Noona unleashing the potential of patient reported data in cancer care

Do you know how cancer patients are doing in real life? Do you have hard data conveniently at hand about treatment outcomes, adverse effects, and patient quality of life? Or is there something critical missing?

Noona’s vision is to be the world´s largest prospective real-time database of cancer patients, thus generating immense amounts of data that can help researchers and medical teams around the world to treat and overcome cancer. To deliver on this vision, we are pleased to introduce Tommi Vilkamo who joins Noona Healthcare as Head of Analytics and Business Development, bringing in 13 years of data-analytics management experience from Nokia and Microsoft. “I feel so energized landing with this job. Noona is something I genuinely believe in, and we have a chance of achieving something truly meaningful”.

Looking at the burgeoning field of wearables, Noona will have the ability to tap into a wide range of new data sources, all the way from medical grade devices to smart watches and basic fitness trackers. “Our strategy is to think simple”, says Tommi: “There are medical-grade devices that can be useful in a medical research settings or during shorter periods of active treatment, but it is difficult to get thousands of cancer survivors to use for them for several years. Even smart watches are something that only a small minority of cancer patients will naturally use by 2019. However, we have reason to believe that even basic activity data from popular $15 fitness trackers would be helpful for doctors to assess patient wellbeing – especially when combined with other data sources”.

As the data volume grows bigger, Noona’s focus will shift to advanced analytics and delivering actionable insights. “There are two interesting breakthroughs in machine learning that we can tap into“, says Tommi. “At the deep end, we have things like Watson oncology, and at the shallow end – but equally important – we have something that I call as the democratization of machine learning; What used to require several weeks from a team of skilled data scientists and engineers, can be now created and deployed in a matter of hours. Algorithms will not replace medical professionals, but they will help them do a better job and significantly reduce their workload.

It’s an exciting journey ahead. If you want to play a part, please don’t hesitate to contact Tommi at or +358504860707.

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