Dr. Rajae GHANIMI
Specialist in occupational medicine.
Doctor (PhD) in artificial intelligence
applied to medicine Doctor specializing in
occupational medicine and occupational diseases
Holder of a doctorate in artificial intelligence.
Writer and author of many books and articles.
Writer, author of several books and articles.
(MOROCCO)
From COVID-19 to monkey pox to recent bedbug concerns, it’s clear that concerns over public health crises have increased significantly in recent years. In a hyper connected world, where climate change and population growth are omnipresent, the appearance of new pathogens occurs with increased frequency, facilitating their spread. Fortunately, significant technological advances have emerged that have the potential to reduce the health impact of these global challenges.
Today, with the advent of artificial intelligence (AI), no sector is exempt from its transformative influence, and public health is no exception. The rapid integration of AI in public health heralds a new paradigm for health promotion, promising to revolutionize our approach to disease prevention, epidemiological surveillance and the delivery of medical care. This development heralds substantial improvements in terms of effectiveness, efficiency and equity in public health interventions.
The scope of AI applications in public health is vast and diverse. Its most notable impact is seen in disease surveillance and epidemiological predictions. Using big data and sophisticated algorithms, AI can analyze huge volumes of data from varied sources, such as online news, phone data, flight plans and weather forecasts. These predictions help anticipate where and when a disease might spread. While this science is not infallible, it has shown effectiveness for COVID-19 and the Zika outbreak in Brazil, predicted by Canada’s BlueDot app for Florida. This predictive capability allows health authorities to take proactive preventative measures, thereby reducing the impact of outbreaks and saving lives. AI-based early warning systems detect epidemiological patterns through mining news articles, online content and other information channels in various languages, complementing syndromic surveillance and other networks health.
Additionally, AI can boost health promotion by offering personalized recommendations. AI algorithms analyze an individual’s health data, lifestyle habits, and even genetic information to develop individualized advice on nutrition, physical activity, and other health-influencing behaviors. This personalized approach could lead to better health outcomes, as individuals tend to follow advice specifically tailored to their needs and preferences.
Furthermore, AI is proving to be an essential ally in the fight against health disparities. AI algorithms can identify patterns and trends within health data, highlighting existing disparities between different population groups, and between urban and rural areas. By exposing these inequalities, AI could guide decision-makers to direct public health interventions and actions in a targeted manner, focusing resources where they are most needed. AI also optimizes the efficiency of healthcare delivery. With it, time-consuming administrative tasks like patient medical and patient data, thus detecting diseases early. This early detection promotes rapid treatment, improving patient outcomes while reducing costs associated with medical care.
However, the integration of AI into public health is not without challenges. Data privacy and security issues raise concerns as AI algorithms require access to enormous amounts of sensitive data. There is also the risk that AI will worsen health disparities if it is not developed and implemented equitably. For example, algorithms trained on data that is not representative of the diversity of the population risk producing biased results, putting certain groups at a disadvantage.
Despite these challenges, the potential benefits of AI in public health are too great to ignore. It ushers in a new era for health promotion, promising to revolutionize disease surveillance, health promotion, medical care delivery and health equity. As we further explore the impacts of AI on public health, it is crucial to proactively address these challenges. This requires close collaboration between public health officials, AI researchers, healthcare professionals, ethicists and policymakers.