3.2. Integrating Artificial Intelligence with Traditional Medicine
The integration of artificial intelligence with traditional medicine represents a crucial stage in the advancement of modern healthcare. AI usage enriches traditional diagnostic and therapeutic methods with new capabilities, increasing the accuracy and speed of obtaining information about the patient’s health status. Machine learning algorithms and big data processing can reveal hidden patterns, significantly expanding physicians’ abilities in early disease detection and personalized treatment.
Within this integration, special importance is placed on the creation of systems that do not fully replace the physician but act as supportive tools that provide a more comprehensive understanding of the body’s condition. This includes the use of data analytics from laboratory tests, medical imaging, and other sources, combining them into a unified platform for more comprehensive analysis.
An important component is aligning AI approaches with existing medical standards and practice protocols, as well as ensuring transparency of algorithms and their verifiability by specialists. Such an approach helps reduce human error, increase the efficiency of medical personnel, and improve patient care quality.
At the same time, ethical and data protection issues must be considered, strictly maintaining information confidentiality and obtaining informed consent for AI use in medicine.
Overall, integration with traditional medicine opens new horizons for improving the effectiveness of diagnosis, prevention, and treatment, ultimately contributing to a deeper and more accurate understanding of human health through advanced technologies.