The Biggest Recent AI Advancements in Healthcare

By: Hay & Kilner
 
NEWCASTLE UPON TYNE, U.K. - Jan. 27, 2021 - PRLog -- The use of artificial intelligence in healthcare has increased exponentially in the past year, with more intelligent applications than ever before. Here, we cover the most innovative advancements in the use of AI in healthcare recently.

Processing cancer scans

The National Health Service (NHS) is using Microsoft's InnerEye technology to automate the process of scans for prostate cancer. Once the scan is taken, the AI gets to work. It outlines the prostate in the scan and marks up any tumours. By automating this manual, laborious process, NHS staff can act faster and speed up prostate cancer treatment.

This technology is also being used to analyse scans from breast cancer screenings, outlining potential tumours. Experimental technology is currently being developed by the University of Nottingham to predict a patient's response to chemotherapy. This combines breast cancer patient MRI scans, clinical data and advanced computational modelling to help clinicians to deliver personalised, right-first-time treatments.

Virtual patients

Virtual GPs powered by artificial intelligence and machine learning are no longer a new innovation. But virtual patients have been introduced in the past year to train NHS staff. Because patients are currently advised to only attend the surgery in urgent situations, in-person training has been limited. The virtual patients utilise mixed reality, allowing trainees to role-play with a virtual patient via video instead of actors in-person.

Using this technology allows learners to build the soft skills required to deal with patients, including providing comfort along with bad news. Users also develop knowledge around building treatment plans and explaining diagnoses. The AI gives the user feedback in real-time so they can continually learn and improve.

Faster stroke detection equalling a lower impact

Viz.ai is a stroke detection solution which uses deep machine learning to identify patterns in a patient's brain activity and accurately identify large vessel occlusions (LVO), which account for up to 46% of ischemic strokes. The AI will send a radiological image to the clinician's smartphone, allowing medical staff to quickly triage patients and prevent the irreversible loss of the patient's brain cells.

Medical professionals who specialise in stroke treatment and care will know that when it comes to treatment, every second counts. In fact, for every minute of additional time-to-treatment, 1.9 million patient brain cells are lost. One study shows that Viz.ai, on average, could prevent patients from being bedridden and requiring 24/7 care, and instead able to walk out of the hospital with no further care required.

https://www.hay-kilner.co.uk/workareas/clinical-medical-n...

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Industry:Medical
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