risk Prediction in Healthcare
Keywords:
Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Genetic Risk Prediction, Precision Medicine, Genomics, Electronic Health Records (EHR), Personalized Healthcare.Abstract
This research focuses on the contribution of the new deep AI, ML and NLP technology to raise genetic risk estimation in healthcare. Through integrating genomics with information obtained from other unstructured clinical sources, the research proposes a mixed, relatively accurate genetic disorder risk prediction model. The methodology involves the use of sophisticated techniques owing to the utilisation of advanced algorithms such as deep learning and natural language processing that would analyse massive datasets to provide a wealth of valuable data that, when analysed, would reduce chances of early diagnosis, development of appropriate treatment plans as well as anticipatory healthcare processes. This approach yields even better results than previous models because of the ability to combine data and features from different sources – a new strengthening of the precision medicine paradigm. This work creates the foundation for using AI in the healthcare system to improve patient experiences, decrease diagnostic mistakes and improve treatment plans.
DOI: https://doi.org/10.24321/3117.4809.202611
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