Abstract
In recent years, the escalating volume of essential information for oncologists has created a challenge, making it arduous to stay abreast of the latest developments in the multifaceted field of cancer care. Although Artificial Intelligence (AI) is increasingly applied in healthcare, particularly for tasks like image recognition and big data analysis, we advocate for an AI-centric public health model tailored to comprehensive cancer care. This model aims to guide patients from their initial doctor’s visit to the conclusion of treatment, thereby minimizing direct doctor involvement. Results. The proposed AI system comprises distinct units: Regional AI (RAI) for patient management and coordination with healthcare specialists and facilities in specific areas, General AI (GAI) to oversee healthcare processes on a broader scale, and Scientific AI (SAI) for data analysis and hypothesis generation, essential for scientific research and clinical trials. To enhance cost efficiency, we suggest introducing an intermediate layer, Teacher AI (TAI), facilitating the development of AI systems like GAI or RAI based on human needs without necessitating extensive specialist intervention. Conclusions. Implementing this model can simplify oncologists’ daily tasks, reduce errors, improve treatment outcomes, and lower the cost of cancer care while maintaining its high quality. The Human–TAI–AI development model can streamline the system’s development and implementation, making it more cost-effective.