AI in Psychiatric Treatment – Using Machine Learning to Increase Treatment Efficacy in Mental Health
Reporter: Aviva Lev- Ari, PhD, RN
Featuring Start Up: aifred
www.aifredhealth.com
About Us
The inability to predict any given individual’s unique response to psychiatric treatment is a huge bottleneck to recovery from mental health conditions.
To address this challenge, we are creating a deep-learning based clinical decision tool for physicians to bring personalized medicine to psychiatry.
Initially, we will be focusing on treatments for depression, but we plan to scale Aifred to encompass all mental health conditions in order to amplify clinical utility. At its core, aifred is leveraging the collective intelligence of the scientific and medical community to bring better healthcare to all.
We are a proud official IBM Watson AI XPrize team, headquartered in Montreal, Canada.Read more about us:
Deep Learning
Something unique to every machine learning company is the precise nature of their hyperparameter optimization and goals of their model. We will optimize aifred with the help of a distributed network of domain experts in psychiatry — a collaboration unique to aifred health. We are implementing attention networks responsible for removing the “black-box” nature of neural networks. As well, we are analyzing the quality of model predictions, allowing both for greater interpretability of model decisions and the generation of new basic research questions, which are going to be unique to the data-set and optimization techniques we develop in-house. By training aifred on reliable datasets, we are able to ensure quality input to our model. De-identified patient outcomes will feed back into our neural networks to continuously improve aifred’s predictive power. Feature engineering is an important part of determining which inputs go into a network and varies how it’s done for every team- once again, this will be undertaken with the support of diverse group of experts we are recruiting.
Our Product
Treatment Prediction
The aifred solution makes use of innovative and powerful machine learning techniques predict treatment efficacy based on an array of patient characteristics.
Interpretability
Forget the blackbox! Our system will provide a report highlighting the most significant features that led to a treatment prediction.
Patient Data Tracking
Track patient symptoms and test results to monitor outcomes or make new predictions. Banks of standardized questionnaires, data visualization, scheduling software — all of it modular and capable of being tailored to clinicians’ needs.
Electronic Patient Record
Keep all important patient information in one place, and get insights using our analytics.
In the News:
Montreal Gazette article written about our startup:
Press about us winning first place globally in the IBM Watson AI XPrize milestone competition
Forbes article that features our CTO, Robert Fratila:
https://www.forbes.com/sites/insights-intelai/2018/11/29/5-entrepreneurs-on-the-rise-in-ai/
Post about our graduation from the prestigious creative destruction lab program:
McGill University article featuring us:
REFERENCE
The Incredible Ways Artificial Intelligence Is Now Used In Mental Health
Bernard Marr 12:23 am
4 Benefits of using AI to help solve the mental health crisis
There are several reasons why AI could be a powerful tool to help us solve the mental health crisis. Here are four benefits:
- Support mental health professionals
As it does for many industries, AI can help support mental health professionals in doing their jobs. Algorithms can analyze data much faster than humans, can suggest possible treatments, monitor a patient’s progress and alert the human professional to any concerns. In many cases, AI and a human clinician would work together.
- 24/7 access
Due to the lack of human mental health professionals, it can take months to get an appointment. If patients live in an area without enough mental health professionals, their wait will be even longer. AI provides a tool that an individual can access all the time, 24/7 without waiting for an appointment.
- Not expensive
The cost of care prohibits some individuals from seeking help. Artificial intelligent tools could offer a more accessible solution.
- Comfort talking to a bot
While it might take some people time to feel comfortable talking to a bot, the anonymity of an AI algorithm can be positive. What might be difficult to share with a therapist in person is easier for some to disclose to a bot.
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