AIMC Topic: Radiology

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Application of deep learning to the diagnosis of cervical lymph node metastasis from thyroid cancer with CT: external validation and clinical utility for resident training.

European radiology
PURPOSE: This study aimed to validate a deep learning model's diagnostic performance in using computed tomography (CT) to diagnose cervical lymph node metastasis (LNM) from thyroid cancer in a large clinical cohort and to evaluate the model's clinica...

Integrating artificial intelligence into the clinical practice of radiology: challenges and recommendations.

European radiology
Artificial intelligence (AI) has the potential to significantly disrupt the way radiology will be practiced in the near future, but several issues need to be resolved before AI can be widely implemented in daily practice. These include the role of th...

Noninterpretive Uses of Artificial Intelligence in Radiology.

Academic radiology
We deem a computer to exhibit artificial intelligence (AI) when it performs a task that would normally require intelligent action by a human. Much of the recent excitement about AI in the medical literature has revolved around the ability of AI model...

Changes in cancer detection and false-positive recall in mammography using artificial intelligence: a retrospective, multireader study.

The Lancet. Digital health
BACKGROUND: Mammography is the current standard for breast cancer screening. This study aimed to develop an artificial intelligence (AI) algorithm for diagnosis of breast cancer in mammography, and explore whether it could benefit radiologists by imp...

Multiparametric radiomics methods for breast cancer tissue characterization using radiological imaging.

Breast cancer research and treatment
BACKGROUND AND PURPOSE: Multiparametric radiological imaging is vital for detection, characterization, and diagnosis of many different diseases. Radiomics provide quantitative metrics from radiological imaging that may infer potential biological mean...

Artificial intelligence: Who is responsible for the diagnosis?

La Radiologia medica
The aim of the paper is to find an answer to the question "Who or what is responsible for the benefits and harms of using artificial intelligence in radiology?" When human beings make decisions, the action itself is normally connected with a direct r...

Deep Learning for Natural Language Processing in Radiology-Fundamentals and a Systematic Review.

Journal of the American College of Radiology : JACR
PURPOSE: Natural language processing (NLP) enables conversion of free text into structured data. Recent innovations in deep learning technology provide improved NLP performance. We aimed to survey deep learning NLP fundamentals and review radiology-r...

Artificial Intelligence in Radiology Residency Training.

Seminars in musculoskeletal radiology
Artificial intelligence (AI) is an emerging technology that brings a wide array of new tools to the field of radiology. AI will certainly have an impact on the day-to-day work of radiologists in the coming decades, thus training programs must prepare...

From Data to Value: How Artificial Intelligence Augments the Radiology Business to Create Value.

Seminars in musculoskeletal radiology
The radiology practice has access to a wealth of data in the radiologist information system, dictation reports, and electronic health records. Although many artificial intelligence applications in radiology have focused on computer vision and the int...