Diagnosing Ovarian Cancer Using Perception-based Nanosensors and Machine Learning

Two studies show the accuracy of perception-based systems in detecting disease biomarkers without needing molecular recognition elements, such as antibodies Researchers from multiple academic and research institutions have collaborated to develop a non-conventional machine learning-based technology for identifying and measuring biomarkers to detect ovarian cancer without the need for molecular identification elements, such as antibodies. Traditional clinical laboratory methods for detecting...

UCF Researchers Develop an Optical Sensor That Identifies Viruses in Blood Samples in Seconds with 95% Accuracy

New nanotechnology device is significantly faster than typical rapid detection clinical laboratory tests and can be manufactured to identify not just COVID-19 at point of care, but other viruses as well Researchers at the University of Central Florida (UCF) announced the development of an optical sensor that uses nanotechnology to identify viruses in blood samples in seconds with an impressive 95% accuracy. This breakthrough underscores the value of continued research into technologies that...
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