Rapid identification of breast cancer subtypes using micro-FTIR and machine learning methods.

Breast cancer (BC) molecular subtypes diagnosis involves improving clinical uptake by Fourier transform infrared (FTIR) spectroscopic imaging, which is a non-destructive and powerful technique, enabling label free extraction of biochemical information towards prognostic stratification and evaluation of cell functionality. However, methods of measurements of samples demand a long time to achieve high quality images, making its clinical use impractical because of the data acquisition speed, poor signal to noise ratio, and deficiency of optimized computational framework procedures. To address those challenges, machine learning (ML) tools can facilitate obtaining an accurate classification of BC subtypes with high actionability and accuracy.

Multimodal evaluation of ultra-short laser pulses treatment for skin burn injuries.

Thousands of people die every year from burn injuries. The aim of this study is to evaluate the feasibility of high intensity femtosecond lasers as an auxiliary treatment of skin burns. We used an animal model and monitored the healing process using 4 different imaging modalities: histology, Optical Coherence Tomography (OCT), Second Harmonic Generation (SHG), and Fourier Transform Infrared (FTIR) spectroscopy.