A computerized method quickly diagnoses malaria read more at here www.spinonews.com/index.php/item/905-a-computerized-method-quickly-diagnoses-malaria

Duke researchers have devised a computerized method to autonomously and quickly diagnose malaria with clinical relevant accuracy.

Engineers report a method that uses computer deep learning and light-based, holographic scans to spot malaria-infected cells from a simple, untouched blood sample without any help from a human.

The innovation could form the basis of a fast, reliable test that could be given by most anyone, anywhere in the field, which would be invaluable in the $2.7 billion-per-year global fight against the disease.

"With this technique, the path is there to be able to process thousands of cells per minute," said Adam Wax, professor of biomedical engineering at Duke.

This technique is based on a technology called quantitative phase spectroscopy. As a laser sweep through the visible spectrum of light, the sensors capture how each discrete light frequency interacts with a sample of blood. The resulting data captures a holographic image that provides a wide array of valuable information that can indicate a malarial infection.

"We identified 23 parameters that are statistically significant for spotting malaria," said Han Sang Park, a doctoral student in Wax's laboratory.

To get a more accurate reading, researchers learning a method by which computers teach themselves how to distinguish between different objects. By feeding data on more than 1,000 healthy and diseased cells into a computer, the deep learning program determined which sets of measurements at which thresholds most clearly distinguished healthy from diseased cells.

When they put the resulting algorithm to the test with hundreds of cells, it was able to correctly spot malaria 97 to 100 percent of the time a number the researchers believe will increase as more cells are used to train the program.