Speak Ai: How Does Machine Learning Play a Part in iSTRYM?

MINDCURE’s proprietary digital therapeutics platform, iSTRYM, is opening big doors for the mental health industry. But changing the face of mental health care is no easy feat and requires various components working in tandem.  

A major component that’s helping iSTRYM accurately capture data and develop valuable insights around patient status is Speak Ai.  

Speak Ai Inc. is a software company focused on extracting and structuring deep insights from a holistic combination of audio, video, and text. Together, MINDCURE and Speak Ai are empowering digital therapeutics to help optimizers take hold of their wellness journeys and assist clinicians in making more accurate diagnoses and effective treatments.

The Technology Putting Data to Use for Better Treatments

How Does Speak Ai Integrate With iSTRYM & Connected Technology?

Speak Ai provides MINDCURE with an API for in-therapy and post-therapy journaling that structures unstructured data and maps how people are going through their healing journey. It works by processing and structuring large amounts of audio, video, and text data collected using speech recognition, language processing, sentiment analysis, and named entity recognition.  

Put simply, named entity and sentiment analysis are forms of language processing. Named entity involves analyzing audio, video, and text and extracting entities (brands, people, events, percentages, and more). Sentiment analysis involves identifying positive and negative instances from recorded conversations in therapy or unstructured notes. Speak Ai is further developing this to enable users to analyze core emotions.

Speak Ai nicely formats this data along with merged biometric data from devices (like Oura Rings, Google Fit, and Apple Healthkit), and meta-data (location, time of day, and weather). iSTRYM then displays the collected insights back to users. As more media is added, Speak Ai and iSTRYM analyze both individual and multiple entries over time to unlock insights and make large libraries of qualitative data more quantitative.  

How Data Collection & Machine Learning Help Therapists & Optimizers

Access to reliable data is lacking in the healthcare field, with digital therapeutics in its infancy. That’s thanks to the complexities of technology, language, communication, the number of variables, healthcare, and humans.

With great data comes great responsibility. So, where does machine learning come in?

For example, while the technology has advanced dramatically, automated transcription still struggles to provide fully accurate results. So, how in a clinical setting, with music, mumbles, crying, and whatever else, can they be reliable? Users, such as clinicians and their clients, review and update recordings, which then informs and trains the Ai’s machine learning. Through iSTRYM and Speak Ai, users can also request trained transcribers to help them clean up their automated transcripts. With multiple ways to make those changes, the system and analysis improve accuracy over time.

Along with transcriptions, machine learning plays a huge part in identifying patterns in patient data. Say you’re more expressive on rainy afternoons, the technology will pick up on the pattern and become better equipped to make more informed suggestions for dealing with agitation. At the same time, your therapist gets updated on your status, thus improving communication and minimizing the gaps between sessions.  

In structuring data sources like objective speech data and personalized information, machine learning can make compelling suggestions and predictions based on what’s working and what’s not in order to avoid downward spirals and foster positive growth. “That’s something iSTRYM and our team is undertaking together and we’re very excited to be a part of it,” said Tyler Bryden, CEO of Speak Ai.

With iSTRYM, clinicians can better monitor patients before, during, and after treatment to help develop more personalized healing journeys and ensure consistency in care protocols and dosing.

It also cuts down on time spent in therapy and on diagnostics. “For example, if you’re going through conventional therapy, you often focus on recounting the most recent events, in the days or weeks leading up to your therapy session,” says Bryden. “You sometimes miss the chance to move forward on the deeper issues when focused on what you have to tackle now. For some, that is a lost opportunity to face the challenges in our lives and start to make changes that lead to healing.”

“We’re able to present insights in such a way that clinicians can better process in order to make more informed decisions with a wealth of contextual information. From a patient standpoint, it also promotes the ability to work on self-healing, rather than be completely dependent on time spent with a provider.”

Building Trust Into Every Aspect: Privacy, Data, & Comfort

The data that iSTRYM and Speak Ai optimize feed into the ultimate goal of creating healing outcomes. Where privacy and comfort are involved, it comes down to what the patient wants and what makes them the most comfortable.

Speak Ai and MINDCURE believe in the importance of integrating data collection across a combination of platforms in the most subtle and naturalized ways possible, while still ensuring the critical accuracy of insights.

Trust is an enormous factor in the work of both MINDCURE and Speak Ai, two companies determined to build accuracy and comfort into how data is collected, handled, understood, and stored.

Thanks to machine learning and Speak Ai, iSTRYM is developing as the leading digital therapeutics tool helping to heal the world’s pain.