Digitization and Artificial Intelligence in Global Public Health

From the Editors ?? - Topic in Focus ?? - Popular on LinkedIn ?? - Featured ?? - Footnote ??

From the Editors ??

In this issue, we explore the role of digitization and artificial intelligence (AI) in the context of global public health. See our previous issues for more information about the digital health and artificial intelligence in the academic research and publishing worlds as well as in biomedicine and healthcare.

Do you use AI in the public health field? Share your thoughts and story in the comments.?

We hope you enjoy reading as much we enjoyed creating the content.

Your "Beyond Science" Editorial Team ??

Nesrin and Victoria

Topic in Focus ??

Artificial intelligence (AI) will be having an increasingly profound impact on global public health in the future, with applications ranging from health education, disease prediction and management of pandemic responses, to personalized medicine and drug discovery and development. Some key areas where AI may impact public health globally include:?

Global health equity: AI can help address disparities in healthcare by providing access to quality health information and diagnostic tools in underserved regions. However, it’s crucial to ensure that these technologies are designed and implemented in a way that is equitable and considers the diverse needs of different populations.?

Healthcare accessibility and telemedicine: AI-powered platforms can assist in providing virtual consultations, providing remote care and improving access to healthcare, especially in underserved or rural areas, while virtual health assistant AI chatbots can provide health information, answer questions, and offer support for managing chronic conditions.?

Health education and promotion in public health campaigns: AI can tailor public health campaigns to target specific issues or demographics by helping in the creation of interactive educational tools and resources to educate and promote healthy behaviors, prevent diseases, and improve health literacy.?

Disease surveillance and prediction of epidemic/pandemic outbreaks: AI with machine learning can analyze vast amounts of data from numerous sources including health records to detect early signs of disease outbreaks. AI algorithms can be used to predict the likelihood of outbreaks and track the spread of viruses by analyzing data on infectious diseases like COVID-19, Flu, Ebola, and more recently, Monkey Pox (mPox).?

Resource allocation and management: AI tools can help to allocate vaccines, medical supplies, and personnel more efficiently, especially during emergencies or pandemics by predicting supply chain shortages and assist with the logistics of distributing medical supplies.?

Health data management and electronic health records (EHRs): AI can streamline the management and analysis of EHRs, improving patient care by providing healthcare professionals with comprehensive, up-to-date information. AI tools can also help in epidemiological research by analyzing complex data from various sources to identify risk factors for diseases, evaluate the effectiveness of public health interventions, and support evidence-based policy decisions.?

Diagnostic and treatment tools: AI algorithms are also increasingly used to analyze medical images (e.g., X-rays, MRIs) with high accuracy, helping in the early diagnosis of diseases such as cancer. In the field of personalized medicine, AI can help scientists and health care practitioners tailor treatments to individual patients by analyzing their genetic information, lifestyle, and other factors to predict how they will respond to different treatments. The use of AI tools can also accelerate the drug discovery process by predicting which drug formulations might be effective against specific diseases, significantly shortening development times, reducing costs, and making new treatments available faster.?

The integration of digitization and AI in global public health presents tremendous opportunities, but it also requires careful consideration of ethical issues, data privacy, and the need for human oversight to ensure that these technologies are used responsibly and effectively. Ensuring that AI systems do not reinforce existing health disparities or biases is crucial and ongoing research and adjustments are needed to address these concerns and promote equitable health outcomes.?

Popular on LinkedIn ??

• Manuel Cossio shared an AI Readiness Assessment Toolkit developed by PAHO/WHO and IDB to evaluate and enhance the preparedness of countries for integrating AI into their public health systems.?
• Reza Rabiei shared a reference tool developed by PAHO about improving surveillance and supporting more effective monitoring actions that are critical in public health planning.?
• Hannah van Kolfschooten shared a paper on the EU AI Act and its implication for health professionals using AI for healthcare activities must comply with the rules stipulated for deployers including public health authorities.?
• Jess Brant wrote about how AI can improve public health in Smart cities.??
• Elizabeth Harris shared draft guidelines for the ethical use of AI in public health communication.?
• Adewunmi Akingbola wrote a paper on AI in healthcare and the importance of balancing AI with human elements.?
• Dr. Ivan Del Valle wrote about the AI perspective on public health threats such as Mpox.?
• Jonathan French shared the revised public policy principles for AI development and use in the healthcare sector.?
• Emma Barlow share a post about NHS staff in the UK supporting AI in patient care, but have concerns about accuracy, care quality, and human connection.?
• Steve Kubenga Banza shared his AI-based chatbot called AI Public Health Assistant that makes navigating public health guidelines easier.?
• Brian Spisak shared key takeaways from the new Brookings Institution findings about AI in healthcare.?
• Ivan Ostojic shared a post about AI transforming the global healthcare sector, making it more efficient and connected.?
• Dr. Rilwan Adan wrote that AI-powered diagnostics and telemedicine are improving access, accuracy, and patient outcomes and driving more effective disease prevention and population health management in public health.?
• Yudara Kularathne shared a newly developed Mpox screening tool? that enables healthcare workers to perform screenings without internet access using mobile devices.?
• Tony Moroney shared a post about the 6P's framework illustration of AI and GenAI’s potential to transform healthcare.?
• Ruth Owino wrote about how AI is a game changer in public service delivery, characterized by efficiency, transparency, and responsiveness.?
• Professor Karin Thursky wrote that AI use in healthcare should include user-centred approaches and implementation plans with clear use cases, for which data is accessible and available.?
• Juan Lopez Madrid wrote about the game-changing potential of generative AI in healthcare, pharma, and private insurance.?

Featured ??

Digitization and AI in global public health?

In this month’s People & Science Live, hosted by Will Mountford, the conversation centered on Dr. Alain Labrique, Director of the Digital Health & Innovation department at the World Health Organization (WHO) . Find out about Dr. Labrique’s personal journey from Bangladesh, what inspired him and led to his current role ethically expanding digitization and artificial intelligence in healthcare around the world.

Footnote ??

Find out more about the WHO guidelines on responsible use of AI in healthcare.

?Check out these Call for Papers:?

• Digital Biomarkers

• Saudi Journal of Health Systems Research:

AI in scholarly communications

In this Karger in Conversation on the “Ethical & Legal Minefield of AI in Scholarly Communication” hosts Francesca Brazzorotto and Christian Box as well as experts Siobhan Haimé, Christine Stohn, and Jonathan Band discuss the complexities of integrating Large Language Models (LLMs) in scholarly publishing and how it impacts researcher’s academic career is unpacked. Learn from the experts how to responsibly harness AI’s power.

AI in research and publishing?

In this InsightsXChange podcast, Mitja-Alexander Linss and Nikesh Gosalia discuss the crucial role of AI and its current and future impact on research and publishing.

Explore the Interaction of AI and Knowledge Management in Academics.