5 Key Takeaways

• 1

  A handheld Raman spectroscopy system combined with machine learning to classify normal skin, basal cell carcinoma, and squamous cell carcinoma in a preliminary study.

• 2

  The researchers analyzed almost 1,000 spectra from more than 50 removed tissue samples using a mobile system with a 785-nm laser.

• 3

  K-nearest neighbors and support vector machine models achieved the highest overall accuracy, at approximately 84%.

• 4

  A shallow neural network achieved 80.8% accuracy and the highest area under the receiver operating characteristic curve, at 0.910.

• 5

  Testing involved removed tissue rather than patients, and the study’s performance remained below the researchers’ stated clinical-use targets of more than 90%.