By learning the relevant features of clinical images along with the relationships between them, the neural network can outperform more traditional methods.

Scientists have carried out a study investigating whether deep neural networks can represent associations between gene expression, histology, and CT-derived image features. They found that the ...

And in the case of Inception v3, it comes pre-trained for image recognition, having been fed a catalog of nearly 1.3 million images before even being asked to do anything medical.

More information: Kewal Mehta et al, Detection of COVID-19 virus using deep learning, International Journal of Computational Biology and Drug Design (2022).DOI: 10.1504/IJCBDD.2021.121619 ...

Researchers at the University of Jyväskylä Digital Health Intelligence Laboratory addressed the problem and developed an artificial neural network that creates synthetic x-ray images that can ...

In 2017, Stanford computer scientists reported their successes with a computer vision tool that utilizes artificial intelligence to diagnose skin abnormalities, an early potential indicator of skin ...

Healthcare and Medical Imaging In the medical field, CNNs have improcws diagnostic processes by: Analyzing radiological images to detect anomalies Identifying potential cancerous tissues in ...

Neural networks made of light Date: July 12, 2024 Source: Max Planck Institute for the Science of Light Summary: Scientists propose a new way of implementing a neural network with an optical ...