Research into the potential benefits of artificial intelligence for comprehending the intricate
biology of cancer has grown as a result of the widespread use of deep learning and …

The quantification of gases in breath has gained significant attention as a modern diagnosis
method due to its non-invasive nature, and as a painless and straightforward method for the …

Abstract Niemann–Pick Class 1 (NPC1) disease is a rare and debilitating
neurodegenerative lysosomal storage disease (LSD). Metabolomics datasets of NPC1 …

Breast cancer is a leading cause of mortality among women. The patient's survival rate is
uncertain due to the limitations in the accuracy of diagnosis and effective monitoring during …

For certain diseases, the continuous long-term monitoring of the physiological condition is
crucial. Therefore, non-invasive monitoring methods have attracted widespread attention in …

Breast cancer is a dreaded disease affecting women the most in cancer-related deaths over
other cancers. However, early diagnosis of the disease can help increase survival rates. The …

Recently, the development of learning-based algorithms has shown a crucial role to extract
features of vital importance from multi-spectral photoacoustic imaging. In particular …

The current study reports an integrated approach of machine learning and tryptophan
fluorescence and photoacoustic spectral properties to assess the mitochondrial status under …

Significance Collagen and lipid are important components of tumor microenvironments
(TME) and participates in tumor development and invasion. It has been reported that …

Depending on the relative numbers and spatial arrangement of Tryptophan (Trp; W) and
Tyrosine (Tyr; Y) residues, different proteins produce distinct autofluorescence (AF) spectral …