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A retrospective study on machine learning assisted stroke recognition for medical helpline calls

 min read
A retrospective study on machine learning assisted stroke recognition for medical helpline calls

New York, NY – December 21, 2023

Corti, the AI-based healthtech startup that recently raised $60M in series B funding, proudly announces its involvement in a landmark study published in Nature this month demonstrating the significant impact of AI in advancing stroke recognition during emergency dispatch calls. The study, conducted in collaboration with leading neurologists, data scientists, and emergency medical experts, showcases the potential of AI and machine learning in enhancing the accuracy and efficiency of stroke diagnosis, a vital factor in the timely and effective treatment of this highly impactful condition.

Link to Nature article.

Stroke, a leading cause of death and disability, presents a formidable challenge in healthcare, especially in the critical prehospital phase, which is projected to incur an annual cost of $240 billion by 2030 according to the American Heart Association. With about half of stroke patients not receiving correct initial assessments, the need for improved triage processes is imperative. Corti's AI-driven decision support tool addresses this gap, offering a revolutionary approach to stroke symptom recognition. The American Heart Association projects that 4% of US adults will suffer from a stroke by 2030.

Corti's AI framework, by analyzing speech and language patterns in emergency calls, significantly outperforms human call-takers in sensitivity and predictive accuracy. This advancement not only bolsters the call-taker's ability to triage effectively but also ensures a faster and more precise emergency response, potentially saving crucial treatment time and improving patient outcomes.

The collaboration for this study involved overcoming challenges in data matching and interdisciplinary coordination. Utilizing Denmark's comprehensive stroke patient registries, the team developed a machine learning framework that showed an improved ability to recognize stroke calls, achieving higher sensitivity and precision compared to human operators. The findings featured in Nature aim to make these technical results accessible to clinicians and decision-makers, highlighting the framework as a supportive tool rather than a replacement for human judgment.

This peer-reviewed study, following Dr. Blomberg's pivotal 2020 dissertation on machine learning in cardiac arrest emergency calls, demonstrates the superiority of Corti's framework over traditional methods in identifying stroke cases. The research, conducted in Scandinavia's technologically advanced and equitable healthcare environment, leverages the region's digital infrastructure and commitment to healthcare innovation, making it an ideal setting for this groundbreaking work.

The success of this framework in stroke recognition exemplifies the power of interdisciplinary collaboration. By combining the expertise of neurologists, data scientists, machine learning specialists, and emergency medical professionals, the team has created a system that significantly enhances the quality of prehospital care. This endeavor represents not just the fusion of medical knowledge with cutting-edge technology, but also a shared commitment to advancing care delivery and saving lives. Corti's involvement in this study underscores its role as a frontrunner in healthcare technology innovation, particularly in the realm of AI and machine learning. The company remains dedicated to leveraging technology to improve patient outcomes and streamline healthcare processes, setting a new standard in the industry as it broadly and rapidly evolves to incorporate AI innovation.

About Corti

Corti is a leading healthcare technology company specializing in AI-enabled decision support tools for healthcare providers. With a focus on innovation and excellence, Corti is committed to developing solutions that enhance patient care and improve healthcare efficiency.