Introduction Morphological assessment of the blood smear has been performed by
conventional manual microscopy for many decades. Recently, rapid progress in digital …

The future of clinical diagnosis and treatment of hematologic diseases will inevitably involve
the integration of artificial intelligence (AI)-based systems into routine practice to support the …

This article makes available a dataset that was used for the development of an automatic
recognition system of peripheral blood cell images using convolutional neural networks [1] …

Background and objectives Morphological analysis is the starting point for the diagnostic
approach of more than 80% of hematological diseases. However, the morphological …

Microscopic examination of peripheral blood plays an important role in the field of diagnosis
and control of major diseases. Peripheral leukocyte recognition by manual requires medical …

Background and objectives Morphological differentiation among blasts circulating in blood
in acute leukaemia is challenging. Artificial intelligence decision support systems hold …

Artificial intelligence (AI) is about to make itself indispensable in the health care sector.
Examples of successful applications or promising approaches range from the application of …

Abstract Machine learning (ML) offers opportunities to advance pathological diagnosis,
especially with increasing trends in digitalizing microscopic images. Diagnosing leukemia is …

Introduction This review focuses on how image processing and machine learning can be
useful for the morphological characterization and automatic recognition of cell images …

The future of the wind energy industry passes through the use of larger and more flexible
wind turbines in remote locations, which are increasingly offshore to benefit stronger and …