Patience is Key to Check Reliability of Artificial Intelligence in Medical Sector

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Artificial intelligence (AI) may turn out to be the logical solution if the data handling poses to be the main obstruction. Deep learning and machine learning are making entries into a wide range of industries, and look poised to have a great impact in medical field, a procedure in motion already – and possibly not a point too soon.

There’s lot to improve in terms of getting a correct diagnosis. If the data is to be analyzed, the chance of a patient getting a wrong diagnosis is 100 percent. This opinion was voiced by the founder and CEO of InnVentis, Thomas Wilckens, at the recently finished summit in San Diego on Precision Medicine Leadership.

Wilckens mediated Going Deep in the Fast Lane – the Rise of AI in Precision Medicine, which involved professionals from the industry and academics to parse this ever-evolving segment. Some cases do make use of this advanced technologies, though indeed in rare silo.

Wilckens shared his memories when he started his company in Israel as the country have had digital medical records for over fifteen years, just like in Estonia. These countries made use of different algorithms to administer diseases such as diabetes. He pointed out that the doctor doesn’t meet with the patient unless a computer gives out results which probably point out some deterioration. There are algorithms from the biobank in Estonia that are nearly spooky in projecting when patients will deteriorate.

One of the elemental issues is to check whether the data is set for AI. Electronic health and genomics records can be seen as excellent examples. There’s also the possibility to mine huge amounts of online data to get interesting results. In the end, the sector needs to educate itself to crawl before it can start to walk. AI in the healthcare sector is under test apart from patient care and will need time to prove its worth.

For more information on this: Transparency Market Research

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