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Artificial Intelligence in Public Health
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- 2. Prof (Dr) C M Singh 2
- 3. Prof (Dr) C M Singh 3
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- 5. Prof (Dr) C M Singh 5
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- 14. Prof (Dr) C M Singh 14
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Editor's Notes
- As we all know, our Government has recently launched Ayushman Bharat Digital Mission and lays emphasis on creation of Ayushman Bharat Health Number β this is great step towards digitalization of health records. And this digitization of health data holds profound potential to change the way we collect information and interact with healthcare system. In the recent times, an increasing volume of health related data is generated from many sources. This necessitates the increasing integration with computers capable of analyzing complex data with the assistance of AI, so that it can be leveraged for the benefit of public health. https://healthid.ndhm.gov.in/
- Before discussing the role of AI in public health, let us see the meaning of AI
- precision public health : Similar to how precision medicine uses genomic and other personalized patient data to provide the right treatment to the right patient at the right time, precision public health is an emerging discipline that uses extensive population-specific data to provide the right intervention to the right population at the right time.
- There are several subfields/components of AI that can benefit public health. The first subfield is Machine Learning
- The next subfield of AI is Natural Language Processing
- The use of Artificial Intelligence (AI) in public health must be guided by superior technical and ethical considerations aimed to mitigate ethical risk in public health and related policy interventions, reflected in the following eight guiding principles: 1)People-centered. Actions and solutions must be people centered and not be used solely by itself. As one of many technologies to aid public health AI should respect the rights of the individual. 2)Ethically grounded. Discussions, developments, and implementation must be grounded in the globally-agreed ethical principles of human dignity, beneficence, nonmaleficence and justice. 3)Transparent. Transparent approaches must always be used and communicated when developing AI algorithms. 4) Data protected. Privacy, confidentiality, and security of data use must be foundational to every AI development. 5) Demonstrates scientific integrity. AI interventions should follow scientific best practice including being reliable, reproducible, fair, honest, and accountable. 6) Open and sharable. Everything must be as open and sharable as possible. Tools and underlying concept of Openness must be a feature and a critical success factor of any AI development. 7)Non-discriminatory. Fairness, equality and inclusiveness in impact and design should always form the foundation of any AI initiative for Public Health. 8) Human-controlled technology. Formal processes for human control and review of automated decisions are mandatory.
- In mid-2020, the United Nations presented eight areas of collaboration based on recommendations from a high-level panel to make technical cooperation operational in the age of digital interdependence. In this regard PAHO has embraced and adapted those areas in eight principles to reflect the imperatives of the Digital Transformation of the Health Sector: 1)Universal connectivity; 2) Digital goods; 3) Inclusive digital health; 4) Interoperability; 5) Human rights; 6) Artificial intelligence; 7) Information security, and, 8) Public health architecture Principle 6: Artificial intelligence. Participation in global cooperation on artificial intelligence and any emerging technology should be part of Public Health policies. The principle of global cooperative support in artificial intelligence and any emerging technology means including the individual and social dimensions in a globalized, interconnected reality that is now part of the human condition. Global cooperation in artificial intelligence involves understanding the individual and social dimension in a globalized and interconnected reality that belongs to the human condition. Such cooperation, as well as working in multisectoral and interdisciplinary networks, is vital in designing and adopting artificial intelligence solutions that promote approaches to equity, gender and cultural diversity with secure, reliable and open algorithms.
- Six key priorities for successful use of artificial intelligence by public health organizations and their relationship to the broader public health system https://bmcpublichealth.biomedcentral.com/articles/10.1186/s12889-022-14422-z
- https://blogs.cdc.gov/genomics/2022/03/01/artificial-intelligence-2/
- https://blogs.cdc.gov/genomics/2022/03/01/artificial-intelligence-2/