Diagnostic Radiology

Development and External Validation of an Artificial Intelligence Model for Identifying Radiology Reports Containing Recommendations for Additional Imaging.

Reported rates of recommendations for additional imaging (RAIs) in radiology reports are low. Bidir...

Teleradiology and technology innovations in radiology: status in India and its role in increasing access to primary health care.

BACKGROUND: There is an inequitable distribution of radiology facilities in India. This scoping revi...

Current and potential applications of artificial intelligence in medical imaging practice: A narrative review.

BACKGROUND AND PURPOSE: Artificial intelligence (AI) is present in many areas of our lives. Much of ...

Emerging trends and research foci of deep learning in spine: bibliometric and visualization study.

As the cognition of spine develops, deep learning (DL) emerges as a powerful tool with tremendous po...

Data drift in medical machine learning: implications and potential remedies.

Data drift refers to differences between the data used in training a machine learning (ML) model and...

A primer on artificial intelligence in pancreatic imaging.

Artificial Intelligence (AI) is set to transform medical imaging by leveraging the vast data contain...

The value of artificial intelligence in the diagnosis of lung cancer: A systematic review and meta-analysis.

Lung cancer is a common malignant tumor disease with high clinical disability and death rates. Curre...

Introduction to Radiomics and Artificial Intelligence: A Primer for Radiologists.

Health informatics and artificial intelligence (AI) are expected to transform the healthcare enterpr...

Explainable AI in medical imaging: An overview for clinical practitioners - Saliency-based XAI approaches.

Since recent achievements of Artificial Intelligence (AI) have proven significant success and promis...

How to keep artificial intelligence evolving in the medical imaging world? Challenges and opportunities.

Artificial intelligence CAD tools in trauma imaging: a scoping review from the American Society of Emergency Radiology (ASER) AI/ML Expert Panel.

BACKGROUND: AI/ML CAD tools can potentially improve outcomes in the high-stakes, high-volume model o...

COVID-19 imaging, where do we go from here? Bibliometric analysis of medical imaging in COVID-19.

OBJECTIVES: We conducted a systematic and comprehensive bibliometric analysis of COVID-19-related me...

Comparison of diagnostic performance of a deep learning algorithm, emergency physicians, junior radiologists and senior radiologists in the detection of appendicular fractures in children.

BACKGROUND: Advances have been made in the use of artificial intelligence (AI) in the field of diagn...

Natural language processing in radiology: Clinical applications and future directions.

Natural language processing (NLP) is a wide range of techniques that allows computers to interact wi...

Artificial Intelligence for Cardiothoracic Imaging: Overview of Current and Emerging Applications.

Artificial intelligence algorithms can learn by assimilating information from large datasets in orde...

Optofluidic imaging meets deep learning: from merging to emerging.

Propelled by the striking advances in optical microscopy and deep learning (DL), the role of imaging...

Revolutionizing radiology with GPT-based models: Current applications, future possibilities and limitations of ChatGPT.

Artificial intelligence has demonstrated utility and is increasingly being used in the field of radi...

A Novel Convolutional Neural Network Model Based on Beetle Antennae Search Optimization Algorithm for Computerized Tomography Diagnosis.

Convolutional neural networks (CNNs) are widely used in the field of medical imaging diagnosis but h...

Imaging Advances in Stroke: Use of Advanced Neurovascular Imaging or Disruptive Innovation With Artificial Intelligence?

Predicting gene mutation status via artificial intelligence technologies based on multimodal integration (MMI) to advance precision oncology.

Personalized treatment strategies for cancer frequently rely on the detection of genetic alterations...

The role of Artificial intelligence in the assessment of the spine and spinal cord.

Artificial intelligence (AI) application development is underway in all areas of radiology where man...