Testimonials

Jeroen Gerritsen, Emotional Brain

"At Emotional Brain, we share ATIA's belief in personalized medicine. The ATIA approach can give us new advanced tools to incorporate ATIA's vision in our drug development programme. AI technology could potentially classify research subjects, and eventually patients, more accurately than the methods currently used. Moreover, calculations can be done faster and cut down the number of necessary predictor values, while still yielding superior sensitivity and specifity. This may be an immensely valuable timesaving feature.

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Bea Tiemens, Manager Research, Indigo Service Organization

"The possibility of an inter-institutional referral decision support system is now being considered.” 

Hans van der Heijden, Stichting Myosotis

“At Myosotis, we want to contribute to building robust solutions that can help physicians and therapists make informed decisions based on a diversity of patient data. We were convinced that the AMDAS model that we had developed was optimally using no fewer than 26 patient parameters to predict the best care. Not only have ATIA shown that they could further improve that model using the same parameters, but they have also
demonstrated how the best care prediction could be further differentiated.
ATIA has helped us to perfect what was already a very good idea.”

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Martijn Arns, Brainclinics

"The ATIA advanced analytics have more than doubled the detection of non-responders. (the so called specifity), while still obtaining a 90% responder detection rate (or sensitivity). In doing so ATIA highlighted the importance of variables that looked promising in the clinic, but did not reach significant explanatory value with mainstream statistical analyses. This wil generate new hypotheses about patterns of brain dysfunction in these non-responders and guide the search for new neuromodulatory theapeutic interventions to treat them." The next step in the collaboration between the two institutes will be to publish these results as proof of concept, to validate them in an prospective sample and explore the data further with other data mining tools.

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