AIMC Topic: Unsupervised Machine Learning

Clear Filters Showing 281 to 290 of 797 articles

Unsupervised machine learning identifies predictive progression markers of IPF.

European radiology Sep 6, 2022
OBJECTIVES: To identify and evaluate predictive lung imaging markers and their pathways of change during progression of idiopathic pulmonary fibrosis (IPF) from sequential data of an IPF cohort. To test if these imaging markers predict outcome.
Humans Tomography, X-Ray Computed Idiopathic Pulmonary Fibrosis Unsupervised Machine Learning Disease Progression Lung
View on PubMed DOI

ULMR: An Unsupervised Learning Framework for Mismatch Removal.

Sensors (Basel, Switzerland) Aug 16, 2022
Due to radiometric and geometric distortions between images, mismatches are inevitable. Thus, a mismatch removal process is required for improving matching accuracy. Although deep learning methods have been proved to outperform handcraft methods in s...
Unsupervised Machine Learning
View on PubMed DOI

Predicting the oxidation states of Mn ions in the oxygen-evolving complex of photosystem II using supervised and unsupervised machine learning.

Photosynthesis research Jul 27, 2022
Serial Femtosecond Crystallography at the X-ray Free Electron Laser (XFEL) sources enabled the imaging of the catalytic intermediates of the oxygen evolution reaction of Photosystem II (PSII). However, due to the incoherent transition of the S-states...
Oxygen Ions Electron Spin Resonance Spectroscopy Photosystem II Protein Complex Unsupervised Machine Learning Water Oxidation-Reduction
View on PubMed DOI

AXEAP: a software package for X-ray emission data analysis using unsupervised machine learning.

Journal of synchrotron radiation Jul 21, 2022
The Argonne X-ray Emission Analysis Package (AXEAP) has been developed to calibrate and process X-ray emission spectroscopy (XES) data collected with a two-dimensional (2D) position-sensitive detector. AXEAP is designed to convert a 2D XES image into...
Software Radiography Data Analysis X-Rays Unsupervised Machine Learning
View on PubMed DOI

Identifying endotypes of individuals after an attack of pancreatitis based on unsupervised machine learning of multiplex cytokine profiles.

Translational research : the journal of laboratory and clinical medicine Jul 18, 2022
After an attack of pancreatitis, individuals may develop metabolic sequelae (eg, new-onset diabetes) and/or pancreatic cancer. These new-onset morbidities are, at least in part, driven by low-grade inflammation. The aim was to study the profiles of c...
Pancreas Inflammation Humans Pancreatitis Cytokines Unsupervised Machine Learning
View on PubMed DOI

Phenotypes of sickle cell intensive care admissions: an unsupervised machine learning approach in a single-center retrospective cohort.

Annals of hematology Jul 15, 2022
Sickle cell disease (SCD) is associated with multiple known complications and increased mortality. This study aims to further understand the profile of intensive care unit (ICU) admissions of SCD patients. In this single-center retrospective cohort (...
Male Brazil Intensive Care Units Female Critical Care Anemia, Sickle Cell Hospital Mortality Unsupervised Machine Learning Humans Phenotype Retrospective Studies
View on PubMed DOI

Informed Chemical Classification of Organophosphorus Compounds via Unsupervised Machine Learning of X-ray Absorption Spectroscopy and X-ray Emission Spectroscopy.

The journal of physical chemistry. A Jul 15, 2022
We analyze an ensemble of organophosphorus compounds to form an unbiased characterization of the information encoded in their X-ray absorption near-edge structure (XANES) and valence-to-core X-ray emission spectra (VtC-XES). Data-driven emergence of ...
X-Ray Absorption Spectroscopy Organophosphorus Compounds Spectrometry, X-Ray Emission Ligands Humans Unsupervised Machine Learning
View on PubMed DOI

Diversity of approaches in artificial intelligence: an opportunity for discoveries in thoracic imaging.

The European respiratory journal Jul 7, 2022
Quinolones Cystic Fibrosis Aminophenols Aminopyridines Humans Tomography, X-Ray Computed Artificial Intelligence Unsupervised Machine Learning Benzodioxoles
View on PubMed DOI

Unsupervised learning methods for efficient geographic clustering and identification of disease disparities with applications to county-level colorectal cancer incidence in California.

Health care management science Jun 23, 2022
Many public health policymaking questions involve data subsets representing application-specific attributes and geographic location. We develop and evaluate standard and tailored techniques for clustering via unsupervised learning (UL) algorithms on ...
Unsupervised Machine Learning Humans Incidence Algorithms Cluster Analysis Colorectal Neoplasms
View on PubMed DOI

Unsupervised Hyperspectral Microscopic Image Segmentation Using Deep Embedded Clustering Algorithm.

Scanning Jun 6, 2022
Hyperspectral microscopy in biology and minerals, unsupervised deep learning neural network denoising SRS photos: hyperspectral resolution enhancement and denoising one hyperspectral picture is enough to teach unsupervised method. An intuitive chemic...
Algorithms Neural Networks, Computer Cluster Analysis Unsupervised Machine Learning
View on PubMed DOI
Popular Topics
Recent Journals