Summary
Surgical Site Infections (SSIs) can have subtle, early signs that are not readily identifiable. This study aimed to develop a machine learning algorithm that could identify early SSIs based on thermal images. Images were taken of surgical incisions on 193 patients who underwent a variety of surgical procedures, but only five of these patients developed SSIs, which limited testing of the models developed. However, the authors were able to generate two models to successfully segment wounds. This proof-of-concept demonstrates that computer vision has the potential to support future surgical applications.
The use of mobile thermal imaging and machine learning technology for the detection of early Surgical Site Infections (2 May 2023)
https://www.americanjournalofsurgery.com/article/S0002-9610(23)00157-5/abstract#%20
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