AIMC Topic: Aged

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A model to forecast the two-year variation of subjective wellbeing in the elderly population.

BMC medical informatics and decision making
BACKGROUND: The ageing global population presents significant public health challenges, especially in relation to the subjective wellbeing of the elderly. In this study, our aim was to investigate the potential for developing a model to forecast the ...

Effect of 4-weeks exercise program using wearable hip-assist robot (EX1) in older adults: one group pre- and post- test.

BMC geriatrics
BACKGROUND: Older adults have muscle loss and are at risk of falling. Recently, research in the healthcare field has been actively conducted, and Samsung Electronics has developed EX1, a hip joint assisted robot for exercise. This study aimed to veri...

Automatic Detection and Classification of Modic Changes in MRI Images Using Deep Learning: Intelligent Assisted Diagnosis System.

Orthopaedic surgery
OBJECTIVE: Modic changes (MCs) are the most prevalent classification system for describing intravertebral MRI signal intensity changes. However, interpreting these intricate MRI images is a complex and time-consuming process. This study investigates ...

Deep learning-based age estimation from clinical Computed Tomography image data of the thorax and abdomen in the adult population.

PloS one
Aging is an important risk factor for disease, leading to morphological change that can be assessed on Computed Tomography (CT) scans. We propose a deep learning model for automated age estimation based on CT- scans of the thorax and abdomen generate...

A Deep Learning Approach for Automatic and Objective Grading of the Motor Impairment Severity in Parkinson's Disease for Use in Tele-Assessments.

Sensors (Basel, Switzerland)
Wearable sensors provide a tool for at-home monitoring of motor impairment progression in neurological conditions such as Parkinson's disease (PD). This study examined the ability of deep learning approaches to grade the motor impairment severity in ...

A Deep Learning Framework for Anesthesia Depth Prediction from Drug Infusion History.

Sensors (Basel, Switzerland)
In the target-controlled infusion (TCI) of propofol and remifentanil intravenous anesthesia, accurate prediction of the depth of anesthesia (DOA) is very challenging. Patients with different physiological characteristics have inconsistent pharmacodyn...

Can machine learning provide preoperative predictions of biological hemostasis after extracorporeal circulation for cardiac surgery?

The Journal of thoracic and cardiovascular surgery
OBJECTIVES: The goal of this study was to improve decision making regarding the transfusion of patients at the end of extracorporeal circulation for cardiac surgery through machine learning predictions of the evolution of platelets counts, prothrombi...

Chamber Attention Network (CAN): Towards interpretable diagnosis of pulmonary artery hypertension using echocardiography.

Journal of advanced research
INTRODUCTION: Accurate identification of pulmonary arterial hypertension (PAH) in primary care and rural areas can be a challenging task. However, recent advancements in computer vision offer the potential for automated systems to detect PAH from ech...

Using Interoperability between Mobile Robot and KNX Technology for Occupancy Monitoring in Smart Home Care.

Sensors (Basel, Switzerland)
It is important for older and disabled people who live alone to be able to cope with the daily challenges of living at home. In order to support independent living, the Smart Home Care (SHC) concept offers the possibility of providing comfortable con...