AIMC Topic: Image Interpretation, Computer-Assisted

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Basic Artificial Intelligence Techniques: Natural Language Processing of Radiology Reports.

Radiologic clinics of North America
Natural language processing (NLP) is a subfield of computer science and linguistics that can be applied to extract meaningful information from radiology reports. Symbolic NLP is rule based and well suited to problems that can be explicitly defined by...

Future Directions in Artificial Intelligence.

Radiologic clinics of North America
No one knows what the paradigm shift of artificial intelligence will bring to medical imaging. In this article, we attempt to predict how artificial intelligence will impact radiology based on a critical review of current innovations. The best way to...

Regulatory Issues and Challenges to Artificial Intelligence Adoption.

Radiologic clinics of North America
Artificial intelligence technology promises to redefine the practice of radiology. However, it exists in a nascent phase and remains largely untested in the clinical space. This nature is both a cause and consequence of the uncertain legal-regulatory...

Separating Hope from Hype: Artificial Intelligence Pitfalls and Challenges in Radiology.

Radiologic clinics of North America
Although recent scientific studies suggest that artificial intelligence (AI) could provide value in many radiology applications, much of the hard engineering work required to consistently realize this value in practice remains to be done. In this art...

Artificial Intelligence Enabling Radiology Reporting.

Radiologic clinics of North America
The radiology reporting process is beginning to incorporate structured, semantically labeled data. Tools based on artificial intelligence technologies using a structured reporting context can assist with internal report consistency and longitudinal t...

Clinical Artificial Intelligence Applications: Breast Imaging.

Radiologic clinics of North America
This article gives a brief overview of the development of artificial intelligence in clinical breast imaging. For multiple decades, artificial intelligence (AI) methods have been developed and translated for breast imaging tasks such as detection, di...

Clinical Artificial Intelligence Applications: Musculoskeletal.

Radiologic clinics of North America
We present an overview of current clinical musculoskeletal imaging applications for artificial intelligence, as well as potential future applications and techniques.

Clinical Artificial Intelligence Applications in Radiology: Neuro.

Radiologic clinics of North America
Radiologists have been at the forefront of the digitization process in medicine. Artificial intelligence (AI) is a promising area of innovation, particularly in medical imaging. The number of applications of AI in neuroradiology has also grown. This ...

Deep Learning for Clinical Image Analyses in Oral Squamous Cell Carcinoma: A Review.

JAMA otolaryngology-- head & neck surgery
IMPORTANCE: Oral squamous cell carcinoma (SCC) is a lethal malignant neoplasm with a high rate of tumor metastasis and recurrence. Accurate diagnosis, prognosis prediction, and metastasis detection can improve patient outcomes. Deep learning for clin...

A Bayesian optimization approach for rapidly mapping residual network function in stroke.

Brain : a journal of neurology
Post-stroke cognitive and linguistic impairments are debilitating conditions, with limited therapeutic options. Domain-general brain networks play an important role in stroke recovery and characterizing their residual function with functional MRI has...