AIMC Topic: Deep Learning

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Classification of Alzheimer's Disease Using Gaussian-Based Bayesian Parameter Optimization for Deep Convolutional LSTM Network.

Computational and mathematical methods in medicine
Alzheimer's disease (AD) is one of the most important causes of mortality in elderly people, and it is often challenging to use traditional manual procedures when diagnosing a disease in the early stages. The successful implementation of machine lear...

Segmentation of Overlapping Cervical Cells with Mask Region Convolutional Neural Network.

Computational and mathematical methods in medicine
The task of segmenting cytoplasm in cytology images is one of the most challenging tasks in cervix cytological analysis due to the presence of fuzzy and highly overlapping cells. Deep learning-based diagnostic technology has proven to be effective in...

Deep-learning model for screening sepsis using electrocardiography.

Scandinavian journal of trauma, resuscitation and emergency medicine
BACKGROUND: Sepsis is a life-threatening organ dysfunction and a major healthcare burden worldwide. Although sepsis is a medical emergency that requires immediate management, screening for the occurrence of sepsis is difficult. Herein, we propose a d...

A deep learning algorithm for white matter hyperintensity lesion detection and segmentation.

Neuroradiology
PURPOSE: White matter hyperintensity (WMHI) lesions on MR images are an important indication of various types of brain diseases that involve inflammation and blood vessel abnormalities. Automated quantification of the WMHI can be valuable for the cli...

Prediction of post-stroke cognitive impairment using brain FDG PET: deep learning-based approach.

European journal of nuclear medicine and molecular imaging
PURPOSE: Post-stroke cognitive impairment can affect up to one third of stroke survivors. Since cognitive function greatly contributes to patients' quality of life, an objective quantitative biomarker for early prediction of dementia after stroke is ...

Deep convolutional neural network-based algorithm for muscle biopsy diagnosis.

Laboratory investigation; a journal of technical methods and pathology
Histopathologic evaluation of muscle biopsy samples is essential for classifying and diagnosing muscle diseases. However, the numbers of experienced specialists and pathologists are limited. Although new technologies such as artificial intelligence a...

Deep-Hook: A trusted deep learning-based framework for unknown malware detection and classification in Linux cloud environments.

Neural networks : the official journal of the International Neural Network Society
Since the beginning of the 21st century, the use of cloud computing has increased rapidly, and it currently plays a significant role among most organizations' information technology (IT) infrastructure. Virtualization technologies, particularly virtu...

Deep Learning-Based Analysis of Face Images as a Screening Tool for Genetic Syndromes.

Sensors (Basel, Switzerland)
Approximately 4% of the world's population suffers from rare diseases. A vast majority of these disorders have a genetic background. The number of genes that have been linked to human diseases is constantly growing, but there are still genetic syndro...

Automating classification of osteoarthritis according to Kellgren-Lawrence in the knee using deep learning in an unfiltered adult population.

BMC musculoskeletal disorders
BACKGROUND: Prevalence for knee osteoarthritis is rising in both Sweden and globally due to increased age and obesity in the population. This has subsequently led to an increasing demand for knee arthroplasties. Correct diagnosis and classification o...

Adaptive investigation of the optical properties of polymer fibers from mixing noisy phase shifting microinterferograms using deep learning algorithms.

Microscopy research and technique
In this article, an adaptive denoising method is suggested to accurate investigate the optical and structural features of polymeric fibers from noisy phase shifting microinterferograms. The mixed class of noise that may produce in the phase-shifting ...