Geriatrics

Machine learning approach for early detection of autism by combining questionnaire and home video screening.

BACKGROUND: Existing screening tools for early detection of autism are expensive, cumbersome, time- intensive, and sometimes fall short in predictive value. In this work, we sought to apply Machine Learning (ML) to gold standard clinical data obtained across thousands of children at-risk for autism spectrum disorder to create a low-cost, quick, and easy to apply autism screening tool.

[Big data and artificial intelligence for diagnostic decision support in atypical dementia].

The differential diagnosis of atypical dementia remains difficult. The use of positron emission tomography (PET) still represents the gold standard for imaging diagnostics. According to the current evidence, however, magnetic resonance imaging (MRI) is almost equal to fluorodeoxyglucose (FDG)-PET, but only when using new big data and machine learning methods. In cases of atypical dementia, especia...

Modeling polypharmacy side effects with graph convolutional networks.

MOTIVATION: The use of drug combinations, termed polypharmacy, is common to treat patients with complex diseases or co-existing conditions. However, a...

Detection of Early Stage Alzheimer's Disease using EEG Relative Power with Deep Neural Network.

Electroencephalogram (EEG) signal based early diagnosis of Alzheimer's Disease (AD), especially a discrimination between healthy control (HC) and mild...

Isometry Invariant Shape Descriptors for Abnormality Detection on Brain Surfaces Affected by Alzheimer's Disease.

Alzheimer's disease (AD), a progressive brain disorder, is the most common neurodegenerative disease in older adults. There is a need for brain struct...

Personalized Human Activity Recognition using Wearables: A Manifold Learning-based Knowledge Transfer.

Human activity recognition (HAR) is an important component in health-care systems. For example, it can enable context-aware applications such as elder...

Validation of Improvements of Robotic Devices for Nursing Care using a Sensing Dummy Simulating Human Body.

The population in advanced countries is rapidly aging, and these countries are faced with various issues pertaining to the rapidly aging population. I...

Thermal Camera Based Physiological Monitoring with an Assistive Robot.

This paper presents a physiological monitoring system for assistive robots using a thermal camera. It is based on the detection of subtle changes in t...

ENS-Unet: End-to-End Noise Suppression U-Net for Brain Tumor Segmentation.

Thanks to deep convolutional neural networks (CNNs), Brain Tumor Segmentation (BTS) has made great progresses, while most existing methods are parsed ...

The New Possibilities from "Big Data" to Overlooked Associations Between Diabetes, Biochemical Parameters, Glucose Control, and Osteoporosis.

PURPOSE OF REVIEW: To review current practices and technologies within the scope of "Big Data" that can further our understanding of diabetes mellitus...

Automated Detection of Clinically Significant Prostate Cancer in mp-MRI Images Based on an End-to-End Deep Neural Network.

Automated methods for detecting clinically significant (CS) prostate cancer (PCa) in multi-parameter magnetic resonance images (mp-MRI) are of high de...

Infection prevention and control challenges of using a therapeutic robot.

This work was part of a National Institute for Health Research participatory action research and practice development study, which focused on the use ...

Validation of artificial neural networks as a methodology for donor-recipient matching for liver transplantation.

In 2014, we reported a model for donor-recipient (D-R) matching in liver transplantation (LT) based on artificial neural networks (ANNs) from a Spanis...

Integrative Analysis of Proteomics Data to Obtain Clinically Relevant Markers.

The analysis of proteomics data can be significantly challenging. Beyond the technical challenges of accurately identifying and quantifying peptides, ...

A Clinically-Translatable Machine Learning Algorithm for the Prediction of Alzheimer's Disease Conversion in Individuals with Mild and Premild Cognitive Impairment.

BACKGROUND: Available therapies for Alzheimer's disease (AD) can only alleviate and delay the advance of symptoms, with the greatest impact eventually...

Network pharmacology-based analysis of Chinese herbal Naodesheng formula for application to Alzheimer's disease.

Naodesheng (NDS) formula, which consists of Rhizoma Chuanxiong, Lobed Kudzuvine, Carthamus tinctorius, Radix Notoginseng, and Crataegus pinnatifida, i...

Data Mining and Machine Learning Methods for Dementia Research.

Patient data in clinical research often includes large amounts of structured information, such as neuroimaging data, neuropsychological test results, ...

Development of Teaching Materials of Dementia by Incorporating a Communications Robot for Schoolchildren Who Are Dementia Supporters.

In this study, we aimed to teach elementary school students how to practically deal with elderly people with dementia and developed and evaluated teac...

On the Representation of Machine Learning Results for Delirium Prediction in a Hospital Information System in Routine Care.

Digitalisation of health care for the purpose of medical documentation lead to huge amounts of data, hence having an opportunity to derive knowledge a...

Evaluating the Impact of Incorrect Diabetes Coding on the Performance of Multivariable Prediction Models.

The use of electronic health records for risk prediction models requires a sufficient quality of input data to ensure patient safety. The aim of our s...