AIMC Topic: Radiology

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The current status and future of FDA-approved artificial intelligence tools in chest radiology in the United States.

Clinical radiology
Artificial intelligence (AI) is becoming more widespread within radiology. Capabilities that AI algorithms currently provide include detection, segmentation, classification, and quantification of pathological findings. Artificial intelligence softwar...

Artificial Intelligence in Spinal Imaging: Current Status and Future Directions.

International journal of environmental research and public health
Spinal maladies are among the most common causes of pain and disability worldwide. Imaging represents an important diagnostic procedure in spinal care. Imaging investigations can provide information and insights that are not visible through ordinary ...

Natural Language Processing in Radiology: Update on Clinical Applications.

Journal of the American College of Radiology : JACR
Radiological reports are a valuable source of information used to guide clinical care and support research. Organizing and managing this content, however, frequently requires several manual curations because of the more common unstructured nature of ...

Application of Deep Learning in Generating Structured Radiology Reports: A Transformer-Based Technique.

Journal of digital imaging
Since radiology reports needed for clinical practice and research are written and stored in free-text narrations, extraction of relative information for further analysis is difficult. In these circumstances, natural language processing (NLP) techniqu...

Tumor Microenvironment, Radiology, and Artificial Intelligence: Should We Consider Tumor Periphery?

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
OBJECTIVES: The tumor microenvironment (TME) consists of cellular and noncellular components which enable the tumor to interact with its surroundings and plays an important role in the tumor progression and how the immune system reacts to the maligna...

How do providers of artificial intelligence (AI) solutions propose and legitimize the values of their solutions for supporting diagnostic radiology workflow? A technography study in 2021.

European radiology
OBJECTIVES: How do providers of artificial intelligence (AI) solutions propose and legitimize the values of their solutions for supporting diagnostic radiology workflow?

Patient communication in radiology: Moving up the agenda.

European journal of radiology
Optimised communication between patients and the imaging team is an essential component of providing patient-centred and value-based care. Communication with patients can be challenging in the setting of busy radiology departments where there is a fo...

Artificial intelligence in emergency radiology: A review of applications and possibilities.

Diagnostic and interventional imaging
Artificial intelligence (AI) applications in radiology have been rising exponentially in the last decade. Although AI has found usage in various areas of healthcare, its utilization in the emergency department (ED) as a tool for emergency radiologist...

Implementation of Clinical Artificial Intelligence in Radiology: Who Decides and How?

Radiology
As the role of artificial intelligence (AI) in clinical practice evolves, governance structures oversee the implementation, maintenance, and monitoring of clinical AI algorithms to enhance quality, manage resources, and ensure patient safety. In this...