AIMC Topic: Humans

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Toward a Better Estimation of Functional Brain Network for Mild Cognitive Impairment Identification: A Transfer Learning View.

IEEE journal of biomedical and health informatics
Mild cognitive impairment (MCI) is an intermediate stage of brain cognitive decline, associated with increasing risk of developing Alzheimer's disease (AD). It is believed that early treatment of MCI could slow down the progression of AD, and functio...

Spatio-Temporal Deep Learning-Based Undersampling Artefact Reduction for 2D Radial Cine MRI With Limited Training Data.

IEEE transactions on medical imaging
In this work we reduce undersampling artefacts in two-dimensional (2D) golden-angle radial cine cardiac MRI by applying a modified version of the U-net. The network is trained on 2D spatio-temporal slices which are previously extracted from the image...

Automated sleep scoring: A review of the latest approaches.

Sleep medicine reviews
Clinical sleep scoring involves a tedious visual review of overnight polysomnograms by a human expert, according to official standards. It could appear then a suitable task for modern artificial intelligence algorithms. Indeed, machine learning algor...

Accurate automated Cobb angles estimation using multi-view extrapolation net.

Medical image analysis
Accurate automated quantitative Cobb angle estimation that quantitatively evaluates scoliosis plays an important role in scoliosis diagnosis and treatment. It solves the problem of the traditional manual method, which is the current clinical standard...

Artificial intelligence in digital pathology - new tools for diagnosis and precision oncology.

Nature reviews. Clinical oncology
In the past decade, advances in precision oncology have resulted in an increased demand for predictive assays that enable the selection and stratification of patients for treatment. The enormous divergence of signalling and transcriptional networks m...

Recognition of peripheral blood cell images using convolutional neural networks.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Morphological analysis is the starting point for the diagnostic approach of more than 80% of hematological diseases. However, the morphological differentiation among different types of normal and abnormal peripheral blood c...

Automated detection of diabetic subject using pre-trained 2D-CNN models with frequency spectrum images extracted from heart rate signals.

Computers in biology and medicine
In this study, a deep-transfer learning approach is proposed for the automated diagnosis of diabetes mellitus (DM), using heart rate (HR) signals obtained from electrocardiogram (ECG) data. Recent progress in deep learning has contributed significant...

A Heuristic Approach to Overcome Architectural Barriers Using a Robotic Wheelchair.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
The Mobility Enhancement roBotic (MEBot) wheelchair was developed to improve the safety and accessibility of wheelchair users when facing architectural barriers. MEBot uses pneumatic actuators attached to its frame and six wheels to provide curb asce...

Hyper-G: An Artificial Intelligence Tool for Optimal Decision-Making and Management of Blood Glucose Levels in Surgery Patients.

Methods of information in medicine
BACKGROUND: Hyperglycemia or high blood glucose during surgery is associated with poor postoperative outcome. Knowing in advance which patients may develop hyperglycemia allows optimal assignment of resources and earlier initiation of glucose managem...

Machine learning for tissue diagnostics in oncology: brave new world.

British journal of cancer
Machine learning is an exciting technology with broad application in big data analysis, as well as increasingly in specialised healthcare. As a diagnostic tool in tissue workup and pathology, it has the potential for personalised and stratified appro...