Artificial intelligence (AI) is poised to change much about the way we practice radiology in the near future. The power of AI tools has the potential to offer substantial benefit to patients. Conversely, there are dangers inherent in the deployment o...
Purpose: This systematic review explores the ethical, legal, and regulatory frameworks governing the deployment of artificial intelligence technologies in radiology. It aims to identify key governance challenges and highlight strategies that promote...
Radiology is undergoing a paradigm shift from traditional single-function AI systems to sophisticated multi-agent networks capable of autonomous reasoning, coordinated decision-making, and adaptive workflow management. These agentic AI systems move b...
The handling of incidental findings (IFs) in brain imaging studies has been a source of contention among scientists and bioethicists. A conceptual framework informed by diversity, equity, and inclusion (DEI) and distributive justice approaches, namel...
Background/Objectives: Artificial intelligence (AI) is increasingly being integrated into dental diagnostics, promising improved detection, efficiency, and patient communication. While these developments offer potential clinical benefits, emerging co...
This comprehensive review unfolds a detailed narrative of Artificial Intelligence (AI) making its foray into radiology, a move that is catalysing transformational shifts in the healthcare landscape. It traces the evolution of radiology, from the init...
Artificial intelligence (AI) is transforming dentomaxillofacial radiology education by enabling adaptive, personalized, and data-driven learning experiences. This review critically examines the pedagogical potential of AI within dental curricula, foc...
Radiological interpretations, while essential, are not infallible and are best understood as expert opinions formed through the evaluation of available evidence. Acknowledging the inherent possibility of error is crucial, as it frames the discussion...
(Background) Domiciliary radiology, which originated in pioneering studies in 1958, has transformed healthcare, particularly during the COVID-19 pandemic, through advancements such as miniaturization and digitization. This evolution, driven by the sy...
16 January 2023
The rise of artificial intelligence (AI) in medicine, and particularly in radiology, is becoming increasingly prominent. Its impact will transform the way the specialty is practiced and the current and future education model. The aim of this study is...
Artificial intelligence (AI) is reshaping radiological practice, with recent advancements in natural language processing (NLP), large language models (LLMs), and chatbot technologies opening new avenues for clinical integration. These AI-driven conve...
The advent of artificial intelligence (AI) is revolutionizing medicine, particularly radiology. With the development of newer models, AI applications are demonstrating improved performance and versatile utility in the clinical setting. Thoracic imagi...
Objectives: Artificial intelligence (AI) is a transformative development in the field of medicine. In the field of musculoskeletal radiology, agentic AI is a technology that could flourish, but currently, the limited evidence base is fragmented and s...
Advancements in artificial intelligence (AI) have significantly transformed the field of abdominal radiology, leading to an improvement in diagnostic and disease management capabilities. This narrative review seeks to evaluate the current standing of...
The application of chatbots and NLP in radiology is an emerging field, currently characterized by a growing body of research. An umbrella review has been proposed utilizing a standardized checklist and quality control procedure for including scientif...
Background/Objectives: Artificial intelligence (AI) is increasingly embedded within diagnostic imaging workflows, reshaping clinical decision-making, health system governance, and regulatory oversight. While technical advances in radiological AI have...
Artificial intelligence (AI) is revolutionarily shaping the entire landscape of medicine and particularly the privileged field of radiology, since it produces a significant amount of data, namely, images. Currently, AI implementation in radiology is...
Background: Metastasis commonly occur in the bone tissue. Artificial intelligence (AI) has become increasingly prevalent in the medical sector as support in decision-making, diagnosis, and treatment processes. The objective of this systematic review...
Multimodal technology is poised to revolutionize clinical practice by integrating artificial intelligence with traditional diagnostic modalities. This evolution traces its roots from Hippocrates’ humoral theory to the use of sophisticated AI-dr...
Background/Objectives: Federated learning (FL) offers a way for healthcare institutions to collaboratively train machine learning models without sharing sensitive patient data. This systematic review aims to comprehensively synthesize the ethical dim...
The widespread use of medical imaging techniques such as X-rays and computed tomography (CT) has raised significant concerns regarding ionizing radiation exposure, particularly among vulnerable populations requiring frequent imaging. Achieving a bala...
The application of chatbots and Natural Language Processing (NLP) in cytology and cytopathology is an emerging field, which is currently characterized by a limited but growing body of research. Here, a narrative review has been proposed utilizing a s...
Background: This paper aims to outline an ethical overview of the potential challenges related to AI technologies in the doctor–patient relationship. Methods: This study is structured as a narrative review of the literature (2015–2025), b...
The integration of artificial intelligence (AI) in cytopathology is an emerging field with transformative potential, aiming to enhance diagnostic precision and operational efficiency. This umbrella review seeks to identify prevailing themes, opportun...
Artificial intelligence (AI)-based object detection in radiology can assist in clinical diagnosis and treatment planning. This article examines the AI-based object detection models currently used in many imaging modalities, including X-ray Magnetic R...
