Asmaa Shati

Asmaa Shati is a researcher at the School of Physics, Mathematics and Computing, King Khalid University, with a focus on applying computer science and artificial intelligence to medical diagnostics. Her work bridges disciplines such as machine learning, image analysis, and public health through innovative research in disease prediction.

Her research output centers on developing advanced algorithms for medical imaging analysis. Using techniques like residual networks, DenseNet, and texture descriptors, she contributes to improving detection systems for pneumonia, tuberculosis, and COVID-19 based on cough audio signals.

Shati's publications demonstrate expertise in computer science and biomedical engineering, with a strong emphasis on practical applications in healthcare. Her work leverages methods such as GLCM, wavelet transforms, and k-NN to enhance diagnostic accuracy.