AIMC Topic: Humans

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A Fundamental Study Assessing the Diagnostic Performance of Deep Learning for a Brain Metastasis Detection Task.

Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine
PURPOSE: Increased use of deep convolutional neural networks (DCNNs) in medical imaging diagnosis requires determinate evaluation of diagnostic performance. We performed the fundamental investigation of diagnostic performance of DCNNs using the detec...

Artificial Intelligence in Drug Treatment.

Annual review of pharmacology and toxicology
The most common applications of artificial intelligence (AI) in drug treatment have to do with matching patients to their optimal drug or combination of drugs, predicting drug-target or drug-drug interactions, and optimizing treatment protocols. This...

Annotated normal CT data of the abdomen for deep learning: Challenges and strategies for implementation.

Diagnostic and interventional imaging
PURPOSE: The purpose of this study was to report procedures developed to annotate abdominal computed tomography (CT) images from subjects without pancreatic disease that will be used as the input for deep convolutional neural networks (DNN) for devel...

Self-supervised learning for medical image analysis using image context restoration.

Medical image analysis
Machine learning, particularly deep learning has boosted medical image analysis over the past years. Training a good model based on deep learning requires large amount of labelled data. However, it is often difficult to obtain a sufficient number of ...

A subgraph-representation-based method for answering complex questions over knowledge bases.

Neural networks : the official journal of the International Neural Network Society
Knowledge-based question answering has attracted a lot of attention in the research communities of natural language processing and information retrieval. However, existing studies do not adequately address the problem of answering complex questions w...

A programmable neural virtual machine based on a fast store-erase learning rule.

Neural networks : the official journal of the International Neural Network Society
We present a neural architecture that uses a novel local learning rule to represent and execute arbitrary, symbolic programs written in a conventional assembly-like language. This Neural Virtual Machine (NVM) is purely neurocomputational but supports...

Fully automated intracranial ventricle segmentation on CT with 2D regional convolutional neural network to estimate ventricular volume.

International journal of computer assisted radiology and surgery
PURPOSE: Hydrocephalus is a clinically significant condition which can have devastating consequences if left untreated. Currently available methods for quantifying this condition using CT imaging are unreliable and prone to error. The purpose of this...

Modelling outcomes after paediatric brain injury with admission laboratory values: a machine-learning approach.

Pediatric research
BACKGROUND: Severe traumatic brain injury (TBI) is a leading cause of mortality in children, but the accurate prediction of outcomes at the point of admission remains very challenging. Admission laboratory results are a promising potential source of ...

Classification of drug-induced hERG potassium-channel block from electrocardiographic T-wave features using artificial neural networks.

Annals of noninvasive electrocardiology : the official journal of the International Society for Holter and Noninvasive Electrocardiology, Inc
BACKGROUND: Human ether-à-go-go-related gene (hERG) potassium-channel block represents a harmful side effect of drug therapy that may cause torsade de pointes (TdP). Analysis of ventricular repolarization through electrocardiographic T-wave features ...

Artificial intelligence for precision education in radiology.

The British journal of radiology
In the era of personalized medicine, the emphasis of health care is shifting from populations to individuals. Artificial intelligence (AI) is capable of learning without explicit instruction and has emerging applications in medicine, particularly rad...