Artificial intelligence-enabled platforms are raising eyebrows in hospitals throughout the country, teasing diagnostic and treatment innovations that are just down the pike.
One cautionary note from Mark Davis, MD, COO of Baptist Health South Florida's Miami Cancer Institute, is that hospitals must weigh the pros and cons of each new technology before diving in with financial investments.
"Today, in hospitals, we must take the time to think about how we're going to deploy AI. We are at an inflection point and we've seen this type of thing before over human history," Dr. Davis told Becker's. "But we must take the time up front to think about how this new technology is going to impact us and how we can best utilize it clinically and operationally."
Or, hospitals can make in-house investments in AI innovations to get ahead of the curve, provide optimal care for patients and possibly create a new revenue- stream.
Here are three hospital-developed AI platforms potentially poised to change the way medicine is practiced.
Connected to pancreatic cancer care — faster
It took less than a month before New Hyde Park, N.Y.-based Northwell Health started seeing the benefits of an AI-enabled tool that helps get patients with pancreatic cancer "connected to care, days, if not weeks, earlier in their care directory."
INav, developed by a team led by Daniel King, MD, PhD, assistant professor at the Institute of Cancer Research at Northwell's Feinstein Institutes for Medical Research in Manhasset, N.Y., may change the way the hospital diagnoses and treats cancer.
The AI software can analyze record amounts of abdominal scans per week to look for signs of pancreatic cancer.
Predicting high-risk surgical complications
A machine-learning platform developed at Pittsburgh-based UPMC is able to predict whether a patient is at high risk of complications following surgery.
Clinicians and researchers at UPMC have been able to use the AI-enabled program to analyze the records of more than 1.25 million patients to find those who had cardiac or cerebral events such as a heart attack or stroke after surgery at the health system.
The program was designed with clinicians in mind. It is able to completely automate analyses and does not add clinician burden while providing them with a reliable, useful tool.
Birth defects, genes and drugs
The Icahn School of Medicine at Mount Sinai Health System in New York City created an AI-powered model it calls "knowledge gap" to determine which medicines may cause birth defects.
Using data from the NIH Common Fund and congenital disability organizations, researchers are able to study, and perhaps predict, an unborn child's chance of having a birth defect. To date, studies have recognized "500 birth-defect/gene/drug cliques" that could explain certain drug-induced disabilities.