AI-Driven Personalized Healthcare Recommendations

Abstract: The application of AI is revolutionizing healthcare by enabling customized treatment and medication recommendations. AI analyses diverse datasets, such as EHRs, genetic information, and real-time patient monitoring through wearable devices, to provide actionable insights based on individual biological and lifestyle characteristics. This transition from generalized protocols to personalized care significantly improves treatment efficacy and patient outcomes. This paper explores the methodologies and technologies of AI in personalized healthcare, highlighting ML and DL algorithms that process structured and unstructured data. NLP extracts critical insights from clinical documents, excelling in precision diagnostics and optimizing treatment pathways. Key applications include oncology, where AI tailors cancer treatments based on tumor genomics, and cardiology, with predictive models for cardiac risks. AI also aids in managing chronic and rare diseases through early intervention and tailored therapies. Challenges include ethical issues like data privacy and fairness, alongside regulatory and technical barriers. Addressing these challenges will foster a patient-centric healthcare ecosystem.

Keywords: AI, Personalized Medicine, Machine Learning (ML), Deep Learning (DL), Natural Language Processing (NLP), Electronic Health Records (EHRs), Pharmacogenomics, Wearable Devices, Precision Healthcare, Data Privacy, Oncology, Cardiology, Chronic Disease Management, AI Ethics, Blockchain.