A Deep Learning Algorithm for Locating Contaminant Plumes From Self-Potential: A Laboratory Perspective Abstract: Leachate leakages from municipal landfills are significant environmental problems that ...

Here, we report on the Pancreatic tumour Metastasis Prediction Deep-learning (PMPD) algorithm, a DL-based fusion model designed to predict the presence of distant metastasis from CECT images of ...

A new machine learning approach tries to better emulate the human brain, in hopes of creating more capable agentic AI.

Gulshan, V., Peng, L., Coram, M., Stumpe, M.C., Wu, D., Narayanaswamy, A., et al. (2016) Development and Validation of a Deep Learning Algorithm for Detection of ...

Deep learning algorithm used to pinpoint potential disease-causing variants in non-coding regions of the human genome The methods help identify 'footprints' that indicate binding sites and reveal ...

This consists of 15 biochemical tests, including serum phosphate. Our aim was to understand if abnormalities in serum phosphate could be predicted, using a machine learning algorithm (MLA) by other ...

What it takes to get useful health data from your smartwatch Training an algorithm is an essential part of translating our bodies’ signals into early diagnoses.

Thanks to a pre-trained deep learning algorithm, it can detect whether that specific sample contains any bacteria or pathogens.

Scientists have developed a geometric deep learning method that can create a coherent picture of neuronal population activity during cognitive and motor tasks across experimental subjects and ...

A geometric neural net for dynamic data Traditional deep learning is not suited to understanding dynamic systems that change regularly as a function of time, like firing neurons or flowing fluids.