Quantitative phase imaging, integrated with artificial intelligence, allows for the rapid and
label-free investigation of the physiology and pathology of biological systems. This review …

Recent advances in computer vision and machine learning underpin a collection of
algorithms with an impressive ability to decipher the content of images. These deep learning …

Fast and selective isolation of single cells with unique spatial and morphological traits
remains a technical challenge. Here, we address this by establishing high-speed image …

Imaging flow cytometry combines the high-event-rate nature of flow cytometry with the
advantages of single-cell image acquisition associated with microscopy. The measurement …

Drug discovery and development are among the most important translational science
activities that contribute to human health and wellbeing. However, the development of a new …

The use of artificial intelligence, and the deep-learning subtype in particular, has been
enabled by the use of labeled big data, along with markedly enhanced computing power …

Single-cell technologies have contributed to unravelling tumour heterogeneity, now
considered a hallmark of cancer and one of the main causes of tumour resistance to cancer …

These guidelines are a consensus work of a considerable number of members of the
immunology and flow cytometry community. They provide the theory and key practical …

Blood tests are considered as standard clinical procedures to screen for markers of diseases
and health conditions. However, the complex cellular background (> 99.9% RBCs) and …

The development and application of bioenergy and biofuels conversion technology can play
a significant role for the production of renewable and sustainable energy sources in the …