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Success Case


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Improving rib fracture detecting rate and enable physicians to provide more holistic treatment plans to patient


Missing a fracture in a radiograph often has severe consequences for patients, resulting in delayed treatment and poor recovery of function. In order to help emergency medicine clinicans reduce misdiagnosis, Y Hospital in the northern Taiwan has developed an AI model for detecting rib fractures.

Detecting rib fractures through X-ray examinations poses considerable challenges, with an average detection rate of only about 40-50%. In many cases, physicians have had to resort to additional procedures, such as CT scans, to identify missed fractures. Unfortunately, the lengthy wait times for imaging reports often lead to delayed treatment.

Empowered by our cutting-edge DeepQ AI platform, Y Hospital in the northern Taiwan has developed an AI model for detecting rib fractures. Through seamless integration with the hospital's internal information system using the DeepQ Deeploy deployment module, this AI model has recently been introduced in the emergency department to help doctors detect rib fracture.

The success of Y Hospital's rib fracture AI detection model extends far beyond the emergency department. Routine X-ray images from other departments are also processed through this AI model, equipping physicians with comprehensive insights into each patient's condition and enabling more holistic treatment plans. For example, an elderly patient presenting with stroke symptoms in the internal medicine department. The physician followed the standard protocol, performing a chest X-ray to rule out additional complications. Simultaneously, the rib fracture AI detection model promptly flagged a fracture in the fifth rib upon analyzing the uploaded image. Subsequent confirmation through a CT scan solidified the diagnosis, ultimately revealing a previously unknown history of a fall at home that had caused the rib fracture.

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