manufacturingtechnologyinsights

Deploying AI and Deep Learning Technologies in Healthcare

By Manufacturing Technology Insights | Friday, November 30, 2018

AI has become a common buzzword in any industry and with new developments and advancements every day. AI (Artificial Intelligence) and its applications are increasingly finding its footing in the healthcare industry. Many of the digital health organizations have faced a great product failure, it is nothing but they build dashboards for doctors to share data from a device or an app. Unfortunately, the doctors were not that much interested to use that platform.

The major role of AI is helping the doctors, nurses, and healthcare organizations to take appropriate decisions. According to the opinion of professors from the Babson College, healthcare AI is all about augmentation, not automation. Arterys and Astarte Medical, two startup organizations, have taken this approach to AI and machine learning.

Arterys is analyzing the medical image for patterns. Here, researchers use healthcare systems like, MRIs, CT scans, X-rays, Ultrasounds, PET scans to train algorithms to mark skin spots that may nodules or melanoma in lungs that could be cancer. These thousands of scans’ analysis can recognize patterns that humans miss. As a next step, they look for patterns identified in from the analysis of patients’ records. After that, the deep learning system will provide recommendations to the doctor about what treatment need to be given. 

4D Flow, software by Arterys can read an MRI of heart and provide information about how the blood flows through the four heart chambers as well as it calculates other heart health data points that are usually been calculated by the MD, the contours of the heart chambers. The software is highly accurate in this calculation.

Today, cardiologists commonly avoid manual tools and replace them with software tools. Thus, they can save time up to 60 to 90 minutes and spend these to some other important healthcare tasks by saving time.  The Arterys also technologies reduce the variations I healthcare. Occasionally, two doctors may recommend two treatment prescriptions from the same records. But deep learning technologies avoid these chances of getting variations in treatments.

Hospitals are the most potential customers of the deep learning technologies by Arterys. The challenge is that, with the implementation of the deep learning technologies, the hospitals are forced to reduce manpower in this field, on the other hand, several hospital staffs will lose their job. But in reality, implementations of these technologies definitely upgrade the healthcare industry to another level.

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