AIMC Topic: Deep Learning

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Using multi-layer perceptron with Laplacian edge detector for bladder cancer diagnosis.

Artificial intelligence in medicine
In this paper, the urinary bladder cancer diagnostic method which is based on Multi-Layer Perceptron and Laplacian edge detector is presented. The aim of this paper is to investigate the implementation possibility of a simpler method (Multi-Layer Per...

Deep Learning Analysis of Coronary Arteries in Cardiac CT Angiography for Detection of Patients Requiring Invasive Coronary Angiography.

IEEE transactions on medical imaging
In patients with obstructive coronary artery disease, the functional significance of a coronary artery stenosis needs to be determined to guide treatment. This is typically established through fractional flow reserve (FFR) measurement, performed duri...

An artificial intelligence-based deep learning algorithm for the diagnosis of diabetic neuropathy using corneal confocal microscopy: a development and validation study.

Diabetologia
AIMS/HYPOTHESIS: Corneal confocal microscopy is a rapid non-invasive ophthalmic imaging technique that identifies peripheral and central neurodegenerative disease. Quantification of corneal sub-basal nerve plexus morphology, however, requires either ...

Fast fit-free analysis of fluorescence lifetime imaging via deep learning.

Proceedings of the National Academy of Sciences of the United States of America
Fluorescence lifetime imaging (FLI) provides unique quantitative information in biomedical and molecular biology studies but relies on complex data-fitting techniques to derive the quantities of interest. Herein, we propose a fit-free approach in FLI...

A Systematic Review of Detecting Sleep Apnea Using Deep Learning.

Sensors (Basel, Switzerland)
Sleep apnea is a sleep related disorder that significantly affects the population. Polysomnography, the gold standard, is expensive, inaccessible, uncomfortable and an expert technician is needed to score. Numerous researchers have proposed and imple...

Mounting Behaviour Recognition for Pigs Based on Deep Learning.

Sensors (Basel, Switzerland)
For both pigs in commercial farms and biological experimental pigs at breeding bases, mounting behaviour is likely to cause damage such as epidermal wounds, lameness and fractures, and will no doubt reduce animal welfare. The purpose of this paper is...

Exploring semantic deep learning for building reliable and reusable one health knowledge from PubMed systematic reviews and veterinary clinical notes.

Journal of biomedical semantics
BACKGROUND: Deep Learning opens up opportunities for routinely scanning large bodies of biomedical literature and clinical narratives to represent the meaning of biomedical and clinical terms. However, the validation and integration of this knowledge...

Self-attention based recurrent convolutional neural network for disease prediction using healthcare data.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Nowadays computer-aided disease diagnosis from medical data through deep learning methods has become a wide area of research. Existing works of analyzing clinical text data in the medical domain, which substantiate useful in...