Our personalized treatment recommendation system employs machine learning and data mining algorithms that process the pre-treatment clinical and laboratory information (including EEG) to confirm diagnosis and predict the response to a variety of treatments for the individual patient. The report sent back to the doctor includes a list of likely diagnoses and treatment options, each with an associated response probability.
Sept. 12, 2014
Dr. Gary Hasey received the RO Jones Award as best paper at the CPA-2014 conference held in Toronto.
Our machine learning based digital psychiatric expert system will offer the clinician a powerful new tool capable of assisting with the process of diagnosis and personalized treatment planning. Our technology would allow the health care professional to determine, from the outset, the specific type of treatment that would be most effective for an individual patient. This would reduce the time to recovery and dramatically reduce the impact of mental illness upon the individual and his or her family, the employer and the insurance provider.
The system and technology can potentially be used to determine or confirm other medical diagnosis, or estimate the level, index, severity or critical medical parameters of the illness or condition.