AIMC Topic: Humans

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Inter-patient automated arrhythmia classification: A new approach of weight capsule and sequence to sequence combination.

Computer methods and programs in biomedicine
OBJECTIVE: We propose a new capsule network to compensate for the information loss in the deep convolutional networks in previous studies, and to improve the performance of arrhythmia classification.

Comparison of machine learning and deep learning for view identification from cardiac magnetic resonance images.

Clinical imaging
BACKGROUND: Artificial intelligence is increasingly utilized to aid in the interpretation of cardiac magnetic resonance (CMR) studies. One of the first steps is the identification of the imaging plane depicted, which can be achieved by both deep lear...

Deep learning-based GTV contouring modeling inter- and intra- observer variability in sarcomas.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND AND PURPOSE: The delineation of the gross tumor volume (GTV) is a critical step for radiation therapy treatment planning. The delineation procedure is typically performed manually which exposes two major issues: cost and reproducibility. D...

O-glycosylation site prediction for by combining properties and sequence features with support vector machine.

Journal of bioinformatics and computational biology
O-glycosylation is a protein posttranslational modification important in regulating almost all cells. It is related to a large number of physiological and pathological phenomena. Recognizing O-glycosylation sites is the key to further investigating t...

Breast imaging: Beyond the detection.

European journal of radiology
Breast cancer is a heterogeneous disease nowadays, including different biological subtypes with a variety of possible treatments, which aim to achieve the best outcome in terms of response to therapy and overall survival. In recent years breast imagi...

Integration of deep learning-based image analysis and genomic data in cancer pathology: A systematic review.

European journal of cancer (Oxford, England : 1990)
BACKGROUND: Over the past decade, the development of molecular high-throughput methods (omics) increased rapidly and provided new insights for cancer research. In parallel, deep learning approaches revealed the enormous potential for medical image an...

Identification of Alzheimer associated differentially expressed gene through microarray data and transfer learning-based image analysis.

Neuroscience letters
Major factors contribute to mental stress and enhance the progression of late-onset Alzheimer's disease (AD). The factors that lead to neurodegeneration, such as tau protein hyperphosphorylation and increased amyloid-beta production, can be mimicked ...

DNA methylation-based classification of malformations of cortical development in the human brain.

Acta neuropathologica
Malformations of cortical development (MCD) comprise a broad spectrum of structural brain lesions frequently associated with epilepsy. Disease definition and diagnosis remain challenging and are often prone to arbitrary judgment. Molecular classifica...

Natural Language Processing Enhances Prediction of Functional Outcome After Acute Ischemic Stroke.

Journal of the American Heart Association
Background Conventional prognostic scores usually require predefined clinical variables to predict outcome. The advancement of natural language processing has made it feasible to derive meaning from unstructured data. We aimed to test whether using u...

Fully automated deep learning-based localization and segmentation of the locus coeruleus in aging and Parkinson's disease using neuromelanin-sensitive MRI.

International journal of computer assisted radiology and surgery
PURPOSE: Development and performance measurement of a fully automated pipeline that localizes and segments the locus coeruleus in so-called neuromelanin-sensitive magnetic resonance imaging data for the derivation of quantitative biomarkers of neurod...