Artificial Intelligence in Healthcare: What Works and What Doesn't?
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Artificial Intelligence in Healthcare: What Works and What Doesn't?

By CIOReview | Wednesday, April 18, 2018

After all the valuable contributions it has done to the healthcare industry, Artificial intelligence (AI) will remain “the buzzword” for the next few centuries. Recently, the hype of machine- learning has begun to overlap with the reality. The benefits AI provides for the healthcare industry fall under these categories: algorithmic solutions, visual tools, and medical practice.

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In the recent past, algorithmic solutions were the most commonly used AI applications in the healthcare industry. Computers can extract algorithmic data saved by human over time and apply it to dissolve problems, for example, providing the right drugs on right time. When it comes to visual tools, the optical pattern recognition software has proved that it is more accurate than human eyes. Storing and comparing thousands of images at the same time means their results can fail even the best physician. In light of the staggering growth of machine learning and deep learning techniques, different sectors of healthcare like radiology, pathology, dermatology, and ophthalmology can be benefited. Moreover, the natural language processing and machine learning from expert physicians are going to take the healthcare industry to an advanced stage. Looking at the hope AI provides startups, tech firms are starting to invest their interests on AI; however many fear that AI would replace humans in the nearest future.

The best side of the coin is that AI integrated healthcare can provide high-quality medical services at affordable price. Over time, patients can take care of themselves with a variety of AI tools. However, this may erase all those promising healthcare jobs. In general, AI still has a long way to go, and these advancements will always be a blessing in disguise.