Artificial Intelligence in Medicine

Today in Medmultilingua

For decades, fungal infections were considered a minor problem: something that mainly affected people with severely weakened immune systems, such as chemotherapy patients or those with HIV. By 2026, that picture no longer reflects reality. Certain fungi—like those that cause blood or lung infections—can kill even relatively healthy people, and they are becoming increasingly difficult to treat because they have developed resistance to available drugs.

The problem isn’t just biological. Creating a new drug can cost more than a billion dollars and take fifteen years. And fungi are more like us than they seem—they share much cellular machinery with humans—making it very difficult to attack them without harming the patient at the same time. It’s a dead end with a pressing need and few exits. That’s where artificial intelligence comes in. [Read more]

From its earliest conceptual roots in the mid‑20th century, artificial intelligence emerged from the ambition to build machines capable of reasoning, learning, and adapting. Early pioneers explored symbolic logic and simple computational models, laying the groundwork for systems that could mimic fragments of human cognition. As research expanded, AI evolved from rule‑based programs into powerful learning architectures capable of processing vast datasets and uncovering complex patterns. This steady progression transformed AI from a theoretical curiosity into a driving force of scientific and technological innovation, reshaping fields such as medicine, biology, and global health with unprecedented speed and impact

Dr. Marco Benavides

Medicine & Surgery