Radiology

Diagnostic Radiology

Latest AI and machine learning research in diagnostic radiology for healthcare professionals.

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Deep learning network enhances imaging quality of low-b-value diffusion-weighted imaging and improves lesion detection in prostate cancer.

BACKGROUND: Diffusion-weighted imaging with higher b-value improves detection rate for prostate canc...

[Clinical value of medical imaging artificial intelligence in the diagnosis and treatment of peritoneal metastasis in gastrointestinal cancers].

Peritoneal metastasis is a key factor in the poor prognosis of advanced gastrointestinal cancer pati...

Diagnostic tools and methods for dermatological assessment.

Advanced clinical practitioners (ACPs) play an essential role in dermatological care but often encou...

Current trends and emerging themes in utilizing artificial intelligence to enhance anatomical diagnostic accuracy and efficiency in radiotherapy.

Artificial intelligence (AI) incorporation into healthcare has proven revolutionary, especially in r...

Research status and progress of deep learning in automatic esophageal cancer detection.

Esophageal cancer (EC), a common malignant tumor of the digestive tract, requires early diagnosis an...

HSG-Assistant: AI-Driven Framework for Enhanced Hysterosalpingography Analysis.

HSG-Assistant is an AI-driven diagnostic framework designed to address the significant limitations o...

Application of artificial intelligence medical imaging aided diagnosis system in the diagnosis of pulmonary nodules.

The application of artificial intelligence (AI) technology has realized the transformation of people...

Privacy-preserving Federated Learning and Uncertainty Quantification in Medical Imaging.

Artificial Intelligence (AI) has demonstrated strong potential in automating medical imaging tasks,...

Artificial Intelligence in Diagnostic Radiology: Where Do We Stand, Challenges, and Opportunities.

Artificial intelligence (AI) is the most revolutionizing development in the health care industry in ...

[Chest radiological lesions in COVID-19 : from classical imaging to artificial intelligence].

In the course of the pandemic induced by the appearance of a new coronavirus (SARS-CoV-2; COVID-19) ...

The Society of Thoracic Radiology Mentorship Program: A Paradigm for Professional Societies.

The Society of Thoracic Radiology (STR) membership enthusiastically embraced the launch of its mento...

The march to harmonized imaging standards for retinal imaging.

The adoption of standardized imaging protocols in retinal imaging is critical to overcoming challeng...

Atrial Cardiomyopathy in Atrial Fibrillation: A Multimodal Diagnostic Framework.

Atrial fibrillation (AF) is increasingly recognized as the clinical manifestation of an underlying a...

Application of Artificial Intelligence in Cardio-Oncology Imaging for Cancer Therapy-Related Cardiovascular Toxicity: Systematic Review.

BACKGROUND: Artificial intelligence (AI) is a revolutionary tool yet to be fully integrated into sev...

Diagnostic Accuracy of Novel Optical Imaging Techniques for Melanoma Detection: A Systematic Review and Meta-Analysis.

The incidence of melanoma is increasing worldwide, requiring early detection to improve survival rat...

Detection of flap malperfusion after microsurgical tissue reconstruction using hyperspectral imaging and machine learning.

Hyperspectral imaging (HSI) has shown significant diagnostic potential for both intra- and postopera...

Pitfalls and Best Practices in Evaluation of AI Algorithmic Biases in Radiology.

Despite growing awareness of problems with fairness in artificial intelligence (AI) models in radiol...

Deep Learning-based Quantitative CT Myocardial Perfusion Imaging and Risk Stratification of Coronary Artery Disease.

Background Precise assessment of myocardial ischemia burden and cardiovascular risk stratification b...

AI Applications for Thoracic Imaging: Considerations for Best Practice.

Artificial intelligence (AI) technology is rapidly being introduced into thoracic radiology practice...

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