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Artificial Intelligence In Medical Devices

Ivan Pandiyan, VP of Global R&D, Natus Medical [NASDAQ:NTUS]
Ivan Pandiyan, VP of Global R&D, Natus Medical [NASDAQ:NTUS]

Ivan Pandiyan, VP of Global R&D, Natus Medical [NASDAQ:NTUS]

The medical device industry is at the forefront of technological advancements that will change the way we practice medicine today. Researchers and manufacturers are focused on producing innovative solutions to integrate accuracy with automation. Globally, there are several emerging applications of artificial intelligence (AI) in the medical device sector today, all of which fall into three distinct categories:

A) Management of Chronic Diseases–Companies have developed machine learning to monitor patients using sensors and are automating the delivery of treatment and prescription medicine utilizing connected mobile applications (e.g. diabetes patients and automated delivery of insulin).

B) Medical Imaging–The integration of AI-driven platforms in medical scanning devices to improve image quality and clinical results while reducing expose to radiation (e.g. GE Healthcare CT scans for liver and kidney lesions).

C) AI and Internet of Things (IoT)–The assimilation of AI and IoT in order to monitor patient adherence to treatment protocols and to improve clinical outcomes (e.g. Philips healthcare solution for continuous monitoring of patients in the ICU).

Within these three areas, AI has the opportunity to change the way medical practitioners apply natural language processing to interpret the expanding scientific literature while assembling diverse electronic medical records into one central location. The movement from clerical patient data management towards cloud data management where AI analysis will be performed will, in turn, reduce human errors within the clinical sphere, positively influencing patient care. Utilizing the cloud to manage and interpret patient records along with scientific research, will allow medical practitioner with the opportunity to have access to a patient’s past in order to predict and mediate future maladies.

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