<?xml version="1.0" encoding="UTF-8"?><oembed><type>video</type><version>1.0</version><html>&lt;iframe src=&quot;https://www.loom.com/embed/396bc5847f0f48058c06768e60356ea5&quot; frameborder=&quot;0&quot; width=&quot;1998&quot; height=&quot;1498&quot; webkitallowfullscreen mozallowfullscreen allowfullscreen&gt;&lt;/iframe&gt;</html><height>1498</height><width>1998</width><provider_name>Loom</provider_name><provider_url>https://www.loom.com</provider_url><thumbnail_height>1498</thumbnail_height><thumbnail_width>1998</thumbnail_width><thumbnail_url>https://cdn.loom.com/sessions/thumbnails/396bc5847f0f48058c06768e60356ea5-15da3ad0f9055ae9.gif</thumbnail_url><duration>506.204</duration><title>Leveraging AI for Clinical Reasoning in Shoulder Assessment</title><description>In this video, I share my experience of developing a custom GPT model focused on shoulder physiotherapy, leveraging a robust diagnostic protocol from the British Elbow Shoulder Society. Having spent three and a half years as a physio in the UK, I emphasize the importance of ruling out red flags and understanding patient history to ensure proper assessment. I demonstrate how AI can assist in clinical reasoning by following algorithmic assessments, which can be particularly beneficial for young therapists struggling with shoulder diagnoses. I encourage viewers to consider how this technology can enhance their practice and improve patient outcomes. Please let me know your thoughts on this approach and how it might fit into your clinical practice.</description></oembed>