How AI Can Transform Healthcare with Personalized Medicine

In the healthcare sector, know about the transformation of personalized medicine by AI

It can frequently appear that adequate and affordable healthcare is impossible, from the skyrocketing healthcare costs in the United States to the ongoing NHS crisis. As we discover new treatments for previously fatal diseases, this will only get worse as chronic conditions become more common. New approaches can be challenging to implement into healthcare systems and personalized medicine that are either resistant to change or exhausted by too much of it, and these new treatments typically come at a high price. In the meantime, the rising demand for social care is increasing funding pressure and complicating resource allocation even more.

Services already forced to do more with less are frequently presented with artificial intelligence as the solution. However, it is a fantasy that intelligent computers could replace human physicians. In the real world, AI typically fails to perform well. Complexity presents a challenge. The messy, innately human field of medicine has been relatively unaffected by AI technologies up until now. However, imagine a scenario where artificial intelligence instruments were planned explicitly for certifiable medication – with all its hierarchical, logical, and monetary intricacy.

The lab I lead at Cambridge University focuses on this "reality-centric" approach to AI. Working intimately with clinicians and clinics, we foster artificial intelligence instruments for scientists, specialists, medical attendants, and patients. MRI scan analysis or the discovery of novel drug compounds are frequently regarded as the primary AI opportunities in healthcare. However, there are numerous alternatives. Something our lab studies is customized or accurate medication. As opposed to one-size-fits-all, we hope to see how therapies can be redone to mirror a singular's unique clinical and way-of-life profile.

Artificial intelligence-controlled customized medication could be a more compelling therapy for normal circumstances like coronary illness and malignant growth or interesting infections like cystic fibrosis. Instead of using age and sex as blanket criteria, it might make it possible for doctors to tailor the timing and dosage of medications to each patient or to screen patients based on their health profiles. This individualized approach has the potential to save lives and make better use of resources by enabling earlier diagnosis, better prevention, and better treatment.