Medical sphere has witnessed a huge amount of breakthroughs over the last decade or so. These breakthroughs have more or less changed the dynamics of the human life. The way we see our body’s health currently is influenced by the advanced metrics we have at our disposal. Now, with the help of all our progression on the technological front, we are about to take a big step towards enhancing healthcare. This step will be inspired by Artificial Intelligence. Using the AI features, the medical specials are hoping to gain a better understanding of the patient’s health. Once they have a deeper insight into the patient’s body, the specialists can put together the best possible treatment, thus reducing the need for a readmission into the hospital.
This idea of integrating AI into patient assessment was first brought in by Dr. Amod Amritphale, M.D., the director of cardiovascular research and an interventional cardiologist at USA health. Amod enlisted the help AI algorithms to gather more information about patients who suffered a stroke. He studied the data comprised of their medical records and found out that a sizeable chunk of these patients had to be readmitted within 30 days of their discharge. Even though they had gone through the proper surgical procedure to open up the narrowed carotid artery, there was some issue or the other that would force these patients to come back. Amod decided to carry out a research on readmissions following CAS procedure.
“I wanted to understand more about the outcomes of patients who underwent CAS and other cardiovascular procedures and harness the power of artificial intelligence to develop a strong prediction model.” Amod said.
What Amod did was to compare the patients who came back after their CAS treatment with the ones who didn’t. This comparison provided him with the common pattern in the readmitted patients, thus putting him in a position where he had the chance to prevent these relapses by working with patients and figuring what course of action is best for them.
This AI-driven model has so far exhibited an impressive 79% success rate in accurately predicting at-risk patients.
