Diagnostic Radiology

Temporomandibular Disorders Diagnosis: Current Challenges and the Promising Role of Artificial Intelligence.

Temporomandibular disorders (TMDs) are a group of musculoskeletal and joint-related conditions affecting the temporomandibular joint (TMJ), masticatory muscles, and associated structures. They are among the most common causes of non-dental orofacial pain and functional impairment, significantly affecting quality of life. Despite advances in assessment and the development of standardized diagnostic...

Deep learning in lower gastrointestinal cancer detection: Advances in endoscopic, radiologic, and histopathologic diagnostics.

Gastrointestinal (GI) cancers, particularly colorectal cancer, continue to be a major contributor to global cancer-related morbidity and mortality. Despite significant advancements in screening protocols and treatment strategies, early detection remains a clinical challenge due to the limitations of conventional diagnostic tools, which often suffer from inter-observer variability, limited sensitiv...

Evaluating the impact of artificial intelligence tools on the detection of chest injuries from medical imaging: A systematic review and meta-analysis.

BACKGROUND: There has been a growing interest in the clinical application of artificial intelligence (AI) tools in medical imaging to aid diagnosis. T...

Establishing an Artificial Intelligence Sandbox for Diagnostic Imaging in Ontario.

Ontario faces persistent diagnostic imaging (DI) challenges, which includes fragmented implementation of Artificial Intelligence (AI) solutions. The C...

Foundation models in radiology: a primer for pediatric radiologists.

Foundation models (FMs) are large deep learning models pre-trained on vast heterogeneous datasets through self-supervised learning that are adaptable ...

State and Diffusion of National Institutes of Health Funding of AI in Radiology.

Artificial intelligence research has profound implications for the future of radiology, making it essential to understand funding patterns and diffusi...

Performance of machine learning algorithms in diffusion tensor imaging of movement disorders: an exploratory meta-analysis.

BACKGROUND: Machine learning (ML) applied to diffusion tensor imaging (DTI) has emerged as a promising tool for detecting microstructural brain altera...

Artificial intelligence for fracture detection on computed tomography: a comprehensive systematic review and meta-analysis of diagnostic test accuracy in non-commercial and commercial solutions.

Rising patient volumes, the increasing use of computed tomography (CT) imaging in emergency departments and the resulting prolonged waiting times high...

Financial Reasoning in Radiology: Interpreting Risk, Value, and Capital Allocation for Resilient and High-Value Imaging Services.

Radiology is among the most capital-intensive specialities in healthcare, relying on high-cost imaging equipment, complex information technology infra...

Comparative diagnostic capability of large language models in neurosurgery.

OBJECTIVE: OpenAI, Google, and Microsoft have recently developed popular large language models (LLMs) with incredible clinical applications. LLMs spec...

Emerging trends in the early diagnosis of dental caries: a scoping review of artificial intelligence, digital diagnostics, and teledentistry.

BACKGROUND: Dental caries is the most prevalent chronic, noncommunicable condition affecting individuals of all ages and socio-economic status. The re...

Atomically Precise Metal Clusters for NIR-II Imaging.

ConspectusNear-infrared II (NIR-II, 1000-3000 nm), also defined as shortwave infrared (SWIR) imaging, offers reduced light scattering and low tissue a...

Evaluation of Large Language Models for Radiologists' Support in Multidisciplinary Breast Cancer Teams: Comparative Study.

BACKGROUND: Artificial intelligence tools, particularly large language models (LLMs), have shown considerable potential across various domains. Howeve...

Machine learning for the diagnosis of fibromyalgia based on magnetic resonance imaging.

The clinical diagnosis of fibromyalgia (FM), a syndrome characterized by generalized pain, is challenging due to its unknown etiology and frequent com...

Artificial intelligence and computer-aided diagnosis in diagnostic decisions: 5 questions for medical informatics and human-computer interface research.

OBJECTIVES: Artificial intelligence (AI) has the potential to transform medical informatics by supporting clinical decision-making, reducing diagnosti...

Veterinary workers report low knowledge of artificial intelligence but positive attitudes toward its adoption in diagnostic imaging and the workplace as a whole.

OBJECTIVE: To describe veterinary workers' knowledge, attitudes, and practices regarding AI in veterinary medicine, with an emphasis on diagnostic ima...

Implementing an Artificial Intelligence Decision Support System in Radiology: Prospective Qualitative Evaluation Study Using the Nonadoption Abandonment Scale-Up, Spread, and Sustainability (NASSS) Framework.

BACKGROUND: Medical imaging remains at the forefront of advancements in adopting digital health technologies in clinical practice. Regulator-approved ...

Fréchet radiomic distance (FRD): A versatile metric for comparing medical imaging datasets.

Determining whether two sets of images belong to the same or different distributions or domains is a crucial task in modern medical image analysis and...

Sex disparities in deep learning estimation of ejection fraction from cardiac magnetic resonance imaging.

The advent of artificial intelligence in cardiovascular imaging holds immense potential for earlier diagnoses, precision medicine, and improved diseas...

Artificial intelligence-enabled pediatric radiology in low-resource settings: addressing resource constraints in the African healthcare system.

Artificial intelligence (AI) holds immense promise in guiding clinical decision making in pediatric radiology, but its implementation in resource-cons...