AIMC Topic: Humans

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RefDNN: a reference drug based neural network for more accurate prediction of anticancer drug resistance.

Scientific reports
Cancer is one of the most difficult diseases to treat owing to the drug resistance of tumour cells. Recent studies have revealed that drug responses are closely associated with genomic alterations in cancer cells. Numerous state-of-the-art machine le...

A deep learning system accurately classifies primary and metastatic cancers using passenger mutation patterns.

Nature communications
In cancer, the primary tumour's organ of origin and histopathology are the strongest determinants of its clinical behaviour, but in 3% of cases a patient presents with a metastatic tumour and no obvious primary. Here, as part of the ICGC/TCGA Pan-Can...

Human arm weight compensation in rehabilitation robotics: efficacy of three distinct methods.

Journal of neuroengineering and rehabilitation
BACKGROUND: Arm weight compensation with rehabilitation robots for stroke patients has been successfully used to increase the active range of motion and reduce the effects of pathological muscle synergies. However, the differences in structure, perfo...

End-to-end trained encoder-decoder convolutional neural network for fetal electrocardiogram signal denoising.

Physiological measurement
OBJECTIVE: Non-invasive fetal electrocardiography has the potential to provide vital information for evaluating the health status of the fetus. However, the low signal-to-noise ratio of the fetal electrocardiogram (ECG) impedes the applicability of t...

Automatic detection of brachytherapy seeds in 3D ultrasound images using a convolutional neural network.

Physics in medicine and biology
A novel approach for automatic localization of brachytherapy seeds in 3D transrectal ultrasound (TRUS) images, using machine learning based algorithm, is presented. 3D radiofrequency ultrasound signals were collected from 13 patients using the linear...

External validation and transfer learning of convolutional neural networks for computed tomography dental artifact classification.

Physics in medicine and biology
Quality assurance of data prior to use in automated pipelines and image analysis would assist in safeguarding against biases and incorrect interpretation of results. Automation of quality assurance steps would further improve robustness and efficienc...

The impact of different training load quantification and modelling methodologies on performance predictions in elite swimmers.

European journal of sport science
The use of rolling averages to analyse training data has been debated recently. We evaluated two training load quantification methods (five-zone, seven-zone) fitted to performances over two race distances (50 and 100 m) using four separate longitudin...

Virtual genetic diagnosis for familial hypercholesterolemia powered by machine learning.

European journal of preventive cardiology
AIMS: Familial hypercholesterolemia (FH) is the most common genetic disorder of lipid metabolism. The gold standard for FH diagnosis is genetic testing, available, however, only in selected university hospitals. Clinical scores - for example, the Dut...

Radiomics for classification of bone mineral loss: A machine learning study.

Diagnostic and interventional imaging
PURPOSE: The purpose of this study was to develop predictive models to classify osteoporosis, osteopenia and normal patients using radiomics and machine learning approaches.