NEWS Studies in a thesis indicate that an AI-supported method is effective in the diagnosis of squamous cell carcinoma of the head and neck (SCCHN). In addition, machine learning (ML, a subfield of artificial intelligence) was used to develop a model from clinically available data for prediction of recurrence in squamous cell carcinoma of the tongue (SCCOT).
The overall aims of the studies were to assess the usefulness of PET/CT (X-ray with contrast agent and images of how the agent is taken up in the body) in head and neck cancer and apply AI for predicting development of SCCOT and recurrence of SCCHN. Four studies answered the questions asked.
– Our studies offer a systematic AI method for detecting squamous cell carcinoma of the tongue, early before clinical symptoms appear, by using, among other things, interpretable machine learning, says the dissertation's author Amir Salehi, Department of Medical Biosciences.
The results suggest that people with SCCOT, regardless of diabetes status, may benefit from treatment of glucose levels, as SCCOT patients with diabetes had better prognosis than non-diabetics.
– Of course, this is just the beginning, and more research needs to be done before it can be put into clinical practice. We were surprised that diabetic patients had better relapse and survival outcomes than non-diabetics when it comes to SCCOT, says Amir Salehi.
Method: From patients suspected of having head and neck cancer between 2014–2016 results from PET/CT, pan-endoscopy with biopsy and US-FNAC were compared. Clinical, genomic, transcriptomic, and proteomic markers identifying recurrence risk were investigated. In blood samples taken from healthy individuals, data from proteins relevant to inflammation and/or tumor processes were evaluated. The SHapley Additive Explanations (SHAP) approach was used to determine the best ML-algorithm for feature selection. AdaBoost, Artificial neural networks (ANNs), Decision Tree (DT), eXtreme Gradient Boosting (XGBoost), and Support Vector Machine (SVM) were used to create prediction models. Clinical data from patients were analyzed using statistical and ML techniques.
Amir Salehi is an ENT specialist and dentist, living in Stockholm, with research interest in Head and Neck cancer. He was born in Tehran, Iran, and came as an 8-year-old with his parents to Sweden in 1979, since his father did his postgraduate degree in Sweden. Initially they were just going to stay for 2 years, but then war broke out after Iraq invaded their country, so they stayed longer and became Swedish citizens. At the moment Amir Salehi does not have a particular plan for the future – It depends on what opportunities comes up.
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Amir Salehi, Department of Medical Biosciences, defends his thesis Clinical examination and use of artificial intelligence in the diagnosis and prognosis of squamous cell carcinoma in the head and neck area June 15 at 09.00 in Betula.
