AIMC Topic: Aged

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From Local to Global: A Graph Framework for Retinal Artery/Vein Classification.

IEEE transactions on nanobioscience
Fundus photography has been widely used for inspecting eye disorders by ophthalmologists or computer algorithms. Biomarkers related to retinal vessels plays an essential role to detect early diabetes. To quantify vascular biomarkers or the correspond...

Prediction of Total Knee Replacement and Diagnosis of Osteoarthritis by Using Deep Learning on Knee Radiographs: Data from the Osteoarthritis Initiative.

Radiology
Background The methods for assessing knee osteoarthritis (OA) do not provide enough comprehensive information to make robust and accurate outcome predictions. Purpose To develop a deep learning (DL) prediction model for risk of OA progression by usin...

A deep learning algorithm to detect anaemia with ECGs: a retrospective, multicentre study.

The Lancet. Digital health
BACKGROUND: Anaemia is an important health-care burden globally, and screening for anaemia is crucial to prevent multi-organ injury, irreversible complications, and life-threatening adverse events. We aimed to establish whether a deep learning algori...

Utilization of machine learning to test the impact of cognitive processing and emotion recognition on the development of PTSD following trauma exposure.

BMC psychiatry
BACKGROUND: Though lifetime exposure to traumatic events is significant, only a minority of individuals develops symptoms of posttraumatic stress disorder (PTSD). Post-trauma alterations in neurocognitive and affective functioning are likely to refle...

Machine learning-based lifetime breast cancer risk reclassification compared with the BOADICEA model: impact on screening recommendations.

British journal of cancer
BACKGROUND: The clinical utility of machine-learning (ML) algorithms for breast cancer risk prediction and screening practices is unknown. We compared classification of lifetime breast cancer risk based on ML and the BOADICEA model. We explored the d...

CT kernel conversions using convolutional neural net for super-resolution with simplified squeeze-and-excitation blocks and progressive learning among smooth and sharp kernels.

Computer methods and programs in biomedicine
PURPOSE: Computed tomography (CT) volume sets reconstructed with different kernels are helping to increase diagnostic accuracy. However, several CT volumes reconstructed with different kernels are difficult to sustain, due to limited storage and main...

Effects of non-facilitated meaningful activities for people with dementia in long-term care facilities: A systematic review.

Geriatric nursing (New York, N.Y.)
This systematic review sought to evaluate the effectiveness of non-facilitated meaningful activities for older people with dementia in long-term care facilities. Searches were conducted in PubMed; CINAHL; EMBASE; Web of science; PsycINFO; Cochrane; P...

Prediction of Body Weight of a Person Lying on a Smart Mat in Nonrestraint and Unconsciousness Conditions.

Sensors (Basel, Switzerland)
We want to predict body weight while lying in bed for an elderly patient who is unable to move by himself/herself. To this end, we have implemented a prototype system that estimates the body weight of a person lying on a smart mat in nonrestraint and...

Serum adipokines/related inflammatory factors and ratios as predictors of infrapatellar fat pad volume in osteoarthritis: Applying comprehensive machine learning approaches.

Scientific reports
OBJECTIVE: The infrapatellar fat pad (IPFP) has been associated with knee osteoarthritis onset and progression. This study uses machine learning (ML) approaches to predict serum levels of some adipokines/related inflammatory factors and their ratios ...