Surveys

Home-care robots - Attitudes and perceptions among older people, carers and care professionals in Ireland: A questionnaire study.

Many countries face major challenges to ensure that their health and social care systems are ready for the growing numbers of older people (OP). As a way of realising ageing in place, assistive technologies such as home-care robots are expected to play a greater role in the future. In Asia and Europe, robots are gradually being adopted as a public policy solution to the workforce shortage. Yet, th...

A comprehensive review and analysis of supervised-learning and soft computing techniques for stress diagnosis in humans.

Stress is the most prevailing and global psychological condition that inevitably disrupts the mood and behavior of individuals. Chronic stress may gravely affect the physical, mental, and social behavior of victims and consequently induce myriad critical human disorders. Herein, a review has been presented where supervised learning (SL) and soft computing (SC) techniques used in stress diagnosis h...

Ensuring that biomedical AI benefits diverse populations.

Artificial Intelligence (AI) can potentially impact many aspects of human health, from basic research discovery to individual health assessment. It is...

Applications of Artificial Intelligence for Static Poisson's Ratio Prediction While Drilling.

The prediction of continued profile for static Poisson's ratio is quite expensive and requires huge experimental works, and the discontinuity in the m...

Reducing Loneliness in Stationary Geriatric Care with Robots and Virtual Encounters-A Contribution to the COVID-19 Pandemic.

The bans on visiting nursing homes during the COVID-19 pandemic, while intended to protect residents, also have the risk of increasing the loneliness ...

Predicting drug metabolism and pharmacokinetics features of in-house compounds by a hybrid machine-learning model.

We constructed machine learning-based pharmacokinetic prediction models with very high performance. The models were trained on 26138 and 16613 compoun...

Addressing Fairness, Bias, and Appropriate Use of Artificial Intelligence and Machine Learning in Global Health.

In Low- and Middle- Income Countries (LMICs), machine learning (ML) and artificial intelligence (AI) offer attractive solutions to address the shortag...

Machine Learning in Clinical Psychology and Psychotherapy Education: A Mixed Methods Pilot Survey of Postgraduate Students at a Swiss University.

There is increasing use of psychotherapy apps in mental health care. This mixed methods pilot study aimed to explore postgraduate clinical psycholog...

A convolutional neural network to identify motor units from high-density surface electromyography signals in real time.

. This paper aims to investigate the feasibility and the validity of applying deep convolutional neural networks (CNN) to identify motor unit (MU) spi...

Extracting Cause of Death From Verbal Autopsy With Deep Learning Interpretable Methods.

The international standard to ascertain the cause of death is medical certification. However, in many low and middle-income countries, the majority of...

Applying deep learning in digital breast tomosynthesis for automatic breast cancer detection: A review.

The relatively recent reintroduction of deep learning has been a revolutionary force in the interpretation of diagnostic imaging studies. However, the...

Development and feasibility of a soft pneumatic-robotic glove to assist impaired hand function in quadriplegia patients: A pilot study.

One of the common disorders in people with quadriplegia is having a weak grip strength that can affect activities of daily living (ADL). This study pr...

Predicting innovative firms using web mining and deep learning.

Evidence-based STI (science, technology, and innovation) policy making requires accurate indicators of innovation in order to promote economic growth....

Reducing bias to source samples for unsupervised domain adaptation.

Unsupervised Domain Adaptation (UDA) makes predictions for the target domain data while labels are only available in the source domain. Lots of works ...

An Automated High-Accuracy Detection Scheme for Myocardial Ischemia Based on Multi-Lead Long-Interval ECG and Choi-Williams Time-Frequency Analysis Incorporating a Multi-Class SVM Classifier.

Cardiovascular Disease (CVD) is a primary cause of heart problems such as angina and myocardial ischemia. The detection of the stage of CVD is vital f...

Protocol for a reproducible experimental survey on biomedical sentence similarity.

Measuring semantic similarity between sentences is a significant task in the fields of Natural Language Processing (NLP), Information Retrieval (IR), ...

Predicting Emotional States Using Behavioral Markers Derived From Passively Sensed Data: Data-Driven Machine Learning Approach.

BACKGROUND: Mental health disorders affect multiple aspects of patients' lives, including mood, cognition, and behavior. eHealth and mobile health (mH...

Validation of a Novel Simulation-Based Test in Robot-Assisted Radical Prostatectomy.

To investigate validity evidence for a simulator-based test in robot-assisted radical prostatectomy (RARP). The test consisted of three modules on t...

Application of artificial intelligence in diagnosis of osteoporosis using medical images: a systematic review and meta-analysis.

Artificial intelligence (AI) is a potentially reliable assistant in the diagnosis of osteoporosis. This meta-analysis aims to assess the diagnostic ac...

Machine learning algorithms trained with pre-hospital acquired history-taking data can accurately differentiate diagnoses in patients with hip complaints.

Background and purpose - Machine learning (ML) techniques are a form of artificial intelligence able to analyze big data. Analyzing the outcome of (di...