Radiology

Diagnostic Radiology

Latest AI and machine learning research in diagnostic radiology for healthcare professionals.

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Artificial Intelligence Applications in Cardiac CT Imaging for Ischemic Disease Assessment.

Artificial intelligence (AI) has transformed medical imaging by detecting insights and patterns ofte...

Foundation Models in Radiology: What, How, Why, and Why Not.

Recent advances in artificial intelligence have witnessed the emergence of large-scale deep learning...

Research on equipment fault diagnosis model based on gan and inverse PINN: Solutions for data imbalance and rare faults.

In the field of medical imaging equipment, fault diagnosis plays a vital role in guaranteeing stable...

Imaging flow cytometry: from high - resolution morphological imaging to innovation in high - throughput multidimensional biomedical analysis.

Imaging flow cytometry (IFC), as an extension of conventional flow cytometry, has emerged as a cutti...

Could metabolic imaging and artificial intelligence provide a novel path to non-invasive aneuploidy assessments? A certain clinical need.

Pre-implantation genetic testing for aneuploidy (PGT-A) via embryo biopsy helps in embryo selection ...

Deep Learning and Multidisciplinary Imaging in Pediatric Surgical Oncology: A Scoping Review.

BACKGROUND: Medical images play an important role in diagnosis and treatment of pediatric solid tumo...

ClinValAI: A framework for developing Cloud-based infrastructures for the External Clinical Validation of AI in Medical Imaging.

Artificial Intelligence (AI) algorithms showcase the potential to steer a paradigm shift in clinical...

Diagnostic Performance of Deep Learning Applications in Hepatocellular Carcinoma Detection Using Computed Tomography Imaging.

Hepatocellular carcinoma (HCC) is a prevalent cancer that significantly contributes to mortality glo...

State-of-the-Art Deep Learning CT Reconstruction Algorithms in Abdominal Imaging.

The implementation of deep neural networks has spurred the creation of deep learning reconstruction ...

Care to Explain? AI Explanation Types Differentially Impact Chest Radiograph Diagnostic Performance and Physician Trust in AI.

Background It is unclear whether artificial intelligence (AI) explanations help or hurt radiologists...

Image-Based Generative Artificial Intelligence in Radiology: Comprehensive Updates.

Generative artificial intelligence (AI) has been applied to images for image quality enhancement, do...

Towards objective and systematic evaluation of bias in artificial intelligence for medical imaging.

OBJECTIVE: Artificial intelligence (AI) models trained using medical images for clinical tasks often...

How Data Infrastructure Deals with Bias Problems in Medical Imaging.

The paper discusses biases in medical imaging analysis, particularly focusing on the challenges pose...

Assessment of Follow-Up for Pulmonary Nodules from Radiology Reports with Natural Language Processing.

Radiology reports are an essential communication method for ensuring smooth workflow in healthcare. ...

Risk factors and development of machine learning diagnostic models for lateral lymph node metastasis in rectal cancer: multicentre study.

BACKGROUND: The diagnostic criteria for lateral lymph node metastasis in rectal cancer have not been...

Leveraging Vision Transformers for Enhanced Accuracy in Pneumonia Detection from Medical Imaging Data.

Medical image analysis has witnessed a paradigm shift with the advent of artificial intelligence, pa...

Multi-Scale Self-Supervised Consistency Training for Trustworthy Medical Imaging Classification.

Modern neural network models have demonstrated exceptional classification capabilities comparable to...

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