AIMC Topic: Aged

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Measurement and immunophenotyping of pleural fluid EpCAM-positive cells and clusters for the management of non-small cell lung cancer patients.

Lung cancer (Amsterdam, Netherlands)
OBJECTIVES: A malignant pleural effusion (MPE) is a common complication in non-small cell lung cancer (NSCLC) with important staging and prognostic information. Patients with MPEs are often candidates for advanced therapies, however, the current gold...

Automated detection of imaging features of disproportionately enlarged subarachnoid space hydrocephalus using machine learning methods.

NeuroImage. Clinical
OBJECTIVE: Create an automated classifier for imaging characteristics of disproportionately enlarged subarachnoid space hydrocephalus (DESH), a neuroimaging phenotype of idiopathic normal pressure hydrocephalus (iNPH).

Using telepresence for social connection: views of older people with dementia, families, and health professionals from a mixed methods pilot study.

Aging & mental health
To explore the acceptability of telepresence robots in dementia care from the perspectives of people with dementia, family carers, and health professionals/trainees, and investigate the utility of a social presence assessment tool, the Modified-Temp...

Use of a robotic walking aid in rehabilitation to reduce fear of falling is feasible and acceptable from the end user's perspective: A randomised comparative study.

Maturitas
Objectives To determine the acceptability and feasibility of the use of a robotic walking aid to support the work of physiotherapists in reducing fear of falling in the rehabilitation of elderly patients with 'psychomotor disadaptation' (the most sev...

Supervised learning for bone shape and cortical thickness estimation from CT images for finite element analysis.

Medical image analysis
Knowledge about the thickness of the cortical bone is of high interest for fracture risk assessment. Most finite element model solutions overlook this information because of the coarse resolution of the CT images. To circumvent this limitation, a thr...

A machine-learning approach to volitional control of a closed-loop deep brain stimulation system.

Journal of neural engineering
OBJECTIVE: Deep brain stimulation (DBS) is a well-established treatment for essential tremor, but may not be an optimal therapy, as it is always on, regardless of symptoms. A closed-loop (CL) DBS, which uses a biosignal to determine when stimulation ...

Radiomics and machine learning may accurately predict the grade and histological subtype in meningiomas using conventional and diffusion tensor imaging.

European radiology
OBJECTIVES: Preoperative, noninvasive prediction of the meningioma grade is important because it influences the treatment strategy. The purpose of this study was to evaluate the role of radiomics features of postcontrast T1-weighted images (T1C), app...

Machine learning of brain gray matter differentiates sex in a large forensic sample.

Human brain mapping
Differences between males and females have been extensively documented in biological, psychological, and behavioral domains. Among these, sex differences in the rate and typology of antisocial behavior remains one of the most conspicuous and enduring...

Deep neural network for estimating low density lipoprotein cholesterol.

Clinica chimica acta; international journal of clinical chemistry
BACKGROUND: LDL cholesterol (LDL-C) has been mainly estimated using the Friedewald equation, and other equations have recently been developed to complement the Friedewald equation. The present study aims to employ a deep neural network (DNN) to impro...

Retinal image analytics detects white matter hyperintensities in healthy adults.

Annals of clinical and translational neurology
OBJECTIVE: We investigated whether an automatic retinal image analysis (ARIA) incorporating machine learning approach can identify asymptomatic older adults harboring high burden of white matter hyperintensities (WMH) using MRI as gold standard.