With a team of Computer Science students from the University of Colorado Denver, cliexa built its’ first artificial intelligence software. This AI Model assesses the comparative impacts of behavioral health metrics on the risk of opioid addiction. The project is our initial AI model, contributing to our larger goal of unleashing the power of AI in healthcare.
The Senior Design Program
The Senior Design Program at the University of Colorado Denver partners with local companies to mentor students on a cumulative project for software development. Organized by Debra Parcheta and the School of Computer Science and Engineering, students in the Senior Design class use their prior learning and experiences to design and build working software for real-world problems. We’re proud to sponsor a project for the 2019-2020 academic year, which resulted in our first AI model.
The Initial Project Proposal
Tackling our first AI project was a daunting task, but we knew this would lead to opportunities across other subspecialties. Our initial brainstorming session produced the design of a convolutional neural network algorithm. This method enables the algorithm to flag potential flareups, unplanned hospitalizations, and other risk factors. We recognized that if we could harness the power of AI to identify correlations within patient-reported data, our platform could revolutionize the personalization of healthcare.
This initial project proposal proved to be a larger concept than what was feasible in a 9-month project timeline. The idea behind this served as the driving factor in the development of our resulting AI model. We narrowed our focus on integrated pain management, where we developed something truly novel in digital health technology.
The Artificial Intelligence Model
Our team, led by Research & Development Lead, Ronald Berry III, consisted of three students: John Williams, Mengistu Shuma, and Uriah Moeller. Over the first semester, our project scope honed in on integrated pain management. After outlining technical specifications, we landed on the idea of improving the risk stratification of modern pain management to flag at-risk patients based on a myriad of behavioral and physical health assessments.
Throughout development, the students made the decision to pursue a convolutional neural network, rather than an alternative form called clustering. When the overarching architecture was decided on, the team went to work on their first-ever machine learning model. They structured the model with seven assessment inputs with an output structure of “low”, “medium,” and “high” risk for potential opioid misuse or addiction. Once the initial structure was defined, the students utilized 1,300 unique de-identified data points to test the model.
The final challenge was fine-tuning the algorithm to obtain an accurate output in relation to the Screener for Opiate Addiction in Patients with Pain (SOAPP-14). Widely used in pain management, the SOAPP-14 is the gold standard for identifying chronic pain patients’ risk of opioid addiction. Upon the final iteration, the AI model achieved a 96.3% accuracy when compared to the SOAPP-14.
Without a doubt, this project proved successful across all deliverables outline in the project specifications. While our model is accurate in comparison to the SOAPP-14, we plan to clinically validate our tool for pain management.
Applying AI in Healthcare
With a background in Computer Science, Mehmet Kazgan has a comprehensive understanding of machine learning and neural networks. This experience, in addition to his time as VP of Engineering at Aetna, establishes him as an expert in leveraging AI technology in modern healthcare as our CEO & Founder. Over the past year, Mehmet joined industry leaders to discuss the role of artificial intelligence in modern healthcare.
#AskTheCEO Podcast
Back in March, we joined the #AskTheCEO podcast with Avrohom Gottheil in a thorough conversation on how cliexa aims to implement machine learning on the Azure Marketplace. The two discuss the importance of utilizing innovative technology to stay at the forefront of patient care. With data collection and AI capabilities rapidly advancing, we hope to see this shift across healthcare.
Colorado Advanced Industries Grant
Fast forward to May, the Colorado Office of Economic Development and International Trade awarded our team the Advanced Industries Accelerator Grant with the purpose of developing a machine learning module for cardiovascular risk. The Colorado OEDIT Advanced Industries Early-Stage Capital and Retention Grant is designed to support early-stage start-ups with viable products that meet a market need and are established in Colorado. Our proposed project is to expand the cliexa-PULSE home-health monitoring platform and develop a predictive risk model for cardiovascular disease. This machine-learning algorithm would expand upon this model for opiate risk and reconfigure to analyze for risk of cardiovascular disease.
Who Would Have Thought Podcast
A few weeks ago, Robert Niichel and Sacha Heppell with SmartTab interviewed Mehmet on their podcast where they took a deep dive into the value of patient-reported data in AI models. In this episode, they discuss the value of patient-reported data and how cliexa leverages artificial intelligence (AI) in the platform. Some of the key topics include improving Crohn’s disease outcomes, patient-centered tools, data in healthcare, and the future of AI.
