Recent Articles

Open access

ISSN: 3050-8371

Evaluation of electronic medical records risk management in Kudus hospitals: A comparative qualitative study

The rapid expansion of digital health infrastructure has positioned electronic medical records (EMR) as a core element of service continuity, clinical decision-making, and data governance, yet the maturity...

Deep learning for early detection of depression and anxiety: A comparative study of CNN, LSTM, and RNN models

Depressive and anxiety disorders have been ranked among the most important public health problems and have been a concern for all age groups, reducing the quality of life of individuals. Commonly used...

Enhancing systemic anti-cancer therapy delivery through early screening and workflow optimisation: A two-cycle service evaluation in a UK cancer centre

Timely administration of systemic anti-cancer therapy (SACT) is essential for optimal oncological outcomes (1). Pre-treatment screening plays a critical role in ensuring fitness for therapy; however,...

Integrative analysis of gut microbiome and treatment outcomes in nephrotic syndrome: The future of AI/ML driven approaches in disease prediction

Nephrotic syndrome (NS) is an immune-mediated kidney disease; it is characterized by colossal proteinuria, low albumin, pitting, and frequent relapses encountered predominantly in children. Although...

Digital twins to improve clinical trial design and patient satisfaction in oncology

Digital Twin (DT) technology, originally developed for engineering and manufacturing applications, is being repurposed for groundbreaking oncology applications. This review describes how DTs enhance...

Interpretable LightGBM framework for predicting esophageal cancer using clinical data: Integrating ensemble feature selection and data balancing

Esophageal cancer is a very aggressive cancer with low chances of survival mainly because of late diagnosis and complexity in clinical heterogeneity. In spite of promising results in terms of early...

Recent approaches of artificial intelligence in intensive care unit: A review

Complex environment of the intensive care unit (ICU), prompt and precise decision-making is essential to patient survival. Healthcare providers face issue including information overload, delayed decision...

An overview of water and environmental pollutants and hospital wastes

Nowadays, one of the biggest challenges of mankind is to obtain safe drinking water. Due to the limited access to healthy water resources and the development of human societies, the increasing need...

Artificial Intelligence and precision medicine for optimizing patient care: A comprehensive review

Precision medicine is a state-of-the-art approach in healthcare that involves tailoring treatments for a subset of individuals with similar sensitivity to a drug or shared susceptibility to a disease....

Advanced anti-biofilm technologies for biomedical devices: Integrating nanomaterials, AI, and stimuli-responsive therapeutics

The control of biofilm-related infection on biomedical devices continues to pose a significant clinical challenge due to microorganism biofilm structural resilience and its tolerance to antimicrobials....

Digital twin technologies in medicine: The innovations, barriers, and future directions

Digital Twin technology revolutionizes modern medicine with the creation of real-time virtual models of patients, organs, and healthcare systems; all of these improve diagnosis, treatment, and management....

Explainable machine and deep learning framework for newborn health monitoring: A simulation-based approach

Machine learning and deep learning techniques are increasingly being adopted in neonatal health research to improve early risk detection and support clinical decision-making. Progress, however, is limited...

Examining the cause–and–effect linkages among eco-innovation enablers for advancing sustainable hospital infrastructure: An MCDM Approach

Eco-innovation is the creation and application of new or highly enhanced products, processes, services, or organisational processes that reduce environmental impacts and innovatively maximise resource...

Evaluating current trends in stress and depression detection using artificial intelligence and machine learning

Stress and depression are two major mental health-related concerns that affect people of varying ages, ranging from teenagers to working class people to senior citizens. The detection of these conditions...

Optimizing hospital bed capacity: How lean-AI integration prevents capacity constraints from multiplying demand

Hospital bed management requires optimizing occupancy levels while maintaining sufficient surge capacity to prevent patient boarding and extended wait times. Industry guidelines target 80–85 % occupancy,...

Modeling enablers of artificial intelligence adoption in smart hospitals: An ISM–MICMAC analysis

The integration of Artificial Intelligence (AI) into healthcare systems has become a vital element of digital transformation, enabling smart hospitals to enhance clinical efficiency, diagnostic accuracy,...

Cardiologists’ insights on AI integration in Nigeria’s cardiac healthcare landscape: A qualitative study

Artificial Intelligence (AI) offers transformative potential in cardiology by enhancing diagnostic precision, improving workflow efficiency, and expanding access to care. However, in low- and middle-income...

AI and ML applications for predicting mortality in osteoporotic fracture patients: A scoping review

Osteoporotic fractures are associated with elevated risks of mortality, particularly among older adults. Artificial intelligence (AI) and machine learning (ML) applications have been increasingly used...

Barriers to adopting Additive Manufacturing in healthcare: An analysis towards their mitigation

Additive Manufacturing (AM) is transforming healthcare by producing customised and intricate medical devices that were previously impossible to produce using traditional manufacturing systems. However,...

Artificial intelligence and robotics in intensive care units (ICUs): A review of critical care innovations

Critical care delivery is undergoing a radical transformation with the integration of AI and robotics into the intensive care unit (ICU) workflow. An extensive summary of recent developments, applications,...

Analysing the barriers to adoption of telemedicine in healthcare sector using fuzzy DEMATEL method

Telemedicine has transformed the healthcare sector as it makes healthcare accessible to the patients in regions where access to healthcare facilities is limited, reduces overall costs, and enables faster...

An early detection of learning disabilities using machine learning: A comparative study of models, datasets, and diagnostic strategies

Learning disabilities (LDs) affect a big portion of the school-age population, which often results in long-term academic and social difficulties. Early identification and timely intervention may lead...

Telepharmacy in hospital pharmacy: Implementation, challenges, and future directions

Telepharmacy is a growing field that supports hospital pharmacists in providing effective service to patients remotely using digital technologies. Telepharmacy enhances patient care in hospitals or...

Blockchain and the metaverse: A dual-tech approach to transforming medical data and patient care

The advancement of the metaverse and the application of blockchain technology in the medical field is probably going to cause a revolution. The concept of the metaverse that enables the integration...

Understanding the causal relationships among healthcare technologies when enabled through IoT: Analysing through the MCDM Approach

The introduction of the Internet of Things (IoT) has revolutionised the healthcare sector through diverse applications. It enables patients to receive prompt healthcare reliably, offering a better value...

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