The world of digital health is undergoing a profound transformation. With the rapid development of artificial intelligence (AI), healthcare providers and patients alike are experiencing unprecedented advances in medical diagnosis, treatment, and overall quality of care. In this article, we'll explore the evolution of AI in healthcare, from its early beginnings to the cutting-edge GPT-4 technology. The seeds of AI in healthcare were planted long before GPT-4, with medical imaging being one of the first fields to experience its transformative impact[1]. Algorithms were trained on thousands of expert-coded images to develop their own expertise.

The global population swells by billions every decade, and the amount of people needing medical treatment climbs wildly in turn. Human processing ability alone is no longer sufficient to sift through and service a worldwide patient list numbering in the hundreds of millions; we are outnumbering ourselves. Doctors and medical staff, tasked with mastering an ever-more advanced arsenal of treatment techniques, must now look to technological innovation to manage the flow of patients, and ensure adequate care for all. The field's tech leaders recognize a dire need for efficiency. Facing the chore of sorting infinite amounts of medical data, many innovators believe that perhaps the most effective approach is to teach that data to sort itself.