Scientists at IASST develop a 98.02% accurate cervical dysplasia diagnosis model using NSCT and YCbCr color model.

Scientists at IASST have developed a new computational model that significantly enhances the diagnosis of cervical dysplasia, a precursor to cervical cancer. The model, using Non-subsampled Contourlet Transform (NSCT) and the YCbCr color model, achieved an average accuracy rate of 98.02%. This breakthrough could revolutionize early cervical cancer detection, providing healthcare professionals with highly accurate diagnostic tools.