Featured Publication with CU Boulder’s CANLab
Most recently, our partners at the CU Boulder’s CANLab published their research on applications of AI in chronic back pain. Their focus on patients’ emotional health and its’ impacts on pain severity leverages machine learning to predict future episodes. For the full publication and more information on this fascinating research, check out our announcement!
The Future of AI in cliexa
So now what? Where are we going from here with our AI goals?
In short, the opportunities are endless. As a subspecialty agnostic platform, our long-term goals with AI will expand to other areas outside of integrated pain management. Already, partnering with the American College of Cardiology, our focus shifts to an interventional AI risk model for cardiovascular diseases. As our experience with machine learning expands, we aim to find institutional partners to enter the world of AI with. To get in touch with our team, reach out via our Contact Us page.
Our Next Steps
Although COVID-19 changes the outlook of this upcoming academic year, we are proud to sponsor another project with UCDenver. We look forward to working with our 2020-21 cohort of students on a new project exploring the workflows for claims verification.
Congratulations to John, Mengistu, and Uriah on graduating this past May and best of luck to you all on your future endeavors!
An Artificial Intelligence Model for Integrated Pain Management
BlogWith a team of Computer Science students from the University of Colorado Denver, cliexa built its’ first artificial intelligence software. This AI Model assesses the comparative impacts of behavioral health metrics on the risk of opioid addiction. The project is our initial AI model, contributing to our larger goal of unleashing the power of AI in healthcare.
The Senior Design Program
The Senior Design Program at the University of Colorado Denver partners with local companies to mentor students on a cumulative project for software development. Organized by Debra Parcheta and the School of Computer Science and Engineering, students in the Senior Design class use their prior learning and experiences to design and build working software for real-world problems. We’re proud to sponsor a project for the 2019-2020 academic year, which resulted in our first AI model.
The Initial Project Proposal
Tackling our first AI project was a daunting task, but we knew this would lead to opportunities across other subspecialties. Our initial brainstorming session produced the design of a convolutional neural network algorithm. This method enables the algorithm to flag potential flareups, unplanned hospitalizations, and other risk factors. We recognized that if we could harness the power of AI to identify correlations within patient-reported data, our platform could revolutionize the personalization of healthcare.
This initial project proposal proved to be a larger concept than what was feasible in a 9-month project timeline. The idea behind this served as the driving factor in the development of our resulting AI model. We narrowed our focus on integrated pain management, where we developed something truly novel in digital health technology.
The Artificial Intelligence Model
Our team, led by Research & Development Lead, Ronald Berry III, consisted of three students: John Williams, Mengistu Shuma, and Uriah Moeller. Over the first semester, our project scope honed in on integrated pain management. After outlining technical specifications, we landed on the idea of improving the risk stratification of modern pain management to flag at-risk patients based on a myriad of behavioral and physical health assessments.
Throughout development, the students made the decision to pursue a convolutional neural network, rather than an alternative form called clustering. When the overarching architecture was decided on, the team went to work on their first-ever machine learning model. They structured the model with seven assessment inputs with an output structure of “low”, “medium,” and “high” risk for potential opioid misuse or addiction. Once the initial structure was defined, the students utilized 1,300 unique de-identified data points to test the model.
The final challenge was fine-tuning the algorithm to obtain an accurate output in relation to the Screener for Opiate Addiction in Patients with Pain (SOAPP-14). Widely used in pain management, the SOAPP-14 is the gold standard for identifying chronic pain patients’ risk of opioid addiction. Upon the final iteration, the AI model achieved a 96.3% accuracy when compared to the SOAPP-14.
Without a doubt, this project proved successful across all deliverables outline in the project specifications. While our model is accurate in comparison to the SOAPP-14, we plan to clinically validate our tool for pain management.
Applying AI in Healthcare
With a background in Computer Science, Mehmet Kazgan has a comprehensive understanding of machine learning and neural networks. This experience, in addition to his time as VP of Engineering at Aetna, establishes him as an expert in leveraging AI technology in modern healthcare as our CEO & Founder. Over the past year, Mehmet joined industry leaders to discuss the role of artificial intelligence in modern healthcare.
#AskTheCEO Podcast
Back in March, we joined the #AskTheCEO podcast with Avrohom Gottheil in a thorough conversation on how cliexa aims to implement machine learning on the Azure Marketplace. The two discuss the importance of utilizing innovative technology to stay at the forefront of patient care. With data collection and AI capabilities rapidly advancing, we hope to see this shift across healthcare.
