One of the hottest tech trends these days is artificial intelligence (AI) , with researchers looking into the use of AI for applications ranging from autonomous vehicles to financial management, to healthcare.


The healthcare industry is often at the forefront of innovation and technological advances due to the wealth of medical devices, equipment and processes that permeate the industry. But AI in particular seems poised to transform the way we collect, understand and use data on patient health, healthcare services and historical health data to revolutionize medical diagnostics, treatment and research.

What makes AI so suitable for use in medical research and the healthcare industry?

Largely, the appeal of AI is its ability to collect, analyze and make sense of vast amounts of unstructured and variable data—especially text, statistical numbers, and visual images—quickly and often more accurately than a human being. With the increase in digitization and computing power, there has been an ever-growing wealth of digital data produced by individuals and systems, and advances in machine learning and analytical algorithms mean AI systems will become ever more powerful and effective at performing their assigned tasks.

We’re already seeing innovative research into applications of AI across the medical and healthcare industries—some applications already seeing use, others still in development or testing but showing great promise. AI for Diagnostics

Determining a patient’s diagnosis is a vital aspect of healthcare. Care providers and medical researchers alike can see the useful potential of using AI to augment or replace the human ability to identify illness and disease. Medical Imaging

Diagnosing patients according by examining medical images is a prime candidate for the application of AI systems to improve both the speed and accuracy of performing these tasks. As such, the development of algorithms and machine learning systems is one of the big research areas for healthcare AI.

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In particular, medical imaging is ideal for AI because we already possess a wealth of medical scans, collected, categorized and stored at medical institutions across the country—many of which are digital, or undergoing the digitization process. These massive collections of image data can be used to train AI systems not only to perform the collection and categorization of scans, but to analyze these medical images to identify a myriad of health conditions—everything from bone fractures to pneumonia to cancer. […]

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