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ISSN: 2588-9141

“The role of telemedicine and e-Health applications in Nursing: A systematic review of global practices (2018–2024)”

The rapid advancement of Information Technology has significantly transformed healthcare delivery, influencing both patients and healthcare professionals. Telemedicine and e-Health applications have...

Advancements in digital data acquisition and CAD technology in Dentistry: Innovation, clinical Impact, and promising integration of artificial intelligence

This review examines recent advancements in digital data acquisition and CAD technology in dentistry, highlighting improvements in communication, AI integration, and predictive analytics in diagnostic...

Advancing healthcare with generative AI and large language models: a systematic review of applications in medical imaging, patient communication, and global innovation

Large language models (LLMs), Generative AI (GAI), and Generative Vision Models (GVMs) have become transformative technologies in healthcare, offering new landscapes for diagnostics, patient communication,...

Agentic AI system for generating evidence-based second medical opinions

Second medical opinions play a critical role in reducing diagnostic uncertainty and supporting high-stakes clinical decision-making. However, healthcare systems often struggle to provide them in a timely...

Securing electronic health records using blockchain-enabled federated learning for IoT-based smart healthcare

The integration of smart city applications with healthcare has revolutionized patient monitoring and medical data management. However, ensuring the privacy and security of Electronic Health Records...

Post pandemic analysis on comprehensive utilization of telehealth and telemedicine

The existing global health crisis characterized by limited resources, including health personnel, has prompted the adoption of telemedicine and telehealth, especially in the post-pandemic era. The COVID-19...

Attitude and perceptions of healthcare professionals towards digital health technologies: a cross-sectional study

To assess healthcare professionals’ (HCPs) attitudes and perceptions towards digital health technologies (DHTs) and identify predictors of willingness to adopt DHTs in a tertiary care setting....

Autonomous AI for Diabetic Retinopathy Screening: Evidence, Regulation, and Health-System Fit

Background: Diabetic retinopathy is a preventable cause of vision loss, but screening coverage is limited when retinal imaging, expert interpretation, referral completion, and access to treatment are...

A comprehensive study on skin cancer detection using artificial neural network (ANN) and convolutional neural network (CNN)

Skin cancer is a significant health risk that requires early detection for effective treatment. This paper discusses two automated techniques, Artificial Neural Network (ANN) and Convolutional Neural...

Personalizing nutrition and recipe recommendation using attention mechanism with an ensemble model

Nutrient management in the context of this proposed work aims to quantize the consumption of essential nutrients in an efficient format such that it leads to a healthy and balanced lifestyle. This paper...

Concept and prospect of the Human-Computer Multi-Disciplinary team (MDT) in pulmonary nodule evaluation

Lung cancer is the leading cause of cancer-related deaths worldwide. Early diagnosis and treatment play a crucial role in improving the prognosis for lung cancer. However, the issue of overtreatment...

Usability evaluation of wearable technology: A pilot study on a smart diabetic shoe for foot care

Smart diabetic shoes can be essential in preventing and monitoring foot ulcers. We developed a smart diabetic shoe to monitor pressure, temperature, and humidity and send the data to patients’ phones...

An explainable machine learning framework for obesity classification with optimized support vector machines

Post-COVID obesity has emerged as a significant public health challenge in Dhaka, driven by a complex interplay of socio-economic, lifestyle, and environmental factors that were exacerbated during the...

Enhancing thyroid disease prediction and comorbidity management through advanced machine learning frameworks

Thyroid disease is one of the most prevalent endocrine disorders worldwide, necessitating precise and efficient diagnostic models for improved clinical outcomes. This study proposes a Hybrid Feature...

Expert consensus on the evaluation and management of high-risk indeterminate pulmonary nodules

The most effective method for improving the prognosis of lung cancer is the application of low-dose computed tomography (LDCT) for pulmonary nodule screening in populations at high risk. Timely diagnosis...

Telemedicine transitional care programs: effects on readmissions and patient experience

•Higher star ratings of care transitions are associated with reduced 30-day hospital readmission rates.•Patient telehealth benefits differ based on three main factors: facility, quality, and clinical...

Association between social media use and cyberchondria during the COVID-19 pandemic: a cross-sectional study

Cyberchondria is defined as an excessive or repeated online health-related information-seeking behavior exacerbated by information overload and quarantine, resulting in amplified health anxiety. A total...

An anatomization on breast cancer detection and diagnosis employing multi-layer perceptron neural network (MLP) and Convolutional neural network (CNN)

This paper aims to review Artificial neural networks, Multi-Layer Perceptron Neural network (MLP) and Convolutional Neural network (CNN) employed to detect breast malignancies for early diagnosis of...

DigiCAS-HPS: A tailored digital competence assessment scale for health professions students in the post-COVID era in Vietnam

The COVID-19 pandemic has accelerated the adoption of digital health, highlighting the critical role of digital health competencies in delivering reliable and effective healthcare services. These competencies...

Application of artificial intelligence in modern medicine

Over the last decade, artificial intelligence in medicine has attracted much attention and interest for its robust automation and efficiency in disease diagnosis, treatment and prognosis. It has shown...

Enhanced epilepsy detection using discrete wavelet transform and bandpass filtering on EEG data: integration of ART-based and LVQ models

Accurate detection of epileptic seizures from EEG signals is vital for early diagnosis and treatment of epilepsy. However, EEG signals are inherently nonstationary and noisy, posing significant challenges...

Healthcare 4.0: Opportunities and barriers in the implementation of medical equipment

This study investigates the opportunities and barriers in the implementation of medical equipment within the context of Healthcare 4.0, offering a comprehensive analysis based on the perspectives of...

The smart and healthy city business model Canvas—A post Covid-19 resilience for smart city business modeling framework

Cities must adopt clever solutions to address the health issues brought on by the COVID-19 pandemic and challenging population growth, as well as to meet the economic, social, and environmental concerns...

Acceptance of telehealth in the Kingdom of Saudi Arabia: an application of the UTAUT model

Understanding telehealth users’ acceptance is essential for ensuring effective implementation and may lead to successful, higher quality, and safer telehealth programs. Therefore, this study aimed to...

“AI et al.” The perils of overreliance on Artificial Intelligence by authors in scientific research

The rapid integration of Artificial Intelligence (AI) into scientific research and publication processes marks a significant shift in knowledge generation. This transition from traditional literature...

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