LDDNet: a deep learning framework for the diagnosis of infectious lung diseases. (2023)
Journal Article
PODDER, P., RANI DAS, S., MONDAL, M.R.H., BHARATI, S., MALIHA, A., HASAN, M.J. and PILTAN, F. 2023. LDDNet: a deep learning framework for the diagnosis of infectious lung diseases. Sensors [online], 23(1), article 480. Available from: https://doi.org/10.3390/s23010480

This paper proposes a new deep learning (DL) framework for the analysis of lung diseases, including COVID-19 and pneumonia, from chest CT scans and X-ray (CXR) images. This framework is termed optimized DenseNet201 for lung diseases (LDDNet). The pro... Read More about LDDNet: a deep learning framework for the diagnosis of infectious lung diseases..

Automated analysis of sleep study parameters using signal processing and artificial intelligence. (2022)
Journal Article
SOHAIB, M., GHAFFAR, A., SHIN, J., HASAN. M.J. and SULEMAN, M.T. 2022. Automated analysis of sleep study parameters using signal processing and artificial intelligence. International journal of environmental research and public health [online], 19(20), article number 13256. Available from: https://doi.org/10.3390/ijerph192013256

An automated sleep stage categorization can readily face noise-contaminated EEG recordings, just as other signal processing applications. Therefore, the denoising of the contaminated signals is inevitable to ensure a reliable analysis of the EEG sign... Read More about Automated analysis of sleep study parameters using signal processing and artificial intelligence..