Heart ailments are the leading cause of death worldwide, which means that predictive AI for spotting them is one of the most impactful ways in which AI can improve health outcomes, in addition to flagging some well-known factors that harm cardiovascular health like poor diets, excessive stress, and insufficient exercise.

Dr Gaurav Chandra discusses AI's role in antimicrobial resistance from diagnosis to therapy, asserting that humanity limits its scientific potential by not embracing the concept of information-sharing for the greater good, and concluding that moving away from working in silos, data-sharing, and creating more extensive databases can assist in early diagnosis and development of novel therapeutics for AMR.

AI use is becoming ever more feasible in computational fluid dynamics, where it has already yielded promising results. Different computational means have their unique advantages and drawbacks, but it is not realistic to expect AI to fully replace these, as it is more likely to serve as a complement to them.

The USA spends trillions of dollars a year on healthcare paperwork. Automated solutions made possible by ML and AI not only mean much of this money can be saved, but also makes largescale adoption of AI more likely before highly regulated medical AI reaches critical mass, finds Satyen K. Bordoloi.

When it comes to AI in the fields of medicine and healthcare, the focus is often on the advancements and improvements that it has enabled, but just as crucial are the mistakes that occur due to flawed or limited AI. Rectifying such errors could help save the lives of millions, thus rendering it a crucially important task.