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Radiologists

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Is Artificial Intelligence (AI) a Pipe Dream? Why Legal Issues Present Significant Hurdles to AI Autonomy.

AJR. American journal of roentgenology
Proponents of artificial intelligence (AI) technology have suggested that in the near future, AI software may replace human radiologists. Although assimilation of AI into the specialty has occurred more slowly than predicted, developments in machine ...

Comparison of error rates between four pretrained DenseNet convolutional neural network models and 13 board-certified veterinary radiologists when evaluating 15 labels of canine thoracic radiographs.

Veterinary radiology & ultrasound : the official journal of the American College of Veterinary Radiology and the International Veterinary Radiology Association
Convolutional neural networks (CNNs) are commonly used as artificial intelligence (AI) tools for evaluating radiographs, but published studies testing their performance in veterinary patients are currently lacking. The purpose of this retrospective, ...

BID-Net: An Automated System for Bone Invasion Detection Occurring at Stage T4 in Oral Squamous Carcinoma Using Deep Learning.

Computational intelligence and neuroscience
Detection of the presence and absence of bone invasion by the tumor in oral squamous cell carcinoma (OSCC) patients is very significant for their treatment planning and surgical resection. For bone invasion detection, CT scan imaging is the preferred...

Deep learning prediction of sex on chest radiographs: a potential contributor to biased algorithms.

Emergency radiology
BACKGROUND: Deep convolutional neural networks (DCNNs) for diagnosis of disease on chest radiographs (CXR) have been shown to be biased against males or females if the datasets used to train them have unbalanced sex representation. Prior work has sug...

FDA-approved deep learning software application versus radiologists with different levels of expertise: detection of intracranial hemorrhage in a retrospective single-center study.

Neuroradiology
PURPOSE: To assess an FDA-approved and CE-certified deep learning (DL) software application compared to the performance of human radiologists in detecting intracranial hemorrhages (ICH).

Artificial intelligence for stepwise diagnosis and monitoring of COVID-19.

European radiology
BACKGROUND: Main challenges for COVID-19 include the lack of a rapid diagnostic test, a suitable tool to monitor and predict a patient's clinical course and an efficient way for data sharing among multicenters. We thus developed a novel artificial in...

The concept of the invisible radiologist in the era of artificial intelligence.

European journal of radiology
The radiologists were traditionally working in the background. What upgraded them as physicians during the second half of the past century was their clinical training and function precipitated by the evolution of Interventional Radiology and Medical ...

Assessment of the effect of a comprehensive chest radiograph deep learning model on radiologist reports and patient outcomes: a real-world observational study.

BMJ open
OBJECTIVES: Artificial intelligence (AI) algorithms have been developed to detect imaging features on chest X-ray (CXR) with a comprehensive AI model capable of detecting 124 CXR findings being recently developed. The aim of this study was to evaluat...

Image quality and radiologists' subjective acceptance using model-based iterative and deep learning reconstructions as adjuncts to ultrahigh-resolution CT in low-dose contrast-enhanced abdominopelvic CT: phantom and clinical pilot studies.

Abdominal radiology (New York)
PURPOSE: In contrast-enhanced abdominopelvic CT (CE-APCT) for oncologic follow-up, ultrahigh-resolution CT (UHRCT) may improve depiction of fine lesions and low-dose scans are desirable for minimizing the potential adverse effects by ionizing radiati...

A machine and human reader study on AI diagnosis model safety under attacks of adversarial images.

Nature communications
While active efforts are advancing medical artificial intelligence (AI) model development and clinical translation, safety issues of the AI models emerge, but little research has been done. We perform a study to investigate the behaviors of an AI dia...