Now a subtype of artificial intelligence called deep learning may be just what the doctor ordered.
The research on deep learning was performed at the University of Toronto by Geoffrey Hinton, Yann LeCun and Yoshua Bengio, and was recognized in 2019 by the Turing Award - the equivalent of the Nobel Prize for computer science.
Deep-learning neural networks have been trained with large, labelled data sets for high-level performance, matching or exceeding humans for games, images, voice recognition and self-driving cars.
Accuracy of medical scans like X-rays to mammograms, CT and MRI images increase with deep-learning algorithms. Diagnoses of the eye disorders like diabetic retinopathy and glaucoma and skin disorders like melanoma have had their accuracy substantially improved by these neural networks.
It also helps improve colonoscopy accuracy and improved embryo selection for in-vitro fertilization in the hospital setting to ensure patient safety.
These tools are synergistic add-ons, not replacements for clinicians.
Italian academic neurosurgeon Antonio Di Ieva nicely summed it up, "Machines will not replace physicians, but physicians using AI will soon replace those not using it."
It liberates doctors and patients from keyboards. Just a minute of keyboard entry time for doctors represented the equivalent of 400,000 hours of consultation time a year, or 230 full-time physicians
Smartwatch algorithms can detect and classify abnormal heart rhythm, a drugstore kit to diagnose a urinary tract infection or a smartphone app to detect whether a child has an ear infection.
It enables doctors and patients to get back to where medicine was decades ago, when the relationship was characterized by a deep bond with trust and empathy.
Though it is ironic that we may depend on AI and machines to promote emotional intelligence, the time for humans to think and be more human. But over the next decade, I hope we'll see exactly that, whereby health systems and practices actually compete on the basis of how much time they give to their patients.