Machine Learning Platform Can Accurately Predict Onset of MS, Maker Says

Machine Learning Platform Can Accurately Predict Onset of MS, Maker Says

IQuity, a data analytics company, announced the launch of an analytics platform that uses machine learning to predict, identify, and monitor chronic disease within large populations of patients, including multiple sclerosis (MS).

The platform was validated using a pilot study that assessed the healthcare claims of 20 million people in New York, which encompassed four billion data points. IQuity focused on using these data to predict the onset of MS.

Results showed that the approach was able to predict, with greater than 90 percent accuracy, the onset of MS within the New York population at least eight months before traditional methods would enable a diagnosis of the disease.

Earlier diagnosis in MS patients, as well as other patient populations, would lead to significant benefits in outcomes and also to financial savings, particularly as healthcare spending tends to increase prior to obtaining a definite diagnosis.

That is why the development of this new technology may lead to an improvement in patient outcomes, while also lowering healthcare costs.

Consequently, this platform is attractive to organizations that are responsible for healthcare expenses, such as employers, benefit managers, health insurance companies, pharmaceutical companies, and care management companies.

According to IQuity, this approach can be applied to any disease.

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IQuity started working with machine learning, which is a subset of artificial intelligence, more than eight years ago. Machine learning is based on the idea that a system can learn from data, identify patterns within the data, and make decisions without human intervention.

“Recent advances in our computational abilities and machine learning methods have allowed us to look at large datasets to derive insights. Our first application combed through genomic data to create diagnostic tools for providers. Our new platform extends our experience and knowledge of data science and chronic disease to inform interventions across the healthcare continuum,” Chase Spurlock, IQuity CEO, said in a press release.

IQuity officials also announced that Ray Guzman and Damian Mingle, two former senior executives of WPC Healthcare/Intermedix, a healthcare data analytics company, have been named advisors and will provide assistance in developing the new technology.

“I am excited to advise IQuity as it builds on its groundbreaking machine learning work in genomics to create technology that analyzes healthcare data across an entire population. The predictive and prescriptive possibilities of this approach can transform how healthcare is provided and paid for,” said Guzman.

“The work IQuity has accomplished in this area to date is impressive and the new platform holds the potential to revolutionize the way diseases are detected and monitored,” Mingle concluded.

Iqra holds a MSc in Cellular and Molecular Medicine from the University of Ottawa in Ottawa, Canada. She also holds a BSc in Life Sciences from Queen’s University in Kingston, Canada. Currently, she is completing a PhD in Laboratory Medicine and Pathobiology from the University of Toronto in Toronto, Canada. Her research has ranged from across various disease areas including Alzheimer’s disease, myelodysplastic syndrome, bleeding disorders and rare pediatric brain tumors.
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Iqra holds a MSc in Cellular and Molecular Medicine from the University of Ottawa in Ottawa, Canada. She also holds a BSc in Life Sciences from Queen’s University in Kingston, Canada. Currently, she is completing a PhD in Laboratory Medicine and Pathobiology from the University of Toronto in Toronto, Canada. Her research has ranged from across various disease areas including Alzheimer’s disease, myelodysplastic syndrome, bleeding disorders and rare pediatric brain tumors.
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