Machine Learning Predicts Laboratory Earthquakes
Sign Up to like & getrecommendations! Published in 2017 at "Geophysical Research Letters"
DOI: 10.1002/2017gl074677
Abstract: We apply machine learning to data sets from shear laboratory experiments, with the goal of identifying hidden signals that precede earthquakes. Here we show that by listening to the acoustic signal emitted by a laboratory… read more here.
Keywords: machine; fault; machine learning; learning predicts ... See more keywords
Machine Learning Predicts Degree of Aromaticity from Structural Fingerprints
Sign Up to like & getrecommendations! Published in 2020 at "Journal of chemical information and modeling"
DOI: 10.1021/acs.jcim.0c00483
Abstract: Prediction of whether a compound is 'aromatic' is at first glance a relatively simple task - does it obey Hückel's rule (planar cyclic π-system with 4n+2 electrons) or not? However, aromaticity is far from a… read more here.
Keywords: learning predicts; predicts degree; machine learning; degree aromaticity ... See more keywords
Unsupervised learning predicts human perception and misperception of gloss.
Sign Up to like & getrecommendations! Published in 2021 at "Nature human behaviour"
DOI: 10.1038/s41562-021-01097-6
Abstract: Reflectance, lighting and geometry combine in complex ways to create images. How do we disentangle these to perceive individual properties, such as surface glossiness? We suggest that brains disentangle properties by learning to model statistical… read more here.
Keywords: unsupervised learning; perception; learning predicts; predicts human ... See more keywords
Deep learning predicts postsurgical recurrence of hepatocellular carcinoma from digital histopathologic images
Sign Up to like & getrecommendations! Published in 2021 at "Scientific Reports"
DOI: 10.1038/s41598-021-81506-y
Abstract: Recurrence risk stratification of patients undergoing primary surgical resection for hepatocellular carcinoma (HCC) is an area of active investigation, and several staging systems have been proposed to optimize treatment strategies. However, as many as 70%… read more here.
Keywords: hepatocellular carcinoma; risk; recurrence; learning predicts ... See more keywords
Machine learning predicts response to TNF inhibitors in rheumatoid arthritis: results on the ESPOIR and ABIRISK cohorts
Sign Up to like & getrecommendations! Published in 2022 at "RMD Open"
DOI: 10.1136/rmdopen-2022-002442
Abstract: Objectives Around 30% of patients with rheumatoid arthritis (RA) do not respond to tumour necrosis factor inhibitors (TNFi). We aimed to predict patient response to TNFi using machine learning on simple clinical and biological data.… read more here.
Keywords: confidence; machine learning; rheumatoid arthritis; response ... See more keywords