With the growing prevalence of sports and traffic accidents, concussions have emerged as a significant public health issue. Statistics indicate that approximately 500,000 individuals in Taiwan suffer concussions annually due to head injuries. Symptoms of concussion are diverse, encompassing sensory, emotional, cognitive, and sleep-related disturbances. About one-third of patients may develop persistent post-concussion syndrome, underscoring the importance of accurate acute-phase assessment. However, the current lack of adequate imaging diagnostic tools has kept treatment primarily focused on passive support, limiting advancements in concussion therapy.
DeepBrain-Concussion System: A Future of Precision Prediction and Personalized Treatment
Addressing this challenge, the research team led by Distinguished Professor Cheng-Yu Chen at Taipei Medical University Hospital has developed the "DeepBrain-Concussion" system. By analyzing functional MRI (fMRI) data from patients during the acute phase, the system examines the cooperative patterns between the thalamus and cerebral cortex. It predicts symptom types and severity, estimates the duration of post-concussion symptoms, and suggests precise interventions to enable early intervention and reduce the risk of persistent post-concussion syndrome.
Unlike traditional concussion diagnostic methods that rely on single biomarkers or imaging results, this technology integrates diverse data and machine learning for a comprehensive evaluation. This approach delivers more accurate predictions and provides clinicians with practical treatment decision support. Moreover, the system automatically generates personalized treatment reports, significantly enhancing the efficiency and accuracy of medical decision-making. Beyond concussion prediction and treatment, this technology also offers robust data support for new drug development and functional therapy research.
From Research to Clinical Application: Professor Cheng-Yu Chen on the Future of AI in Concussion Treatment
Professor Cheng-Yu Chen emphasized that the goal of his team is to leverage this AI technology to provide early and precise diagnostic and treatment recommendations for concussion patients, facilitating quicker recovery and reducing long-term impacts. He noted that the development of this technology, spanning from animal studies to clinical trials, has been published in high-impact international journals. The success lies in incorporating multiple factors of concussion symptoms into predictive models and achieving seamless integration with various medical imaging tools and devices through efficient data processing and analysis, offering clinicians unprecedented diagnostic and treatment support.
Professor Chen highlighted plans to conduct further clinical trials at two medical centers. He also revealed ambitions to extend the system's application beyond Taiwan, aiming to introduce it to the U.S. market, particularly for high-value applications in American football and veterans with post-traumatic stress disorder (PTSD).
As AI technology advances, early diagnosis and treatment of concussions will no longer pose a challenge. The implementation of this technology heralds greater possibilities in precision medicine. The DeepBrain-Concussion system is poised to become a breakthrough tool in concussion diagnosis and treatment, significantly improving diagnostic accuracy and providing refined support for personalized treatment. It signals a future where concussion therapy becomes increasingly intelligent and precise.
Resource: 化被動為主動 腦震盪急性期AI出招精準治療
