In the contemporary medical landscape, genetics is no longer an afterthought: it is becoming central to personalized therapies. Experts say that understanding even minor genetic variations is transforming how we diagnose chronic, autoimmune, and metabolic diseases.

But identifying mutations isn't enough. The real breakthrough is the use of AI and intelligent algorithms that integrate genetics, medical history, and medical images to predict risks, optimize treatments, and adjust dosages. A group of researchers at MIT has just presented a system that accelerates the analysis of medical images, reducing hours of human work.

In oncology, for example, the combination of AI and genetics allows for the selection of targeted therapies with greater efficacy and fewer side effects. In cardiology, it can predict events such as heart attacks in seemingly healthy patients.

However, it's not all good news: we must carefully manage biases in algorithms, the privacy of genetic data, and ensure that these advances reach less fortunate populations.

For women, this change is crucial: many women's diseases have been underestimated because genetic studies were not inclusive. A fairer, more personalized approach promises to close those gaps.