Tag Archives: artificial intelligence

Enlitic closes funding to advance Artificial Intelligence solutions for radiologists

enlitic_logo

–(BUSINESS WIRE)– Enlitic, a privately-held company utilizing artificial intelligence to streamline medical imaging workflows for radiologists, announced the close of its $15M Series B financing round. The investment was led by Marubeni, with whom the company has been developing the Japanese market since 2017.

The round saw further investment from Capitol Health, who previously led the company’s Series A in 2016, as well as new participation from several top investors in Australia.

Kevin Lyman, CEO of Enlitic, commented:

“Radiologists have one of the hardest jobs in the world. They need to be able to identify thousands of different abnormalities in hundreds of different types of images. Even a single mistake can mean life or death, and yet they’re asked to read under tremendous time pressure in an environment full of distractions.”

Enlitic – deep learning medical imaging process
Enlitic - deep learning medical imaging process

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Using Machine Learning to develop blood test for key Alzheimer’s biomarker

giornata-mondiale-alzheimer-2018-824-464Alzheimer’s disease, a terminal neurodegenerative disease, has historically been diagnosed based on observing significant memory loss. Recent research has shown that a biological marker associated with the disease, a peptide called amyloid-beta, changes long before any memory-related issues are apparent.

Examining the concentration of the peptide in an individual’s spinal fluid provides an indication of risk decades before any memory related issues occur. Unfortunately, accessing spinal fluid is highly invasive, requires an anaesthetist and is expensive to conduct on large segments of the population. Hence, there is a strong effort in the research community to develop a less invasive test, such as a blood test, that can yield information about Alzheimer’s disease risk.

A recent paper by my team at IBM Research – Australia, published today in Scientific Reports, used machine learning to identify a set of proteins in blood that can predict the concentration of amyloid-beta in spinal fluid. The models we built could one day help clinicians to predict this risk with an accuracy of up to 77%.

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Scientific ReportsA blood-based signature of cerebrospinal fluid Aβ1–42 status (Published: 11 March 2019)

Philips incubator program focuses on AI healthcare

philips-incubator-program-focuses-on-ai-healthcare-min2-min-910x420As a global leader in health technology, Philips, or Royal Philips, has opened a collaboration programme for 19 start-ups to join the Philips incubator program.

The initiative is a global collaboration working across the Philips innovation hubs across the world with the focus on improving AI in healthcare.

The global collaboration program includes intelligent treatment for radiology, oncology and ultrasound. It also covers AI clinical decisions support tools such as image interpretation, analysis and workflow tools.

Out of 750 applicants, 19 of the most promising start-ups were selected for the incubator program.

How it works
The fast-track program takes place over 12 weeks. During this time Philips will engage with all of the early stage start-ups, which come from 14 different countries.

Patient-Centred AI
While AI has already proven its ability to improve patient outcomes and the efficiency of care, it is important not to lose sight of the patient-centred approach.

Accelerating breakthrough innovation
With the collaboration programs, Philips aims to speed up breakthrough innovation within the health industry. They are doing this through supporting internal venturing and external start-up engagement.

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