Abstract
BackgroundArtificial intelligence (AI) is one of the most promising areas in medicine with many possibilities for improving health and wellness. Already today, diagnostic decision support systems may help patients to estimate the severity of their complaints. This fictional case study aimed to test the diagnostic potential of an AI algorithm for common sports injuries and pathologies.MethodsBased on a literature review and clinical expert experience, five fictional “common” cases of acute, and subacute injuries or chronic sport-related pathologies were created: Concussion, ankle sprain, muscle pain, chronic knee instability (after ACL rupture) and tennis elbow. The symptoms of these cases were entered into a freely available chatbot-guided AI app and its diagnoses were compared to the pre-defined injuries and pathologies.ResultsA mean of 25–36 questions were asked by the app per patient, with optional explanations of certain questions or illustrative photos on demand. It was stressed, that the symptom analysis would not replace a doctor’s consultation. A 23-yr-old male patient case with a mild concussion was correctly diagnosed. An ankle sprain of a 27-yr-old female without ligament or bony lesions was also detected and an ER visit was suggested. Muscle pain in the thigh of a 19-yr-old male was correctly diagnosed. In the case of a 26-yr-old male with chronic ACL instability, the algorithm did not sufficiently cover the chronic aspect of the pathology, but the given recommendation of seeing a doctor would have helped the patient. Finally, the condition of the chronic epicondylitis in a 41-yr-old male was correctly detected.ConclusionsAll chosen injuries and pathologies were either correctly diagnosed or at least tagged with the right advice of when it is urgent for seeking a medical specialist. However, the quality of AI-based results could presumably depend on the data-driven experience of these programs as well as on the understanding of their users. Further studies should compare existing AI programs and their diagnostic accuracy for medical injuries and pathologies.
Highlights
Artificial intelligence (AI) is one of the most promising areas in medicine with many possibilities for improving health and wellness
Data has already shown that such a diagnostic decision support system (DDSS) can help patients to estimate the severity of their complaints and can be useful to support medical personnel [12, 13]
To establish an initial impression of the potential of a DDSS, 5 different fictional sport injuries and pathologies were analyzed with an AI chatbot app in this case report
Summary
Artificial intelligence (AI) is one of the most promising areas in medicine with many possibilities for improving health and wellness. Diagnostic decision support systems may help patients to estimate the severity of their complaints This fictional case study aimed to test the diagnostic potential of an AI algorithm for common sports injuries and pathologies. The current age of digital health offers a wide range of possibilities for improving medical care Various technologies, such as telemedicine with video consultation or mobile health (mHealth) applications can already be considered established [1, 2], and the potentials of Rigamonti et al BMC Sports Science, Medicine and Rehabilitation (2021) 13:13 achieving similar or even superior results when compared to humans [7, 8].
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