This paper provides a comprehensive state-of-the-art investigation of the recent advances in
data science in emerging economic applications. The analysis is performed on the novel …

Chemical imaging, especially mid-infrared spectroscopic microscopy, enables label-free
biomedical analyses while achieving expansive molecular sensitivity. However, its slow …

Hyperspectral imaging is a technique that provides rich chemical or compositional
information not regularly available to traditional imaging modalities such as intensity …

Software is increasingly vital, with automated systems regulating critical functions. As
development demands grow, manual code review becomes more challenging, often making …

Due to the high classification accuracy and fast computational speed offered by Deep
Neural Networks (DNNs), they have been widely used for the design and development of …

The use of infrared spectroscopy to augment decision-making in histopathology is a
promising direction for the diagnosis of many disease types. Hyperspectral images of …

Application of deep learning (DL) to the field of healthcare is aiding clinicians to make an
accurate diagnosis. DL provides reliable results for image processing and sensor …

Featured Application Quantitative characterization of intratumor heterogeneity using medical
imaging is valuable for guiding theranostic technology in inductive moderate hyperthermia …

Uncertainty quantification in deep learning models is especially important for the medical
applications of this complex and successful type of neural architectures. One popular …

In contemporary medical research, respiratory disorders have become a primary focus.
Improving patient outcomes for any medical condition largely depends on early identification …