AIMC Topic: Diagnostic Imaging

Clear Filters Showing 181 to 190 of 978 articles

Artificial Intelligence in Radiology: Opportunities and Challenges.

Seminars in ultrasound, CT, and MR
Artificial intelligence's (AI) emergence in radiology elicits both excitement and uncertainty. AI holds promise for improving radiology with regards to clinical practice, education, and research opportunities. Yet, AI systems are trained on select da...

Meta-research on reporting guidelines for artificial intelligence: are authors and reviewers encouraged enough in radiology, nuclear medicine, and medical imaging journals?

Diagnostic and interventional radiology (Ankara, Turkey)
PURPOSE: To determine how radiology, nuclear medicine, and medical imaging journals encourage and mandate the use of reporting guidelines for artificial intelligence (AI) in their author and reviewer instructions.

Artificial intelligence in liver imaging: methods and applications.

Hepatology international
Liver disease is regarded as one of the major health threats to humans. Radiographic assessments hold promise in terms of addressing the current demands for precisely diagnosing and treating liver diseases, and artificial intelligence (AI), which exc...

DeepION: A Deep Learning-Based Low-Dimensional Representation Model of Ion Images for Mass Spectrometry Imaging.

Analytical chemistry
Mass spectrometry imaging (MSI) is a high-throughput imaging technique capable of the qualitative and quantitative in situ detection of thousands of ions in biological samples. Ion image representation is a technique that produces a low-dimensional v...

Proceedings From the 2022 ACR-RSNA Workshop on Safety, Effectiveness, Reliability, and Transparency in AI.

Journal of the American College of Radiology : JACR
Despite the surge in artificial intelligence (AI) development for health care applications, particularly for medical imaging applications, there has been limited adoption of such AI tools into clinical practice. During a 1-day workshop in November 20...

Deep learning in rheumatological image interpretation.

Nature reviews. Rheumatology
Artificial intelligence techniques, specifically deep learning, have already affected daily life in a wide range of areas. Likewise, initial applications have been explored in rheumatology. Deep learning might not easily surpass the accuracy of class...

Deep learning-assisted mass spectrometry imaging for preliminary screening and pre-classification of psychoactive substances.

Talanta
Currently, it is of great urgency to develop a rapid pre-classification and screening method for suspected drugs as the constantly springing up of new psychoactive substances. In most researches, psychoactive substances classification approaches depe...

Medical Imaging Applications Developed Using Artificial Intelligence Demonstrate High Internal Validity Yet Are Limited in Scope and Lack External Validation.

Arthroscopy : the journal of arthroscopic & related surgery : official publication of the Arthroscopy Association of North America and the International Arthroscopy Association
PURPOSE: To (1) review definitions and concepts necessary to interpret applications of deep learning (DL; a domain of artificial intelligence that leverages neural networks to make predictions on media inputs such as images) and (2) identify knowledg...

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RoFo : Fortschritte auf dem Gebiete der Rontgenstrahlen und der Nuklearmedizin