Breast cancer remains a leading cause of cancer-related mortality among women worldwide. Mammography is the cornerstone of population-based breast cancer screening, significantly improving prognosis and survival outcomes. However, limitations related...
Background: The integration of artificial intelligence (AI) into lung cancer screening offers significant potential; however, public adoption of AI-assisted lung cancer screening remains inconsistent and poorly understood. A robust understanding of t...
Background/Objectives: This study assesses the cost-effectiveness of integrating artificial intelligence (AI) into breast cancer screening programs in Singapore. It evaluates AI as a standalone reader and as a companion reader alongside a consultant...
Background/Objectives: Lung cancer remains the leading cause of cancer-related mortality worldwide among both men and women. Early and accurate detection is essential to improve patient outcomes. This study explores the use of artificial intelligence...
Cancer is one of the biggest health burdens for women in the Middle East and North Africa (MENA), with the incidence of breast, cervical and colorectal cancer on the rise. Although preventive measures such as the HPV vaccination and population-based...
Background/Objectives: Artificial intelligence (AI)-enabled digital interventions are increasingly used to expand access to mental health care. This PRISMA-ScR scoping review maps how AI technologies support mental health care across five phases: pre...
The prevalence of oral potentially malignant disorders (OPMDs) and oral cancer is surging in low- and middle-income countries. A lack of resources for population screening in remote locations delays the detection of these lesions in the early stages...
Systematic reviews require labor-intensive screening processes—an approach prone to bottlenecks, delays, and scalability constraints in large-scale reviews. Large Language Models (LLMs) have recently emerged as a powerful alternative, capable o...
As climate change transforms our environment and human intrusion into natural ecosystems escalates, there is a growing demand for disease spread models to forecast and plan for the next zoonotic disease outbreak. Accurate parametrization of these mod...
Cervical cancer is a common and preventable disease that poses a significant threat to women’s health and well-being. It is the fourth most prevalent cancer among women worldwide, with approximately 604,000 new cases and 342,000 deaths in 2020,...
Early detection and accurate diagnosis of leukemia pose significant challenges due to the disease’s complexity and the need for minimally invasive methods. Acute myeloid leukemia (AML) accounts for most cases of adult leukemia, and our goal is...
Early identification of reading difficulties enables timely classroom intervention; however, teachers often have limited time and restricted access to specialist assessment. This study explores a brief, teacher-friendly screening approach based on sh...
Background: Sickle cell disease (SCD) is a prevalent hereditary hemoglobinopathy associated with substantial morbidity, particularly in regions with limited access to advanced laboratory diagnostics. Conventional diagnostic workflows, including manua...
Secure exchange of electronic health records (EHRs) requires clinical confidentiality, verifiable provenance, patient-controlled authorization, and practical handling of high-resolution medical imaging payloads generated by IoMT digital radiography s...
Municipal sewage sludge is an environmental liability but also an energy-rich biomass that can support circular economy resource recovery. Here, we benchmark thin-layer drying of dewatered municipal sewage sludge (sludge cake) (40 g; layer thickness...
Background: Colonoscopy remains the gold standard for colorectal cancer screening. Deep learning systems with real-time computer-aided polyp detection (CADe) demonstrate high accuracy in controlled research settings and preliminary randomized control...
Introduction: Lung cancer remains a major cause of cancer-related death; prompt detection and monitoring of pulmonary nodules through computed tomography (CT) is critical to prevent mortality. CT interpretation is time-intensive and can be prone to f...
The heavy global burden and mortality of breast cancer emphasize the importance of early diagnosis and treatment. Imaging detection is one of the main tools used in clinical practice for screening, diagnosis, and treatment efficacy evaluation, and ca...
Background: Ultrasound is the gold standard for the screening of developmental dysplasia of the hip (DDH). However, there are several problems in overcoming the learning curve of technical skills required to detect DDH using ultrasound. Thus, several...
Colorectal cancer (CRC) remains a major global health burden, necessitating continuous advancements in diagnostic methodologies. Traditional screening techniques, including barium enema and fecal occult blood tests, have been progressively replaced b...
Background: Non-specific low back pain (LBP) is a widespread condition with significant impacts on physical activity, muscle strength, psychological well-being, and economic status. Traditional physiotherapy shows variable efficacy, prompting growing...
The accuracy of artificial intelligence (AI)-assisted discrimination of oral cancerous lesions from normal mucosa based on mucosal images was evaluated. Two authors independently reviewed the database until June 2022. Oral mucosal disorder, as record...
Background: Artificial intelligence has revolutionized the field of dentistry. This systematic review evaluated the clinical performance of artificial intelligence (AI)-assisted cephalometric tracing compared with manual or expert digital tracing. Me...
Background: Periodontal charting remains the gold standard for periodontal diagnosis but is time-consuming, operator-dependent, and not always feasible in routine clinical practice. In contrast, panoramic radiographs are widely available and increasi...
Industrial sustainability assessment needs a transparent and operational framework that can manage multidimensional indicators, expert uncertainty, weighting complexity, and managerial interpretation. This research presents the Sustainable Industrial...
