A Systematic Review on Incorporation of Artificial Intelligence in Precision Healthcare
Precision medicine is transforming healthcare in the future owing to artificial intelligence (AI), enabling treatment to be personalized in line with a person's genetic, environmental, and lifestyle characteristics. In this article, AI's potential to revolutionize clinical decision-making, hasten drug discovery, and boost diagnostic accuracy is explored. Advanced AI technologies such as deep learning and natural language processing unlock new insights in genomic data, medical imaging, and patient records to enable more personalized treatment and better outcomes for patients. Among the technologies that build transparency and trust, aside from overcoming challenges related to algorithmic interpretability and bias, are explainable models and multi-modal AI systems. Despite its promise, AI in precision medicine is also hindered by various challenges such as concerns over confidentiality of data, ethical questions, and a lack of standardized regulatory frameworks. The review highlights AI's use in genomics, diagnosis, and treatment alongside challenges in deployment and new developments such as federated learning and use of real-world evidence. Ultimately, the article underscores the importance of high ethical standards and cross-disciplinary collaboration in unleashing AI's potential to deliver personalized medicine to the entire globe. By overcoming challenges that already face it and developing new methods, AI can revolutionize precision medicine and pave the way for a new era of patient-centered healthcare.
Authors
- Karnika Dwivedi (ORCID: https://orcid.org/0000-0002-1131-9223)
- Jyoti Chaudhary
- Bharti Chugh
- Pankaj Bhatt (ORCID: https://orcid.org/0000-0003-1341-7422)
- Deepak Chandra Joshi (ORCID: https://orcid.org/0000-0002-5681-4017)
Institutions
- Institute of Management Technology (IN)
- Shiv Nadar University (IN)
- Bennett University (IN)
- University of Uyo (NG)
Publication Details
- Published
- 2025-05-29
- DOI
- https://doi.org/10.1109/netcrypt65877.2025.11102485
- Primary Topic
- Artificial Intelligence in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 0.00