Summary:
UCLA researchers in the David Geffen School of Medicine and USC researchers in the Viterbi School of Engineering have developed a computerized diagnostic tool which can identify and rank the probability of neurological symptoms that may appear after a head trauma in childhood and adolescence solely based on patient-reported symptoms.
Background:
Head trauma occurs commonly in childhood and adolescence. Children with repeated injuries may develop serious complications. Thus, it is necessary to diagnose neurological symptoms and develop a plan for minimizing the risk of future injuries. However, accurate diagnosis requires access to costly, highly trained health care workers that are often located in larger metropolitan areas. Patients in less affluent regions suffer from poor access to accurate, affordable diagnosis. To reduce the economic burden and improve the quality of care, computer assisted diagnostic tools have been studied, but are poorly adopted due to unreliable diagnoses. There remains a need for reliable computer-assisted diagnostic tools to improve clinical assessment of neurological symptoms after a head trauma.
Innovation:
UCLA researchers in the David Geffen School of Medicine and USC researchers in the Viterbi School of Engineering have developed a computerized diagnostic tool for healthcare providers and patients with antecedent head trauma. It can provide a ranked differential diagnosis of neurological symptoms solely based on the description of the patients. A questionnaire comprised of the patient’s head trauma history is input into this computerized diagnostic tool, and is subsequently processed by the inference engine, generating a set of diagnoses that are ranked based on the likelihood and relevance. The target population of this application is limited to pediatrics and young adults. The tool could be applied in a streamlined platform for disease diagnosis with less effort and improved accuracy. The developed method has the potential to improve pediatric head trauma management via timely diagnosis and assessment of symptoms reported by the patients. In addition, this method can be easily extended to a range of other disease conditions and may be invaluable to providers seeking an evidence-based cognitive assessment tool for their physicians.
Potential Applications:
• Clinical diagnosis of child and adolescent head trauma
• Symptom prediction
• Computer-aided detection
• Preventative care
• Cognitive assistant tool
Advantages:
• Less labor-intensive
• Using only partial evidence such as input of the presenting symptoms
• Improvement on the diagnostic accuracy of computerized systems
• More accessible and affordable for patients living in poor areas
• Applicable to a wide array of disease conditions
Development to Date:
Invention has been conceived and fully described.
Related Papers (from the inventors only):
Shahram Yazdani, Carlos Lerner, Deepa Kulkarni, Audrey Kamzan, Ronald C. Henry, A new expert system with diagnostic accuracy for pediatric upper respiratory conditions, Healthcare Analytics, Volume 2, 2022, 100042, ISSN 2772-4425
Reference: UCLA Case No. 2022-243