AIMC Topic: Humans

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Automatic height measurement of central serous chorioretinopathy lesion using a deep learning and adaptive gradient threshold based cascading strategy.

Computers in biology and medicine
Accurately quantifying the height of central serous chorioretinopathy (CSCR) lesion is of great significance for assisting ophthalmologists in diagnosing CSCR and evaluating treatment efficacy. The manual measurement results dominated by single optic...

Comprehensive quantitative radiogenomic evaluation reveals novel radiomic subtypes with distinct immune pattern in glioma.

Computers in biology and medicine
BACKGROUND: Accurate classification of gliomas is critical to the selection of immunotherapy, and MRI contains a large number of radiomic features that may suggest some prognostic relevant signals. We aim to predict new subtypes of gliomas using radi...

A novel feature extraction method PSS-CSP for binary motor imagery - based brain-computer interfaces.

Computers in biology and medicine
In order to improve the performance of binary motor imagery (MI) - based brain-computer interfaces (BCIs) using electroencephalography (EEG), a novel method (PSS-CSP) is proposed, which combines spectral subtraction with common spatial pattern. Spect...

Computed tomography machine learning classifier correlates with mortality in interstitial lung disease.

Respiratory investigation
BACKGROUND: A machine learning classifier system, Fibresolve, was designed and validated as an adjunct to non-invasive diagnosis in idiopathic pulmonary fibrosis (IPF). The system uses a deep learning algorithm to analyze chest computed tomography (C...

MRIO: the Magnetic Resonance Imaging Acquisition and Analysis Ontology.

Neuroinformatics
Magnetic resonance imaging of the brain is a useful tool in both the clinic and research settings, aiding in the diagnosis and treatments of neurological disease and expanding our knowledge of the brain. However, there are many challenges inherent in...

Deep Learning Method for Rapid Simultaneous Multistructure Temporal Bone Segmentation.

Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery
OBJECTIVE: To develop and validate a deep learning algorithm for the automated segmentation of key temporal bone structures from clinical computed tomography (CT) data sets.

Formulation of Common Spatial Patterns for Multi-Task Hyperscanning BCI.

IEEE transactions on bio-medical engineering
This work proposes a new formulation for common spatial patterns (CSP), often used as a powerful feature extraction technique in brain-computer interfacing (BCI) and other neurological studies. In this approach, applied to multiple subjects' data and...

A Spatiotemporal Deep Learning Framework for Scalp EEG-Based Automated Pain Assessment in Children.

IEEE transactions on bio-medical engineering
OBJECTIVE: Common pain assessment approaches such as self-evaluation and observation scales are inappropriate for children as they require patients to have reasonable communication ability. Subjective, inconsistent, and discontinuous pain assessment ...