AI Medical Compendium Journal:
Informatics for health & social care

Showing 1 to 10 of 13 articles

Identifying biological markers and sociodemographic factors that influence the gap between phenotypic and chronological ages.

Informatics for health & social care
INTRODUCTION: The world's population is aging rapidly, leading to increased public health and economic burdens due to age-related cardiovascular and neurodegenerative diseases. Early risk detection is essential for prevention and to improve the quali...

How satisfied are patients with nursing care and why? A comprehensive study based on social media and opinion mining.

Informatics for health & social care
To assess the overall experience of a patient in a hospital, many factors must be analyzed; nonetheless, one of the key aspects is the performance of nurses as they closely interact with patients on many occasions. Nurses carry out many tasks that co...

Promoting activity in long-term care facilities with the social robot Pepper: a pilot study.

Informatics for health & social care
About 40 000 individuals depend on assisted living in long-term care facilities in Norway. Around 80% of these have a cognitive impairment or suffer from dementia. This actualizes the need for activities that are tailored to individual needs. For som...

Machine learning and natural language processing to identify falls in electronic patient care records from ambulance attendances.

Informatics for health & social care
We derived machine learning models utilizing features generated by natural language processing (NLP) of free-text data from an ambulance services provider to identify fall cases. The data comprised samples of electronic patient care records care reco...

Intelligent type 2 diabetes risk prediction from administrative claim data.

Informatics for health & social care
Type 2 diabetes is a chronic, costly disease and is a serious global population health problem. Yet, the disease is well manageable and preventable if there is an early warning. This study aims to apply supervised machine learning algorithms for deve...

Comparison of different predicting models to assist the diagnosis of spinal lesions.

Informatics for health & social care
In neurosurgical or orthopedic clinics, the differential diagnosis of lower back pain is often time-consuming and costly. This is especially true when there are several candidate diagnoses with similar symptoms that might confuse clinic physicians. T...

Model and variable selection using machine learning methods with applications to childhood stunting in Bangladesh.

Informatics for health & social care
Childhood stunting is a serious public health concern in Bangladesh. Earlier research used conventional statistical methods to identify the risk factors of stunting, and very little is known about the applications and usefulness of machine learning (...

Machine learning approaches to constructing predictive models of vitamin D deficiency in a hypertensive population: a comparative study.

Informatics for health & social care
Given the association between vitamin D deficiency and risk for cardiovascular disease, we used machine learning approaches to establish a model to predict the probability of deficiency. Determination of serum levels of 25-hydroxy vitamin D (25(OH)D...

Users' ambivalent sense of security with humanoid robots in healthcare.

Informatics for health & social care
Humanoid robots have already been shown to be useful in healthcare. To ensure successful interactions with humanoid robots, is it essential that the factors that influence users' sense of security be understood. Ensuring patients' sense of security i...

Predicting treatment outcome of drug-susceptible tuberculosis patients using machine-learning models.

Informatics for health & social care
Tuberculosis (TB) is a deadly contagious disease and a serious global health problem. It is curable but due to its lengthy treatment process, a patient is likely to leave the treatment incomplete, leading to a more lethal, drug resistant form of dise...