Statistics and Machine Learning in Public Health: When to Use What

If you’re trained in epidemiology or biostatistics, you likely think in terms of models, inference, and evidence. Now, with machine learning entering the scene, you’re probably hearing about algorithms that can “predict” disease, “detect” outbreaks, and “learn” from data. But while ML offers exciting possibilities, it’s important to understand how it differs from classical statistical…

Good and Evil of AI in Medicine: Where Is the Boundary?

Artificial intelligence (AI) is rapidly transforming the field of medicine, offering unprecedented opportunities to improve healthcare delivery, diagnosis, and population health management. However, with its promise comes a risk of harm, particularly when AI systems are poorly designed, implemented without appropriate safeguards, or driven by commercial interests at the expense of public good. This paper…

Integrating AI in Healthcare

Artificial intelligence (AI) is reshaping healthcare by offering remarkable capabilities in diagnostics, decision-making, and patient care. Recent research published in JAMA Network Open demonstrated that large language models (LLMs), such as ChatGPT, can outperform human physicians in diagnostic tasks under controlled scenarios (Hswen & Rubin, 2024). This potential has sparked enthusiasm, yet concerns about ethical…

Using AI in Medicine and Preparing a Framework for Medical Education

The integration of artificial intelligence (AI) in medicine is transforming healthcare, enabling advanced diagnostics, improved decision-making, and operational efficiencies. However, its application requires careful consideration to ensure that the essence of patient care—ethical responsibility and compassion—is maintained. Clear guidelines are essential to navigate this evolving landscape while simultaneously preparing medical professionals to harness AI effectively…