Imaging techniques are used to capture anomalies of the human body. The captured images
must be understood for diagnosis, prognosis and treatment planning of the anomalies …

Convolutional neural networks (CNN) are widely used in computer vision and medical
image analysis as the state-of-the-art technique. In CNN, pooling layers are included mainly …

Artificial intelligence (AI) tools are increasingly being applied in drug discovery. While some
protagonists point to vast opportunities potentially offered by such tools, others remain …

Histopathological images contain rich phenotypic information that can be used to monitor
underlying mechanisms contributing to disease progression and patient survival outcomes …

Deep learning algorithms, in particular convolutional networks, have rapidly become a
methodology of choice for analyzing medical images. This paper reviews the major deep …

Microglia are the brain's immunocompetent macrophages with a unique feature that allows
surveillance of the surrounding microenvironment and subsequent reactions to tissue …

Computerized microscopy image analysis plays an important role in computer aided
diagnosis and prognosis. Machine learning techniques have powered many aspects of …

Fruit classification is an important task in many industrial applications. A fruit classification
system may be used to help a supermarket cashier identify the fruit species and prices. It …

Automation-assisted cervical screening via Pap smear or liquid-based cytology (LBC) is a
highly effective cell imaging based cancer detection tool, where cells are partitioned into …

The diagnosis of blood-related diseases involves the identification and characterization of a
patient's blood sample. As such, automated methods for detecting and classifying the types …