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ISSN: 2949-9534

Health informatics to enhance the healthcare industry's culture: An extensive analysis of its features, contributions, applications and limitations

Health informatics is a fast-growing area in the healthcare sector. It concerns the technologies, tools, equipment, and procedures required to gather, store, retrieve, and use health data and medical...

Next-generation agentic AI for transforming healthcare

Artificial Intelligence (AI) is transforming the healthcare landscape, yet many current applications remain narrowly task-specific, constrained by data complexity and inherent biases. This paper explores...

Nursing in the Digital Age: Harnessing telemedicine for enhanced patient care

Telemedicine has emerged as a transformative force in contemporary healthcare, reshaping nursing practice across various specialties. This narrative review explored the role, challenges, and ethical...

Telemedicine use in rural areas of the United Kingdom to improve access to healthcare facilities: A review of current evidence

Rural populations in the UK face healthcare inequities despite the NHS's aim of providing universal healthcare. These disparities include restricted access, transportation challenges, and healthcare...

An Agentic AI system for disease diagnosis with explanations

With the increasing complexities in the medical domain, the demand for autonomous, adaptable, scalable, and personalized Artificial Intelligence (AI)-based disease diagnostic systems is growing. However,...

What is digital health, eHealth, uHealth and Healthcare 4.0?

As digital health continues to evolve, the need for ongoing refinement of its terminology remains essential. A perspective piece originated from the authors' attempt to answer the seemingly simple question,...

Predicting diabetes using supervised machine learning algorithms on E-health records

Diabetes mellitus is one of the most significant health challenges currently faced by people especially in the United States of America because of hyperglycemia. Despite recent research on predicting...

Assessing the challenges to digital technology adoption in the healthcare sector: Implications for sustainability in emerging economies

The exponential population growth over the last two decades, combined with increased life expectancy, has placed unsustainable pressure on healthcare systems in emerging economies like Bangladesh. Despite...

Enhancing teaching and learning in health sciences education through the integration of Bloom's taxonomy and artificial intelligence

The purpose of this research is to integrate artificial intelligence (AI) in Bloom's Taxonomy with the aim of improving critical thinking in health science education. Innovative teaching approaches...

Advancing public health through artificial intelligence in physiotherapy: a bibliometric analysis

This scientometric study investigates global trends and applications of artificial intelligence (AI) in physiotherapy, including rehabilitation, movement analysis, and telerehabilitation, between 2006...

Role of data as an interface between primary, secondary and tertiary care: Evidence from literature

The healthcare system relies on efficient data flow across primary, secondary, and tertiary care levels to ensure timely and effective patient care. However, despite the growing body of research on...

The impact analysis of digital transformation on upper-middle-class hospital performance through business model innovation

This study investigates the influence of digital transformation (DT) and resource integration (RI) on hospital performance (HP) in upper-middle-class hospitals in Indonesia, with business model innovation...

Artificial intelligence in modern healthcare: Applications, innovations, and ethical dimensions in personalized, predictive, and inclusive care

Artificial intelligence (AI) in healthcare is evolving from narrow single-task models to multimodal systems that integrate text, images, physiological signals, and structured clinical records. This...

Digital transformation for sustainable healthcare education: Evaluating the impact of Moodle learning management system on ICD-11 training

The Malaysian Ministry of Health (MOH) adopted the International Classification of Diseases Eleventh Revision (ICD-11) and used a Moodle learning management system (LMS) for clinical coder training,...

AIDA: A health informatics-oriented adaptive cybersecurity framework for clinically aware detection and response in healthcare

Healthcare organizations increasingly depend on integrated electronic health records, connected medical devices, and identity-aware clinical workflows, yet these health informatics systems remain vulnerable...

LA-TextCNN-BiLSTM: A classification model for ICD-11

A model for ICD-11 automatic coding is proposed for the problem of ICD-11 automatic coding to further improve the coding performance....

Impact of GOTHOMIS on healthcare transformation in Tanzania: Insights from digital health stakeholders

Many low- and middle-income countries have invested in digital health information systems to improve service delivery, reporting, and decision-making. However, evidence on whether such systems translate...

Explainability enhanced liver disease diagnosis technique using tree selection and stacking ensemble-based random forest model

Liver disease (LD) significantly impacts global health, requiring accurate diagnostic methods. This study aims to develop an automated system for LD prediction using machine learning (ML) and explainable...

An explainable ensemble learning framework for ovarian cancer classification using blood biomarkers

Background Ovarian cancer remains one of the most lethal gynecological malignancies, largely due to delayed diagnosis and the limited sensitivity of conventional screening approaches. Methods This study...

Optimizing the light gradient-boosting machine algorithm for an efficient early detection of coronary heart disease

Coronary heart disease (CHD) remains a prominent cause of mortality globally, necessitating early and accurate detection methods. Traditional diagnostic approaches can be invasive, costly, and time-consuming,...

Data privacy in EHR systems: A TCCM systematic literature review of practices in developing countries

To examine how data privacy is addressed in electronic health record (EHR) systems across developing countries using the TCCM (Theory-Context-Characteristics-Methodology) framework....

A novel attention-enhanced hybrid deep learning approach for malaria diagnosis in microscopic cell images

Malaria remains a major global public health challenge, transmitted through the bites of infected female mosquitoes. Despite progress in prevention and treatment, the disease continues to cause significant...

ICD-11 in global public health surveillance: Advancements in infectious disease tracking, non-communicable disease management, and antimicrobial resistance monitoring

As medical knowledge continues to evolve, the limitations of the International Classification of Diseases, 10th Revision (ICD-10), in supporting public health surveillance and reporting have become...

Predicting diabetes related complications in Alberta, Canada for health jurisdictions: A machine learning prediction approach

Diabetes-related complications pose significant burdens on healthcare systems, necessitating effective predictive tools for early intervention. In the Canadian healthcare context, leveraging population-level...

Large language models driven reliable clinical decision-making: Framework and application

With the proliferation of data and increased complexity of clinical decision-making in the medical field, powerful computational tools are needed to assist physicians in making precise and reliable...

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