Results 101 to 110 of about 8,972,433 (325)
Exploration of heterogeneity and recurrence signatures in hepatocellular carcinoma
Molecular Oncology, EarlyView.This study leveraged public datasets and integrative bioinformatic analysis to dissect malignant cell heterogeneity between relapsed and primary HCC, focusing on intercellular communication, differentiation status, metabolic activity, and transcriptomic profiles.
Wen‐Jing Wu +15 more
wiley +1 more source
, 2020 Talk at the 3rd NOAA Workshop on leveraging AI in Environmental Sciences;
openaire +4 more sources
SoilGrids250m: Global gridded soil information based on machine learning
PLoS ONE, 2017 This paper describes the technical development and accuracy assessment of the most recent and improved version of the SoilGrids system at 250m resolution (June 2016 update).
T. Hengl +18 more
semanticscholar +1 more source
Molecular Oncology, EarlyView.Integrating ancestry, differential methylation analysis, and machine learning, we identified robust epigenetic signature genes (ESGs) and Core‐ESGs in Black and White women with endometrial cancer. Core‐ESGs (namely APOBEC1 and PLEKHG5) methylation levels were significantly associated with survival, with tumors from high African ancestry (THA) showing ...
Huma Asif, J. Julie Kim
wiley +1 more source
Investigating Machine Learning Techniques for Gesture Recognition with Low-Cost Capacitive Sensing Arrays [PDF]
, 2020 Machine learning has proven to be an effective tool for forming models to make predictions based on sample data. Supervised learning, a subset of machine learning, can be used to map input data to output labels based on pre-existing paired data. Datasets
Fahr Jr., Michael
core +2 more sources
Machine learning for neuroscience [PDF]
Neural Systems & Circuits, 2011 What is machine learning? Machine learning is a type of statistics that places particular emphasis on the use of advanced computational algorithms. As computers become more powerful, and modern experimental methods in areas such as imaging generate vast bodies of data, machine learning is becoming ever more important for extracting reliable and ...
openaire +4 more sources
Molecular Oncology, EarlyView.This article advocates integrating temporal dynamics into cancer research. Rather than relying on static snapshots, researchers should increasingly consider adopting dynamic methods—such as live imaging, temporal omics, and liquid biopsies—to track how tumors evolve over time.
Gautier Follain +3 more
wiley +1 more source
The Journal of Physical Chemistry Letters, 2018 William F. Schneider, Hua Guo
openaire +7 more sources
Lecture Notes: Optimization for Machine Learning [PDF]
arXiv, 2019 Lecture notes on optimization for machine learning, derived from a course at Princeton University and tutorials given in MLSS, Buenos Aires, as well as Simons Foundation, Berkeley.
arxiv
Knowledge representation issues in control knowledge learning [PDF]
, 2000 Seventeenth International Conference on Machine Learning. Stanford, CA, USA, 29 June-2 July, 2000Knowledge representation is a key issue for any machine learning task.
Aler, Ricardo +2 more
core +2 more sources