Colorado Advanced Industries Grant
Fast forward to May, the Colorado Office of Economic Development and International Trade awarded our team the Advanced Industries Accelerator Grant with the purpose of developing a machine learning module for cardiovascular risk. The Colorado OEDIT Advanced Industries Early-Stage Capital and Retention Grant is designed to support early-stage start-ups with viable products that meet a market need and are established in Colorado. Our proposed project is to expand the cliexa-PULSE home-health monitoring platform and develop a predictive risk model for cardiovascular disease. This machine-learning algorithm would expand upon this model for opiate risk and reconfigure to analyze for risk of cardiovascular disease.
Who Would Have Thought Podcast
A few weeks ago, Robert Niichel and Sacha Heppell with SmartTab interviewed Mehmet on their podcast where they took a deep dive into the value of patient-reported data in AI models. In this episode, they discuss the value of patient-reported data and how cliexa leverages artificial intelligence (AI) in the platform. Some of the key topics include improving Crohn’s disease outcomes, patient-centered tools, data in healthcare, and the future of AI.
Featured Publication with CU Boulder’s CANLab
Most recently, our partners at the CU Boulder’s CANLab published their research on applications of AI in chronic back pain. Their focus on patients’ emotional health and its’ impacts on pain severity leverages machine learning to predict future episodes. For the full publication and more information on this fascinating research, check out our announcement!
The Future of AI in cliexa
So now what? Where are we going from here with our AI goals?
In short, the opportunities are endless. As a subspecialty agnostic platform, our long-term goals with AI will expand to other areas outside of integrated pain management. Already, partnering with the American College of Cardiology, our focus shifts to an interventional AI risk model for cardiovascular diseases. As our experience with machine learning expands, we aim to find institutional partners to enter the world of AI with. To get in touch with our team, reach out via our Contact Us page.
Our Next Steps
Although COVID-19 changes the outlook of this upcoming academic year, we are proud to sponsor another project with UCDenver. We look forward to working with our 2020-21 cohort of students on a new project exploring the workflows for claims verification.
Congratulations to John, Mengistu, and Uriah on graduating this past May and best of luck to you all on your future endeavors!
Our Featured Publication with CU Boulder’s CANLab
NewsOur partners at the University of Colorado Boulder’s Cognitive and Affective Neuroscience Lab (CANLab) feature our collaboration with their most recent publication.
The Publication
Featured in Neurotherapeutics, the CANLab researchers explore the application of machine learning to chronic pain assessments, leveraging emotional body maps powered by the cliexa platform. With emotional and behavioral health as cornerstones of their chronic pain research, the study explores the emotional processing associated with body sensations. Remote patient outcomes reporting for the study was built into our integrated pain management platform, cliexa-EASE.
The study consisted of sixty-five chronic back pain patients, of whom reported their pain intensity and its’ location on an interactive body map. This focus on patient-reported data aligns with cliexa’s vision of placing the patient at the center of their care journey. With these metrics, the team leveraged two separate machine learning models to predict future pain levels two weeks in advance.
The CANLab’s Initial Findings
The CANLab’s initial findings were deduced as two separate models. One model ignored pain-related features as predictive measures of future pain with the second factoring in existing levels of pain. The contribution of emotions, especially emotional experiences felt by the patients, impacted chronic pain levels considerably. With these findings, they believe these results could contribute to the generation of a novel artificial intelligence model to assist in the diagnosis and treatment approaches to chronic back pain. Read the complete publication here.
Future Collaborations and Research
Our collaboration with the CANLab is one of many ways we strive to innovate in the clinical research space. With artificial intelligence moving into the forefront of modern healthcare, we are continually searching for further areas to drive innovation in the medical field. If you are interested in exploring some of our research partnership opportunities, please Contact Us for further details.
Tune in to the Who Would Have Thought – Digital Health Podcast
Newscliexa’s CEO & Founder, Mehmet Kazgan, is featured in the Who Would Have Thought – Digital Health Innovation Podcast! The Who Would Have Thought – Digital Health Innovation Podcast host, Robert Niichel, CEO and Founder of SmartTab, was joined by Chief Marketing Officer, Sacha Heppell.
In this episode, we take a deep dive into the value of patient-reported data and how cliexa leverages artificial intelligence (AI) to drive innovation in healthcare. Let’s take a look at the interview topics:
1. Improving Crohn’s Disease Outcomes
With any chronic disease, patients should be at the center of their own care. Our goal is to empower patients to guide their own care journey through real-time symptom reporting at the tip of their fingers. The cliexa-IBD platform embodies this approach by collecting information in-between visits to provide physicians a comprehensive overview of day-to-day symptoms experienced by their patients.
