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Artificial Intelligence is transforming public health in many ways, especially through innovative practices and solutions, including disease monitoring, modelling and forecasting. It helps in risk assessment, analyzing health behaviors, managing public communication, guiding research, health education and disease prevention efforts (1).
The application of AI in public health has the potential to improve health outcomes at both individual and population. It plays a critical role in pharmacovigilance, disaster response and resource allocation during health emergencies (1). For instance, the research indicates a deep neural network, which was trained on over 37,000 head CT scans of intracranial hemorrhage, assessed 9,500 unseen cases, shortening the time taken to diagnose intracranial hemorrhage in new outpatient clinics by 96% with an accuracy of 84% (2).
AI-driven systems process real-time public health surveillance or epidemiological surveillance by electronic health records, environmental data, and social media trends to spot outbreaks early and predict anomalies. Natural language processing (NLP) helps practitioners at public health authorities detect trends in mental health issues, vaccine hesitancy, and misinformation, which was especially important during the COVID-19 infodemic (3) (4).
In public health education, AI offers a new opportunity, guidance and technical support for training professionals to improve the quality of education. AI-integrated curricula in medical schools to equip public health professionals to respond to emergencies (2).
But challenges persist. AI can perform many tasks of healthcare personnel better than humans, potentially displacing a portion of the health workforce. A Deloitte-Oxford Martin Institute suggests that 35% of UK jobs could be automated in the next 10 to 20 years. Additionally, issues like data bias, lack of diversity in training datasets, and privacy concerns need immediate attention (5). The World Health Organization (WHO) recommends the need for transparent algorithms and ethical frameworks for the use of AI for health to ensure responsible implementation (6).
References
- Jagdish Khubchandani, Banerjee, S., Yockey, R. A., & Batra, K. (2024). Artificial Intelligence for Medicine, Surgery, and Public Health. Journal of Medicine Surgery and Public Health, 100141–100141. //doi.org/10.1016/j.glmedi.2024.100141
- Wang, X., He, X., Wei, J., Liu, J., Li, Y., & Liu, X. (2023). Application of artificial intelligence to the public health education. Frontiers in Public Health, 10. //doi.org/10.3389/fpubh.2022.1087174
- Pilipiec, P., Isak Samsten, & Bota, A. (2023). Surveillance of communicable diseases using social media: A systematic review. PLoS ONE, 18(2), e0282101–e0282101. //doi.org/10.1371/journal.pone.0282101
- Cinelli, M., Quattrociocchi, W., Galeazzi, A., Valensise, C. M., Brugnoli, E., Schmidt, A. L., Zola, P., Zollo, F., & Scala, A. (2020). The COVID-19 social media infodemic. Scientific Reports, 10(1). //doi.org/10.1038/s41598-020-73510-5
- Davenport, T., & Ravi Kalakota. (2019). The potential for artificial intelligence in healthcare. Future Healthcare Journal, 6(2), 94–98. //doi.org/10.7861/futurehosp.6-2-94
- World Health Organization. (2021). ETHICS AND GOVERNANCE OF ARTIFICIAL INTELLIGENCE FOR HEALTH ETHICS AND GOVERNANCE OF ARTIFICIAL INTELLIGENCE FOR HEALTH. //iris.who.int/bitstream/handle/10665/341996/9789240029200-eng.pdf?sequence=1
Posted : July 5, 2025 4:10 pm
Interesting reads, indeed, artificial intelligence is revolutionizing the public health landscape through virtual screening, early detection, real-time surveillance, and tailored interventions. The association of the two enhances strategic decision-making, education, and emergency response, keeping in mind ethical oversight and data integrity.
Jagdish Khubchandani, Banerjee, S., Yockey, R. A., & Batra, K. (2024). Artificial Intelligence for Medicine, Surgery, and Public Health. Journal of Medicine Surgery and Public Health, 100141–100141. //doi.org/10.1016/j.glmedi.2024.100141
Posted : July 7, 2025 10:06 am
Artificial Intelligence (AI) is changing the way we take care of people’s health at a large scale. It is being used to help doctors, researchers, and health workers make better and faster decisions to prevent and control diseases.
One big use of AI in public health is to predict disease outbreaks. For example, AI systems can scan news articles, social media, and travel data to give early warnings about new diseases like COVID-19—even before the government officially announces them. This helps in taking quick action.
AI is also helping in understanding who is at risk of diseases like diabetes or heart problems. By studying health data, AI can identify high-risk people and help in planning early treatments or awareness campaigns.
Another interesting use is analyzing public health data, like what people are posting on social media or what doctors are writing in reports. AI can find patterns in this large amount of data that a human might miss.
