Abstract
An overview of the promise, restrictions, and difficulties of artificial intelligence (AI) in revolutionizing primary care is given in this chapter. The application of AI, machine learning, and deep learning in healthcare has made significant strides in several primary care domains, including screening, preoperative care, and disease diagnosis. Numerous diseases, including cancer, cardiovascular disease, sexually transmitted diseases, osteoporosis, diabetes mellitus, hypertension, ophthalmic diseases, and obstructive sleep apnea, have been successfully predicted, diagnosed, and risk assessed using AI models. For the widespread adoption of AI in primary care, issues including data quality, interpretability, and regulatory constraints must be resolved. Nevertheless, by enhancing disease diagnosis, risk assessment, and personalized care, AI has the potential to transform primary care.
| Original language | English |
|---|---|
| Title of host publication | Artificial Intelligence in Clinical Practice |
| Subtitle of host publication | How AI Technologies Impact Medical Research and Clinics |
| Publisher | Elsevier |
| Pages | 1-13 |
| Number of pages | 13 |
| ISBN (Electronic) | 9780443156885 |
| ISBN (Print) | 9780443156892 |
| DOIs | |
| State | Published - 1 Jan 2023 |
Keywords
- Artificial intelligence
- machine learning
- preoperative care
- primary care
- risk assessment
- screening
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