Have you ever watched the TV series called House?

It was a very popular long running medical TV drama based on a main character by the name of Dr. Gregory House. His specialty was correctly diagnosing and treating patients with diseases which were often missed and incorrectly diagnosed by other doctors.

Fast forward to 2017 and a tech company has now developed a computer system that can do the same thing.

How clever is this computer system? The following real life examples are just the start and we genuinely think it is set to save millions of lives around the world.

The following information does not take into account your personal objectives, financial situation or needs. You should consider if the relevant investment is appropriate having regard to your own objectives, financial situation and needs.

Rare Diseases

Rare diseases are generally defined as diseases that affect fewer than 1 in 2,000 people. As there are around 7,000 rare diseases worldwide, there are estimates that 350 million people worldwide are living with some form of rare disease. In Australia, an estimated 6% – 8% of the population are affected.

Rare diseases, despite its name, are a serious problem for millions of people. In many instances, these diseases are difficult to diagnose and have similar medical symptoms compared to more common diseases. It is not unexpected that doctors do misdiagnose patients since it is impossible even for the most experienced doctor to know all the symptoms for 7,000 rare diseases.

This is where this tech company’s big data artificial intelligence medical diagnosis system becomes incredibly valuable. In fact, what took Dr. House days or weeks to diagnose, this computer system can do the same in real life within minutes. Let’s look at some recent examples:

1. Rare Leukemia

A patient was admitted to a Japanese hospital and initially diagnosed by doctors with a type of blood cancer called acute myeloid leukemia. The initial treatment appeared to work but her recovery was slower than expected which led the doctors to suspect something else was happening.

The doctors consulted the big data computer medical system which had read and interpreted tens of millions of medical papers on cancer. They provided the system with the patient’s records and genetic data. The system then identified gene mutations in the patient that are unique to a specific rare form secondary leukemia different to the initial diagnosis and she was then successfully treated. Doctors said it would have taken humans perhaps 2 weeks to come to the same correct diagnosis.

It took this big data medical computer system 10 minutes. The system has since gone on to help diagnose many more illnesses in the same hospital.

2. Rare Disease Centre

In a rare disease centre within a German hospital, there is a 6,000 person long waiting list where some patients have been seen previously by up to 40 doctors that have not been able to properly diagnose them. The hospital has recently started using the same computer system to help provide desperately needed answers for these patients.

In an initial trial, doctors randomly selected some past patient records and fed them into the computer system as a test. The system correctly identified the top possibilities for the diseases these patients had. It was all completed in a manner of seconds.

This computer system has great potential to improve healthcare for millions of lives around the world and in many cases also save those lives with earlier diagnosis. Do you know which tech company has spent years developing this big data computer system?

To find out which company it is, why AtlasTrend’s big data focused managed fund has invested in the company’s shares and why they remain one of the cheapest big data technology shares to invest in, click here to sign up for a free AtlasTrend membership to access all our articles in full.

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About Kent Kwan

Kent Kwan is a Co-Founder of AtlasTrend, an investment platform that makes it easy for anyone to learn and invest in trends impacting our world. Kent has over 17 years experience in financial markets including as Chief Investment Officer at Arowana International Limited, and roles at JP Morgan and Macquarie.