AIMC Topic: Deep Learning

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Deep-learning based monitoring of FOG layer dynamics in wastewater pumping stations.

Water research
Accumulation of fat, oil and grease (FOG) in the sumps of wastewater pumping stations is a common failure cause for these facilities. Floating solids are often not transported by the pump suction inlets and the individual solids can accumulate to sti...

A deep learning based ensemble learning method for epileptic seizure prediction.

Computers in biology and medicine
In epilepsy, patients suffer from seizures which cannot be controlled with medicines or surgical treatments in more than 30% of the cases. Prediction of epileptic seizures is extremely important so that they can be controlled with medication before t...

Applications of deep learning techniques for automated multiple sclerosis detection using magnetic resonance imaging: A review.

Computers in biology and medicine
Multiple Sclerosis (MS) is a type of brain disease which causes visual, sensory, and motor problems for people with a detrimental effect on the functioning of the nervous system. In order to diagnose MS, multiple screening methods have been proposed ...

Implementation of a Deep Learning Algorithm Based on Vertical Ground Reaction Force Time-Frequency Features for the Detection and Severity Classification of Parkinson's Disease.

Sensors (Basel, Switzerland)
Conventional approaches to diagnosing Parkinson's disease (PD) and rating its severity level are based on medical specialists' clinical assessment of symptoms, which are subjective and can be inaccurate. These techniques are not very reliable, partic...

Application of deep-learning to the seronegative side of the NMO spectrum.

Journal of neurology
OBJECTIVES: To apply a deep-learning algorithm to brain MRIs of seronegative patients with neuromyelitis optica spectrum disorders (NMOSD) and NMOSD-like manifestations and assess whether their structural features are similar to aquaporin-4-seroposit...

A 3D deep learning model to predict the diagnosis of dementia with Lewy bodies, Alzheimer's disease, and mild cognitive impairment using brain 18F-FDG PET.

European journal of nuclear medicine and molecular imaging
PURPOSE: The purpose of this study is to develop and validate a 3D deep learning model that predicts the final clinical diagnosis of Alzheimer's disease (AD), dementia with Lewy bodies (DLB), mild cognitive impairment due to Alzheimer's disease (MCI-...

xDeep-AcPEP: Deep Learning Method for Anticancer Peptide Activity Prediction Based on Convolutional Neural Network and Multitask Learning.

Journal of chemical information and modeling
Cancer is one of the leading causes of death worldwide. Conventional cancer treatment relies on radiotherapy and chemotherapy, but both methods bring severe side effects to patients, as these therapies not only attack cancer cells but also damage nor...

Deep Learning-Based ECG-Free Cardiac Navigation for Multi-Dimensional and Motion-Resolved Continuous Magnetic Resonance Imaging.

IEEE transactions on medical imaging
For the clinical assessment of cardiac vitality, time-continuous tomographic imaging of the heart is used. To further detect e.g., pathological tissue, multiple imaging contrasts enable a thorough diagnosis using magnetic resonance imaging (MRI). For...

S3Reg: Superfast Spherical Surface Registration Based on Deep Learning.

IEEE transactions on medical imaging
Cortical surface registration is an essential step and prerequisite for surface-based neuroimaging analysis. It aligns cortical surfaces across individuals and time points to establish cross-sectional and longitudinal cortical correspondences to faci...

Quantum algorithm for quicker clinical prognostic analysis: an application and experimental study using CT scan images of COVID-19 patients.

BMC medical informatics and decision making
BACKGROUND: In medical diagnosis and clinical practice, diagnosing a disease early is crucial for accurate treatment, lessening the stress on the healthcare system. In medical imaging research, image processing techniques tend to be vital in analyzin...