2. Patient-Centered Platforms vs. Tools for Physicians
Applications that benefit both the patient and physician journeys are critical to successful digital health tools. We subdivide our platform by two separate segments: Patient Profile and Diagnostic Profile. While the patient profile remains stagnant based on past medical and family history, the diagnostic profile is highly influenced by real-time symptoms experienced by the patient and has a large effect on their changing treatment plan. Check out our solutions for more information!
3. Data in Healthcare
The fourth industrial revolution is here, and data is at the forefront of innovation. For healthcare, the power of data is seen every day with each new discovery surrounding COVID-19. Digital health puts actionable data in the hands of clinical professionals and researchers to collect real data from patients and put it to use in defining their personalized treatment plans.
4. The Future of AI in Healthcare
Further building on how data will change modern healthcare, artificial intelligence accelerates the rate at which we identify trends in patient-reported data. With AI at the forefront of innovation, cliexa is proud to be implementing our proprietary model into chronic pain settings. Stay tuned for more information on our opioid risk AI model.
Thanks to Robert and Sacha for hosting cliexa on the Who Would Have Thought – Digital Health Innovation Podcast. We enjoyed the mindful discussion surrounding patient-reported outcomes and the future of AI in modern healthcare. Tune in to the podcast for more information on how cliexa is reinventing the way medical conditions are managed!
Recapping the UX & Telehealth RapidConf Event
NewsBene Studio RapidConf Event Recap
cliexa was a proud exhibitor for the UX & Telehealth RapidConf as a part of their COVID-19 Crisis Workshop! Joining technology leaders from around the world, our team became a part of the conversation on the importance of UX design in telehealth.
The Role of UX in Digital Health
This year has been a game changer for digital health technologies, with telehealth and telemedicine being at the forefront of every clinical practice. With the rapid deployment of technologies, it’s critical to acknowledge how user experience (UX) plays a role in a patient’s healthcare journey. Designing a user-friendly application or web interface is critical to engaging patient’s in their treatment and is where UX plays a huge role in these novel technologies. With the shift to patient-driven healthcare, there is the need to instill new habits to make interacting with the technology a part of their routine.
Our team has emphasized the importance of UX/UI design on the patient journey over the recent months. While our platform primarily gears towards clinicians and medical staff, patients must have their own intuitive interface. Check out our virtual health solution to visualize the UX design work we have implemented as healthcare goes digital.
A huge thank you to Bene Studio for having us as an exhibitor and to all of the panelists that took part in the event!
Digital Tools that Help Patients Where They Are
NewsDigital Health at the Forefront
Over the past few days, healthcare professionals and industry leaders across the nation are suggesting that our healthcare environment is more akin to rural care than ever before. Given the state of our rural care in the United States, this proves to be challenging for healthcare systems to adopt novel technologies that curb the challenges of virtual care. With patients less likely to pursue care for major issues throughout this pandemic, digital interventions are more desirable than ever.
In a recent interview with McKinsey & Company and CVS Caremark’s president, Alan Lotvin, Mr. Lotvin highlights their shift to in-home models and nontraditional care during the COVID-19 pandemic. One of the larger topics discussed was how patients and physicians are working to understand the risk of avoidable emergency department visits, and how they can effectively use digital tools, like telehealth and telemedicine, to run parts of the clinical practice. Additionally, the avoidance of care persists as a valid concern across healthcare systems, as people with comorbidities are at higher risk for severe COVID-19 complications.
Our Response
It shouldn’t come as a surprise that telehealth and telemedicine have come into the forefront of the digital health conversation. As Mr. Lotvin discussed, “telehealth and telemedicine are huge right now… I think most doctors have found that there are effective ways to run big parts of their practice.” The importance of telehealth and other digital interventions emphasizes the need for tools like cliexa in clinical practices. cliexa’s own virtual care solutions were significantly expanded in response to the needs of client clinics within weeks of the onset of the coronavirus pandemic, which integrates seamlessly into the other product offerings.
With industry leaders promoting the value of digital interventions, full-stack virtual health solutions continue to prove their long-term value in healthcare. Check out our latest blog as we discuss how the Access to Care in Rural Settings remains a challenge in the United States and continues to be an obstacle during the coronavirus pandemic.