Artificial Intelligence Microscope Helps Find Cancer Cells Using Photonic Time Stretch and Deep Learning
Adam Rifkin stashed this in Machine Learning
AI Medicine keeps advancing.
A microscope, invented by a professor at the University of California, uses artificial intelligence in order to locate cancer cells more efficiently than ever before. The device uses photonic time stretch and deep learning to analyze 36 million images every second without damaging the blood samples. This new technique for identifying problematic cells is faster and more accurate than standard methods currently in practice.
Commonly, doctors will add biochemicals to blood samples in order to check for cells containing cancer. The biochemicals attach what scientists call “biological labels” to damaged cells, which enables instruments to both locate and identify differences. These tests have proven problematic, as the biochemicals used would often damage cells, making them unusable for future testing. Other techniques currently in practice do not label cells, but identify cancer cells based on physical characteristics that can oftentimes falsely identify regular cells as damaged.