AIMC Topic: Diagnosis, Computer-Assisted

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Deep learning based computer-aided diagnosis systems for diabetic retinopathy: A survey.

Artificial intelligence in medicine
Diabetic retinopathy (DR) results in vision loss if not treated early. A computer-aided diagnosis (CAD) system based on retinal fundus images is an efficient and effective method for early DR diagnosis and assisting experts. A computer-aided diagnosi...

Computer-aided detection and visualization of pulmonary embolism using a novel, compact, and discriminative image representation.

Medical image analysis
Diagnosing pulmonary embolism (PE) and excluding disorders that may clinically and radiologically simulate PE poses a challenging task for both human and machine perception. In this paper, we propose a novel vessel-oriented image representation (VOIR...

Epilepsy Seizure Prediction on EEG Using Common Spatial Pattern and Convolutional Neural Network.

IEEE journal of biomedical and health informatics
Epilepsy seizure prediction paves the way of timely warning for patients to take more active and effective intervention measures. Compared to seizure detection that only identifies the inter-ictal state and the ictal state, far fewer researches have ...

Accurate detection of atrial fibrillation from 12-lead ECG using deep neural network.

Computers in biology and medicine
Atrial fibrillation (AF) is the most common heart arrhythmia, and 12-lead electrocardiogram (ECG) is regarded as the gold standard for AF diagnosis. Highly accurate diagnosis of AF based on 12-lead ECG is valuable and remains challenging. In this pap...

Characterizing Alzheimer's Disease With Image and Genetic Biomarkers Using Supervised Topic Models.

IEEE journal of biomedical and health informatics
Neuroimaging and genetic biomarkers have been widely studied from discriminative perspectives towards Alzheimer's disease (AD) classification, since neuroanatomical patterns and genetic variants are jointly critical indicators for AD diagnosis. Gener...

A neural network-based software to recognise blepharospasm symptoms and to measure eye closure time.

Computers in biology and medicine
Blepharospasm (BSP) is an adult-onset focal dystonia with phenomenologically heterogeneous effects, including, but not limited to, blinks, brief or prolonged spasms, and a narrowing or closure of the eyelids. In spite of the clear and well-known symp...

Electroencephalogram Spectral Moments for the Detection of Nocturnal Hypoglycemia.

IEEE journal of biomedical and health informatics
Hypoglycemia or low blood glucose is the most feared complication of insulin treatment of diabetes. For people with diabetes, the mismatch between the insulin therapy and the body's physiology could increase the risk of hypoglycemia. Nocturnal hypogl...

Automated detection and classification of early AMD biomarkers using deep learning.

Scientific reports
Age-related macular degeneration (AMD) affects millions of people and is a leading cause of blindness throughout the world. Ideally, affected individuals would be identified at an early stage before late sequelae such as outer retinal atrophy or exud...

Accurate prediction of glaucoma from colour fundus images with a convolutional neural network that relies on active and transfer learning.

Acta ophthalmologica
PURPOSE: To assess the use of deep learning (DL) for computer-assisted glaucoma identification, and the impact of training using images selected by an active learning strategy, which minimizes labelling cost. Additionally, this study focuses on the e...