The aim of this study was to analyze published works that investigate the in vivo bone regeneration capacity of polymeric membranes loaded with active substances and growth factors. This scoping review’s purpose was to highlight the histologica...
Background: Fractures in elderly patients are common and have severe implications on a socioeconomic level, as musculoskeletal integrity and competence is crucial for independence. Changes in both composition and biology of bones during aging potenti...
The integration of deep learning into radiology has the potential to enhance diagnostic processes, yet its acceptance in clinical practice remains limited due to various challenges. This study aimed to develop and evaluate a fine-tuned large language...
Artificial Intelligence (AI) is rapidly transforming medical education by enabling adaptive tutoring, interactive simulation, diagnostic enhancement, and competency-based assessment. This narrative review explores how AI has influenced learning proce...
The integration of artificial intelligence (AI) into healthcare practice has improved patient management and care. Many clinical laboratory specialties have already integrated AI in diagnostic specialties such as radiology and pathology, where it can...
Background: Anti-synthetase Syndrome (ASyS) is an idiopathic inflammatory myopathy characterized by muscle weakness and inflammatory infiltrates in muscles. Sjogren’s disease (SD) is an autoimmune condition primarily affecting exocrine glands....
Kidney allograft rejection is one of the main limitations to long-term kidney transplant survival. The diagnostic gold standard for detecting rejection is a kidney biopsy, an invasive procedure that can often give imprecise results due to complex dia...
Cancer remains one of the main global public health challenges, with rising incidence and mortality rates demanding more effective diagnostic and therapeutic approaches. Recent advances in artificial intelligence (AI) have positioned it as a transfor...
Catheter ablation is an established treatment method for atrial fibrillation. In most cases, the arrhythmia substrate is located within the pulmonary veins and their isolation has become the cornerstone of catheter ablation therapy. However, it is es...
Today, there is growing interest in artificial intelligence (AI) in the field of digital radiology (DR). This is also due to the push that has been applied in this sector due to the pandemic. Many studies are devoted to the challenges of integration...
Background/Objectives: This study aims to determine the validity of a recently developed and published index (the modified Composite Radiographic Index—CRIm) as an indicator of disease gravity and progression in the CBCT scans of patients with...
This study aimed to evaluate the DSP method’s applicability to Romania’s contemporary population and to assess the accuracy and reliability of variables derived from CT images. A total of 80 pelvic CT scans were analyzed. Participants ran...
Artificial intelligence (AI) is rapidly gaining attention in radiology and cardiology for accurately diagnosing structural heart disease. In this review paper, we first outline the technical background of AI and echocardiography and then present an a...
The aim of the article is to highlight the key role of artificial intelligence in modern oncology. The search for scientific publications was carried out through the following web search engines: PubMed, PMC, Web of Science, Scopus, Embase and Ebsco....
Improving the proportion of patients diagnosed with early-stage cancer is a key priority of the World Health Organisation. In many tumour groups, screening programmes have led to improvements in survival, but patient selection and risk stratification...
Cyanoacrylates were first used for medical purposes during World War II to close skin wounds. Over time, medical applications were developed, specifically in the vascular field. Uses now range from extravascular instillation in vascular grafting to i...
In the last decade, geopolitical instability across the globe has increased the risk of a large-scale radiological event, when radiation biomarkers would be needed for an effective triage of an irradiated population. Ionizing radiation elicits a comp...
Background/Objectives: Precocious puberty (PP), defined as the onset of secondary sexual characteristics before 8 years in girls and 9 years in boys, is associated with psychosocial distress, compromised adult height, and long-term metabolic risk. Ea...
Background: Theintegration of artificial intelligence (AI) into clinical decision support systems (CDSSs) has significantly enhanced diagnostic precision, risk stratification, and treatment planning. AI models remain a barrier to clinical adoption, e...
Advancements in artificial intelligence (AI) are poised to catalyze a transformative shift across diverse dental disciplines including endodontics, oral radiology, orthodontics, pediatric dentistry, periodontology, prosthodontics, and restorative den...
Cone beam computed tomography (CBCT) has become an essential tool in modern dentistry, allowing dentists to analyze the relationship between teeth and the surrounding tissues. However, traditional manual analysis can be time-consuming and its accurac...
The integration of artificial intelligence (AI) into medical disciplines is rapidly transforming healthcare delivery, with audiology being no exception. By synthesizing the existing literature, this review seeks to inform clinicians, researchers, and...
Artificial intelligence (AI) is increasingly integrated into emergency general surgery (EGS), where rapid diagnosis, accurate decision-making, and timely intervention are essential for improving patient outcomes. Recent advances in machine learning,...
Background: Multiple sclerosis (MS) is a chronic inflammatory, autoimmune, and neurodegenerative disease of the central nervous system. Our study aimed to examine the relationship between serum iron levels and the following clinical parameters: depre...
Acute respiratory distress syndrome (ARDS) has traditionally been managed with population-based, protocolized mechanical ventilation strategies designed to limit ventilator-induced lung injury. While these approaches have improved outcomes, they fail...
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