Surveys

Reliability and validity of a novel single-lead portable electrocardiogram device for pregnant women: a comparative study.

BACKGROUND: WenXinWuYang, a novel portable Artificial Intelligence Electrocardiogram (AI-ECG) device, can detect many kinds of abnormal heart disease and perform a single-lead ECG, but its reliability and validity among pregnant women is unclear. The aim of this study was to assess the reliability and validity of heart rate, ECG measurements and diagnostic results by compared the portable device w...

Deep Reinforcement Learning in Human Activity Recognition: A Survey and Outlook.

Human activity recognition (HAR) is a popular research field in computer vision that has already been widely studied. However, it is still an active research field since it plays an important role in many current and emerging real-world intelligent systems, like visual surveillance and human-computer interaction. Deep reinforcement learning (DRL) has recently been used to address the activity reco...

Using explainable machine learning to investigate the relationship between childhood maltreatment, positive psychological traits, and CPTSD symptoms.

The functional impairment resulting from CPTSD symptoms is enduring and far-reaching. Existing research has found that CPTSD symptoms are closely ass...

Development and validation of a machine learning approach for screening new leprosy cases based on the leprosy suspicion questionnaire.

Leprosy is a dermatoneurological disease and can cause irreversible nerve damage. In addition to being able to mimic different rheumatological, neurol...

Utilization and perception of generative artificial intelligence by medical students in residency applications.

After completing medical school in the United States, most students apply to residency programs to progress in their training. The residency applicati...

MERIT: Multi-view evidential learning for reliable and interpretable liver fibrosis staging.

Accurate staging of liver fibrosis from magnetic resonance imaging (MRI) is crucial in clinical practice. While conventional methods often focus on a ...

A machine learning approach to feature selection and uncertainty analysis for biogas production in wastewater treatment plants.

The growing demand for efficient waste management solutions and renewable energy sources has driven research into predicting biogas production at wast...

AI in medical diagnosis: A contextualised study of patient motivations and concerns.

Patients' reactions to the implementation of Artificial Intelligence (AI) in healthcare range from adverse to favourable. While AI holds the promise o...

Optimized machine learning framework for cardiovascular disease diagnosis: a novel ethical perspective.

Alignment of advanced cutting-edge technologies such as Artificial Intelligence (AI) has emerged as a significant driving force to achieve greater pre...

Exploring the capabilities of GenAI for oral cancer consultations in remote consultations : Author.

BACKGROUND: Generative artificial intelligence (GenAI) has demonstrated potential in remote consultations, yet its capacity to comprehend oral cancer ...

LSTM and ResNet18 for optimized ambulance routing and traffic signal control in emergency situations.

Traffic congestion, particularly in rapidly expanding urban centers, significantly impacts the timely delivery of emergency medical services (EMS), wh...

Research on key factors influencing Chinese designers' use of AIGC: An extension based on TAM and TRI.

With the rapid development of AI intelligent technology, AIGC can bring an innovative revolution to art creation, providing designers with unlimited p...

A simple clustering approach to map the human brain's cortical semantic network organization during task.

Constructing task-state large-scale brain networks can enhance our understanding of the organization of brain functions during cognitive tasks. The pr...

Artificial Intelligence (AI) - Powered Documentation Systems in Healthcare: A Systematic Review.

Artificial Intelligence (AI) driven documentation systems are positioned to enhance documentation efficiency and reduce documentation burden in the he...

Using artificial intelligence tools for data quality evaluation in the context of microplastic human health risk assessments.

Concerns about the negative impacts of microplastics on human health are increasing in society, while exposure and risk assessments require high-quali...

Stress management with HRV following AI, semantic ontology, genetic algorithm and tree explainer.

Heart Rate Variability (HRV) serves as a vital marker of stress levels, with lower HRV indicating higher stress. It measures the variation in the time...

Robot-Assisted Approach to Diabetes Care Consultations: Enhancing Patient Engagement and Identifying Therapeutic Issues.

: Diabetes is a rapidly increasing global health challenge compounded by a critical shortage of diabetes care and education specialists. Robot-assiste...

Reliability-enhanced data cleaning in biomedical machine learning using inductive conformal prediction.

Accurately labeling large datasets is important for biomedical machine learning yet challenging while modern data augmentation methods may generate no...

A novel method for assessing cycling movement status: an exploratory study integrating deep learning and signal processing technologies.

This study proposes a deep learning-based motion assessment method that integrates the pose estimation algorithm (Keypoint RCNN) with signal processin...

UnBias: Unveiling Bias Implications in Deep Learning Models for Healthcare Applications.

The rapid integration of deep learning-powered artificial intelligence systems in diverse applications such as healthcare, credit assessment, employme...