Human-computer collaboration improves predictions

What is it about?

Multiple sclerosis has extremely variable natural course and to date predictions on the rate of disease progression remain suboptimal. This limits the opportunity to tailor therapy on individual patient's needs. To improve predictions on disease course in clinical practice, new approaches such as collective intelligence of human groups and machine learning algorithms are widely investigated. In this paper, we present proof-of-principle that hybrid human-computer predictions provide a significant improvement of prognostic ability .

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Why is it important?

A reliable tool to predict MS progression can be of aid to clinicians to tailor therapy to each patient. A deeper study is therefore of interest. To recruit more humans, we propose a crowdsourcing initiative called DiagnoShare (http://www.phys.uniroma1.it/diagnoshare/)