Deep neural networks are at the heart of artificial intelligence, ranging from pattern recognition to large language and ...

In order to produce effective targeted therapies for cancer, scientists need to isolate the genetic and phenotypic ...

Scientists at ETH Zurich have broken new ground by generating over 400 types of nerve cells from stem cells in the lab, far ...

Herein, we explore the potential of a deep learning model to automatically distinguish abnormal cells from normal cells. The ThinPrep cytologic test dataset was collected from the fourth central ...

A deep convolutional neural network, Mask R-CNN, is used to detect and segment stain-free adherent cells, leading to a considerable increase in operational efficiency and subsequent throughput. In the ...

Compared to a previous deep learning AI method, Mizzou's tool is more than twice as accurate when analyzing human single-cell data.

Protein structure prediction (PSP) is a vital challenge in bioinformatics, structural biology and drug discovery. Protein secondary structure (SS) prediction is critical since three-dimensional (3D) ...

In this study, we demonstrate a modular deep learning system, DeepCAN, providing a complete solution for automated cell counting and viability analysis. DeepCAN employs three different neural network ...