In some countries, AI chatbots are being used to give people basic health advice, reminders for vaccines, and even mental health support.
But there are also some concerns. We need to be careful about data privacy and make sure the technology works fairly for everyone, not just for people in rich or urban areas.
References:
- World Health Organization (WHO). (2021). Ethics and Governance of Artificial Intelligence for Health.
//www.who.int/publications/i/item/9789240029200 - Topol, E. (2019). Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again. Basic Books.
- Beam, A. L., & Kohane, I. S. (2018). Big data and machine learning in health care. JAMA, 319(13), 1317–1318.
//doi.org/10.1001/jama.2017.18391 - BlueDot. (2020). Using AI to track and predict global disease outbreaks.
//bluedot.global - IBM. (n.d.). AI in Public Health.
//www.ibm.com/blogs
Posted : July 7, 2025 2:06 pm
Diagnosis is a crucial component of public health because rapid and precise disease diagnosis is need for efficient disease treatment and management. Traditional diagnostic techniques, such as laboratory testing, can be expensive and time-consuming, and their results may not always be reliable. AI has the ability to increase the speed and precision of diagnostic procedures, improving the outcomes for public health. Machine learning algorithms can examine and integrate massive volumes of data, including laboratory test results and medical imaging, to find patterns and forecast disease. Deep learning algorithms, which can evaluate complex data and produce predictions with high accuracy, are especially helpful for deciphering patterns in medical pictures like x-rays and CT scans that could point to the presence of disease. In addition to this, AI can evaluate vast amounts of data and more rapidly and identify trends and give advance warning of potential disease outbreaks and epidemics and thereby can contribute in public health surveillance. Leveraging these insights will allow policies to be developed that are better-targeted, impactful and timely. AI has a great deal to offer policymakers but, like all new technologies, trust and education in how to use it effectively and responsibly are critical to its future uptake and usefulness.
References
1. Olawade DB, Wada OJ, David-Olawade AC, Kunonga E, Abaire O, Ling J. Using artificial intelligence to improve public health: a narrative review. Front Public Health. 2023 Oct 26;11:1196397. doi: 10.3389/fpubh.2023.1196397. PMID: 37954052; PMCID: PMC10637620.
2. Fitzpatrick F, Doherty A, Lacey G. Using artificial intelligence in infection prevention. Curr Treat Options Infect Dis. (2020) 12:135–44. doi: 10.1007/s40506-020-00216-7.
3. Mourya AK, Idrees SM. Cloud computing-based approach for accessing electronic health record for healthcare sector In: Chaudhary A, Choudhary C, Gupta M, Lal C, Badal T. editors. Microservices in big data analytics: Second international, ICETCE 2019, Rajasthan, India, February 1st-2nd 2019, revised selected papers. Singapore: Springer; (2020). 179–88. doi: 10.1007/978-981-15-0128-9_16
Posted : July 8, 2025 4:33 pm
The use of AI in public health has garnered more attention in recent years, particularly in the areas of predictive modeling and public health surveillance. By using AI algorithms, we are able to predict the spread of infectious diseases such as influenza or COVID-19, which has allowed public health officials to take preventive measures. AI has additionally been used to monitor the spread of diseases by analyzing huge volumes of data from various sources to predict possible outbreaks. Because of the advanced computational resources available, AI in public health has also extended to new areas such as tailored
treatment plans and medication development.
treatment plans and medication development.
Through the provision of easily accessible, reasonably priced, and engaging solutions, AI-based applications can enhance health education and promotion initiatives. AI can help people manage their chronic conditions, such as asthma, diabetes, and hypertension, on their own. AI technologies can facilitate people’s access to automated or remote medical screenings, diagnosis, and treatment. AI can also assist in tracking and monitoring health data, symptoms, and therapies in a semiautomated manner. The provision of emotional support for individuals with mental health concerns has demonstrated the utility of AI. Personalization that is tailored to a user’s medical history, lifestyle, and preferences, as well as reminders to get vaccines and health exams, could all be helpful. Artificial intelligence (AI) models offer context-sensitive health education materials, such as tailored advice on exercise, nutrition, and healthy lifestyle practices.12 AI is also capable of reminding people to repeatedly finish the recommended health exams. These technologies facilitate the availability of health information to consumers, empowering them to make more informed decisions regarding their health.
References:
Shrestha, N. (2024). USE OF ARTIFICIAL INTELLIGENCE IN PUBLIC HEALTH. Journal of Chitwan Medical College, 14(1), 1–4. //doi.org/10.54530/jcmc.1482
This post was modified 12 months ago 2 times by Shivani Sharma
Posted : July 10, 2025 2:03 pm