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Geriatric Assessment

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Preoperative Delirium Risk Screening in Patients Undergoing a Cardiac Surgery: Results from the Prospective Observational FINDERI Study.

The American journal of geriatric psychiatry : official journal of the American Association for Geriatric Psychiatry
OBJECTIVE: Postoperative delirium (POD) is a common complication of cardiac surgery that is associated with higher morbidity, longer hospital stay, cognitive decline, and mortality. Preoperative assessments may help to identify patients´ POD risk. Ho...

An Artificial Neural Network Model for Assessing Frailty-Associated Factors in the Thai Population.

International journal of environmental research and public health
Frailty, one of the major public health problems in the elderly, can result from multiple etiologic factors including biological and physical changes in the body which contribute to the reduction in the function of multiple bodily systems. A diagnosi...

An Automated Planning Model for HRI: Use Cases on Social Assistive Robotics.

Sensors (Basel, Switzerland)
Using Automated Planning for the high level control of robotic architectures is becoming very popular thanks mainly to its capability to define the tasks to perform in a declarative way. However, classical planning tasks, even in its basic standard P...

Predictors of Toxicity Among Older Adults with Cancer.

Seminars in radiation oncology
An increasing number of cancer patients are of advanced age as the incidence of cancer increases with age. In this article, the clinical predictors of toxicity that may help in treatment selection are addressed, as well as mitigators of toxicity. The...

Frailty Identification Using Heart Rate Dynamics: A Deep Learning Approach.

IEEE journal of biomedical and health informatics
Previous research showed that frailty can influence autonomic nervous system and consequently heart rate response to physical activities, which can ultimately influence the homeostatic state among older adults. While most studies have focused on rest...

Determinants of Attitude to a Humanoid Social Robot in Care for Older Adults: A Post-Interaction Study.

Medical science monitor : international medical journal of experimental and clinical research
BACKGROUND While there is a growing body of research examining opinions on social robots in elderly care, there is a lack of comprehensive studies investigating the underlying factors influencing these opinions. The Godspeed Questionnaire Series (GQS...

Development and validation of machine learning models to predict frailty risk for elderly.

Journal of advanced nursing
AIMS: Early identification and intervention of the frailty of the elderly will help lighten the burden of social medical care and improve the quality of life of the elderly. Therefore, we used machine learning (ML) algorithm to develop models to pred...

Machine-learning classifier models for predicting sarcopenia in the elderly based on physical factors.

Geriatrics & gerontology international
AIM: As the size of the elderly population gradually increases, musculoskeletal disorders, such as sarcopenia, are increasing. Diagnostic techniques such as X-rays, computed tomography, and magnetic resonance imaging are used to predict and diagnose ...

Higher blood biochemistry-based biological age developed by advanced deep learning techniques is associated with frailty in geriatric rehabilitation inpatients: RESORT.

Experimental gerontology
BACKGROUND: Accelerated biological ageing is a major underlying mechanism of frailty development. This study aimed to investigate if the biological age measured by a blood biochemistry-based ageing clock is associated with frailty in geriatric rehabi...

Drug Burden Index Is a Modifiable Predictor of 30-Day Hospitalization in Community-Dwelling Older Adults With Complex Care Needs: Machine Learning Analysis of InterRAI Data.

The journals of gerontology. Series A, Biological sciences and medical sciences
BACKGROUND: Older adults (≥65 years) account for a disproportionately high proportion of hospitalization and in-hospital mortality, some of which may be avoidable. Although machine learning (ML) models have already been built and validated for predic...