Low-dose computed tomography (LDCT) has emerged as a standard method for detecting early-stage lung cancer. However, the tedious computer tomography (CT) slide reading, patient-by-patient check, and lack of standard criteria to determine the vague bu...
Screening for retinal disease is increasingly performed by general practitioners and other non-ophthalmologist clinicians in primary care, especially where access to ophthalmology is limited and diagnostic accuracy may be suboptimal. To investigate t...
The rising global incidence of cervical cancer is estimated to have affected more than 600,000 women, and nearly 350,000 women are predicted to have died from the disease in 2020 alone. Novel advances in cancer prevention, screening, diagnosis and tr...
Wellbore fluid flow and heat transfer are strongly coupled during drilling and well construction, where temperature, pressure, rheology, gas behavior, transient operations, and cementing displacement jointly affect pressure-window control and wellbor...
Background: Developmental coordination Disorder (DCD) is a prevalent and persistent neurodevelopmental condition characterized by motor learning difficulties that significantly affect daily functioning and participation. Despite growing interest in a...
Background and Objectives: Advances in digital dentistry, particularly CAD-CAM, have improved the efficiency and precision of crown design and fabrication. Recently, artificial intelligence (AI)-integrated CAD-CAM systems have enabled automated tooth...
This AI-assisted integrative literature review, grounded in complexity theory, examines how existing scholarship conceptualizes the potential of scenario planning to support future-ready mindsets, shared language, symbolic anchors, and adaptive capac...
Artificial intelligence (AI) has gained prominence in medical imaging, particularly in obstetrics and gynecology (OB/GYN), where ultrasound (US) is the preferred method. It is considered cost effective and easily accessible but is time consuming and...
This study proposes a stage-aware governance framework for large language models (LLMs) that structures human oversight and accountability across different decision stages in AI-assisted literature review systems. Large language models (LLMs) are inc...
Ultrasound examination using the Graf method is widely applied for early detection of developmental dysplasia of the hip (DDH), but intra- and inter-operator variability remains a limitation. This study aimed to quantify operator variability in hip u...
The coronavirus disease 2019 (COVID-19) pandemic highlighted the need for rapid, accurate, and point-of-care diagnostic technologies, accelerating interest in biosensors as next-generation analytical platforms. However, biosensor performance is gover...
Background: Breast cancer (BC) is one of the most diagnosed malignancies and a leading cause of cancer-related mortality among women worldwide, thereby posing a substantial threat to women’s health worldwide. However, clinically robust diagnost...
Cervical cancer remains a major global health challenge, particularly in low- and middle-income countries, where access to screening, vaccination, and timely treatment may be limited. Cervical cytology has played an important historical role in preve...
The development of artificial intelligence (AI) algorithms has permeated the medical field with great success. The widespread use of AI technology in diagnosing and treating several types of cancer, especially colorectal cancer (CRC), is now attracti...
Background: Artificial intelligence (AI) is increasingly used in forensic firearm evidence analysis to improve pattern recognition, automation, and analytical efficiency. Despite advances in machine learning (ML) and deep learning (DL), limitations i...
The application of artificial intelligence (AI) is accelerating the paradigm shift towards patient-tailored brain tumor management, achieving optimal onco-functional balance for each individual. AI-based models can positively impact different stages...
Generative AI systems increasingly mediate how students retrieve literature and generate citations, shifting methodological rigor toward the maintenance of an auditable evidence trail. This study audits the search stage of AI-assisted literature revi...
Background/Objectives: Artificial intelligence (AI) shows promise in supporting mammography interpretation and triaging referrals, potentially enhancing breast screening. However, successful AI integration depends on patient acceptance and trust. Thi...
Background/Objectives: Concern that COVID-19 vaccination causes pulmonary nodules persists because vaccination coincided with expanded computed tomography (CT), low-dose CT (LDCT) screening, post-COVID imaging and artificial intelligence (AI)-assiste...
Artificial intelligence (AI) is increasingly being applied in healthcare, with growing relevance to clinical nutrition. This narrative review examines current and emerging uses of AI in nutrition care within the Nutrition Care Process framework, with...
The development of drug delivery systems (DDSs) is moving from empirical, trial-and-error formulation toward data-driven, artificial intelligence (AI)-guided, and automated workflows. Microfluidics provides precise control of microscale fluids, enabl...
Background/Objectives: Artificial intelligence (AI) is increasingly being integrated into vascular surgery, particularly in diagnostic imaging, perioperative planning, intraoperative guidance, and postoperative surveillance. This literature review ev...
Background: The eye provides a valuable window for the identification of neurological diseases, as pathological changes may involve both the retina and the optic nerve. Standard imaging of the retina and the optic nerve are non-invasive and are usefu...
Optical biopsy in Barrett’s oesophagus (BE) using endocytoscopy (EC) could optimize endoscopic screening. However, the identification of dysplasia is challenging due to the complex interpretation of the highly detailed images. Therefore, we ass...
Point-of-care electroencephalography (POC-EEG) systems are rapid-access, reduced-montage devices designed to address the limitations of conventional EEG (conv-EEG), enabling faster neurophysiological assessment in acute settings. This review evaluate...
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