The Thermography studies – we are Developing Clinical Intelligence based on evidence using thermography.

STUDY START April 2021

Termografi

 

After surgery, patient and surgeon wish to avoid ONE thing

– INFECTION in the surgical wound.

 

The Thermography studies will investigate how we can detect and monitor early signs of infection, before the patient develop symptoms and how we use the discipline of thermography evidence based in clinical practice. The aim is to improve postsurgical care for patients and avoid complications to surgery.

 

It might even be possible to monitor patients outside the hospital by small thermographic cameras that your ad on to a mobile phone. If thermography can be used as an adjunct tool to improve surveillance from the patient's home setting, then we can minimize follow up visits in the outpatient clinic and avoid unnecessary time and resource consumption for both the patient and in the healthcare system.

 

This project will generate a huge amount of precise data, a unique and well-suited base to work with machine learning and AI solutions. The political tendency is that health data will be used to develop AI solutions in healthcare – maybe not in an evidence and rational way though - we clinicians need to devote ourselves in this innovative process and keep focus on a clinical intelligent way of learning and secure an evidence-based introduction of AI into clinical practice.

 

The setup is multidisciplinary international cross-sectional studies. The Thermography studies will focus on orthopedic patients with external frames. These patients are in considerable risk of infection during treatment period of several months, and an infection can in worst case scenario be limb threatening. The experience and knowledge will we obtain from this project can be used in general to improve care for patients after surgery in the future.

 

The Thermography studies is a part of the clinical intelligence project – a new innovative solution to care for post-surgical patients with new technology equipment and evidence based use of AI In health care.

 

Read more about the PhD project