Welcome to the reveal of the HTN AI and Data Awards! We’re delighted to announce our winning entries across four competitive categories covering the use of AI and data in diagnosis, treatment, communication, system efficiency, and more.
Before we start, we’d like to take this opportunity to congratulate and thank all of our entrants on their incredible hard work and dedication to health and care. We’ve had a great time reading about your innovations, solutions, and approaches making a real impact in this space.
Best use of AI for diagnosis, treatment and patient care
Winner: Sanius Health
Well done to our worthy winners Sanius Health, with their AI-driven approach to rare disease diagnosis utilising machine learning and advanced analytics to identify at-risk patients early, and enable timely, personalised care. In Primary Biliary Cholangitis (PBC), Sanius Health’s AI-powered approach tracked key datapoints and biomarkers over time to evaluate the entire patient cohort for risk stratification. This was also used to assess effectiveness and patient response to specific therapies, identifying 76 percent of patients with an inadequate response to a specific therapy to ensure timely and personalised treatment plan adjustment.
We’d also like to congratulate West London NHS Trust/Healthy io, as our highly commended entry, for their work on the implementation of the Minuteful for Wound AI digital wound management solution, enabling the standardised measurement and documentation of wounds and monitoring over time.
To learn more, and to browse all of our entries in this category, please click here.
Best use of AI for promotion, communication and prevention
Winner: VirtTuri
Congratulations to VirtTuri for their winning entry in this category, celebrating work with the NHS, pharmaceutical companies, and medical charities to deliver clinically compliant AI avatars that enhance patient engagement, recall, and understanding. VirtTuri AI technology was first deployed to improve patient engagement and awareness of Infacol. Successes of that deployment include 250,000+ interactions, 24/7 user access to vital product information, and a 95 percent reduction in pharmacovigilance management costs.
A huge well done to our highly commended entry, PharmaTools.AI, for their innovative mobile app that transforms complex medical notes into clear, actionable insights. Designed for patients, caregivers, and healthcare professionals, it enhances health literacy by tailoring information to various audiences, styles, and languages.
To learn more, and to browse all of our entries in this category, please click here.
Best use of AI and Data for system efficiency
Winner: Lilli
Lilli’s home monitoring technology providing care teams with AI-driven insights generating efficiencies across health and care is our worthy winner in this category. By using Lilli, carers can: generate additional carer hours through right-sizing support; spot health decline early to enable early intervention; accelerate waiting lists for care assessments & discharge times from hospital. The technology helps people live safely and independently at home for longer, generating significant efficiencies across both the health and social care systems.
We’d also like to congratulate our highly commended entry in this category, X-on Health, whose Surgery Assist AI tool and AOS helped Tudor Lodge Health Centre optimise its telephony, resulting in 50 percent reduced call waiting times and a 65 percent reduction in missed calls.
To learn more, and to browse all of our entries in this category, please click here.
AI Solution of the Year
Winner: AILIS
Well done to AILIS, our winner in this category, whose integrated breast health monitoring system combines AI with Deep Neural Networks (DNN), Parametric Dynamic Imaging and telemedicine. The system performs a breast examination in just 4 minutes, with results provided in-app after 10 minutes, meaning the whole procedure takes about 15 minutes total. To date, nearly 1,500 ladies both healthy and with suspected cancer (BI-RADS 4b, 4c) have already been examined with the AILIS device.
And congratulations to Medtronic for their highly commended entry, the AccuRhythm AI platform, applying deep learning algorithms to LINQ II insertable cardiac monitor (ICM) data flowing into the CareLink™ network, reducing false diagnostic alerts by 97.4 percent for pause episodes and 88.2 percent in Atrial fibrillation alerts.
To learn more, and to browse all of our entries in this category, please click here.
That’s a wrap!
And with that, the HTN AI and Data Awards come to an end. We’d like to offer one final congratulations to our winners, our highly commended entries, and every single one of our finalists.
You can read more about each category and the entries here.
