Diagnostic Radiology

Artificial Intelligence and Clinical Decision Support for Radiologists and Referring Providers.

Recent advances in artificial intelligence (AI) are providing an opportunity to enhance existing cli...

The Role of Generative Adversarial Networks in Radiation Reduction and Artifact Correction in Medical Imaging.

Adversarial networks were developed to complete powerful image-processing tasks on the basis of exam...

Strengths, Weaknesses, Opportunities, and Threats Analysis of Artificial Intelligence and Machine Learning Applications in Radiology.

Currently, the use of artificial intelligence (AI) in radiology, particularly machine learning (ML),...

Toward Complete Structured Information Extraction from Radiology Reports Using Machine Learning.

Unstructured and semi-structured radiology reports represent an underutilized trove of information f...

RIL-Contour: a Medical Imaging Dataset Annotation Tool for and with Deep Learning.

Deep-learning algorithms typically fall within the domain of supervised artificial intelligence and ...

Eye Tracking for Deep Learning Segmentation Using Convolutional Neural Networks.

Deep learning with convolutional neural networks (CNNs) has experienced tremendous growth in multipl...

[Research progress in medical imaging based on deep learning of neural network].

The development of computer hardware allows rapid accumulation of medical imaging data. Deep learnin...

[Artificial Intelligence for Diagnostic Support of Neuroimage].

Artificial intelligence (AI) shows promises in terms of diagnostic support on neuroimaging. We devel...

A new era: artificial intelligence and machine learning in prostate cancer.

Artificial intelligence (AI) - the ability of a machine to perform cognitive tasks to achieve a part...

Collaborations of Industry, Academia, Research and Application Improve the Healthy Development of Medical Imaging Artificial Intelligence Industry in China.

In recent years, artificial intelligence (AI) has developed rapidly in the field of medical imaging....

The Artificial Intelligence-Enabled Medical Imaging: Today and Its Future.

Medical imaging is now being reshaped by artificial intelligence (AI) and progressing rapidly toward...

Artificial intelligence at the intersection of pathology and radiology in prostate cancer.

Pathologic grading plays a key role in prostate cancer risk stratification and treatment selection, ...

Integrating an Ontology of Radiology Differential Diagnosis with ICD-10-CM, RadLex, and SNOMED CT.

An ontology offers a human-readable and machine-computable representation of the concepts in a domai...

Automated Diagnosis of Lymphoma with Digital Pathology Images Using Deep Learning.

Recent studies have shown promising results in using Deep Learning to detect malignancy in whole sli...

Integrating ontologies of human diseases, phenotypes, and radiological diagnosis.

Mappings between ontologies enable reuse and interoperability of biomedical knowledge. The Radiology...

Artificial intelligence, machine learning, computer-aided diagnosis, and radiomics: advances in imaging towards to precision medicine.

The discipline of radiology and diagnostic imaging has evolved greatly in recent years. We have obse...

Artificial Intelligence and Radiology in Singapore: Championing a New Age of Augmented Imaging for Unsurpassed Patient Care.

Artificial intelligence (AI) has been positioned as being the most important recent advancement in r...

Machine learning applications for the differentiation of primary central nervous system lymphoma from glioblastoma on imaging: a systematic review and meta-analysis.

OBJECTIVEGlioblastoma (GBM) and primary central nervous system lymphoma (PCNSL) are common intracran...

Machine learning: from radiomics to discovery and routine.

Machine learning is rapidly gaining importance in radiology. It allows for the exploitation of patte...

Proposing New RadLex Terms by Analyzing Free-Text Mammography Reports.

After years of development, the RadLex terminology contains a large set of controlled terms for the ...

FDA backs clinician-free AI imaging diagnostic tools.