Technological prospection: artificial intelligence for predicting risk factors in Primary Health Care
DOI:
https://doi.org/10.21527/2176-7114.2026.51.16617Keywords:
Risk factors, Primary Health Care, Artificial Intelligence, Information and Communication Technology ProjectsAbstract
Objective: To identify artificial intelligence technologies for predicting risk factors within the scope of Primary Health Care (PHC). Method: Technological prospection, with searches conducted in patent databases. Data collection took place in April 2024. Artificial intelligence (AI) technologies addressing risk prediction in PHC and technologies available in English, Portuguese, and Spanish were included. The analysis was conducted through a qualitative comparative approach using Microsoft Excel spreadsheets extracted directly from patent databases. Results: Thirty patents were identified, most of them launched in 2022. The country with the highest number of developments was Brazil (29.03%), followed by the United States (25.8%) and India (25.8%). Regarding developers, most patents were filed by the inventors themselves (40%), followed by healthcare companies (20%) and health technology companies (13.33%). The objectives of the identified technologies were prediction of risks of a specific disease (46.67%), prediction of disease diagnosis (23.33%), prediction in health management (13.33%), and provision of health recommendations (16.67%). Final consideration: No technologies were found for predicting and assessing risk factors originating from the territory and thus providing risk stratification of the demand of Basic Health Units. Therefore, a gap was identified that can be filled through the use of AI, transforming PHC into a more predictive and less reactive model, optimizing resources and directing preventive actions more effectively.
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