SoftBank investment group is leading a $63 million (€59 million) investment in AI Medical Service Inc, a company which makes AI software that diagnoses stomach cancers.
Colonoscopy technology concept with 3d rendering x-ray endoscope inside of intestine. Credit: Phonlamai Photo / Shutterstock.
The AI software won’t solely diagnose the potential gastrointestinal (GI) issues but will boost the work of medical professionals by producing faster, earlier and more reliable diagnoses.
This is the third SoftBank Vision Fund 2 investment in the Japanese conglomerate’s home country since November. Vision Fund 2 is an offshoot of SoftBank’s Vision Fund – the world's largest technology-focused investment fund with $100 billion.
AI Medical Service is a Japanese company dedicated to the early detection of GI cancers – though there is the potential that its technology can be applied to other areas of the body.
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According to AI Medical Service Inc, Japanese endoscopes already account for 70% of the world’s share of equipment so this could be seen as a natural expansion of this medical export.
AI Medical “is a company that has the potential to take its business to the global market, not just Japan,” said Kentaro Matsui, SoftBank Vision Fund’s Managing Partner.
Gastrointestinal cancers currently account for one in four cancer cases and one in three cancer deaths globally.
SoftBank has been systematically expanding its portfolio over the last year, despite reports that a slow in investments would follow a tech holdings crash.
In November, SoftBank invested in Aculys Pharma LLC and lead a $220 million (€208 million) investment in Agile Robots last year, while the SoftBank Robotics arm joined forces with smart building systems leader Inforgrid in January and announced it would be buying a 5% stake in Hong Kong-based Avalon SteriTech in April.
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In recent years the use of AI in cancer detection has been gaining both interest and investment because of its accuracy in predicting tumour regrowth, detecting breast cancer during screening, cutting hospital error rates and reducing result waiting times.
America’s National Cancer Institute, for example, taught an AI machine to detect precancerous lesions using 60,000 cervical images. The study found that over the subsequent seven years after the analysis, the AI results produced more accurate predictions of the lesions, than other methods.
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