AI

In a video interview, Morris Panner, the president of Intelerad Medical Systems, discussed key observations from the recent Society for Imaging Informatics in Medicine (SIIM) conference, recent research about artificial intelligence (AI) adoption and emerging goals for enhancing the efficiency of radiology workflows.

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The artificial intelligence (AI) capabilities of the new software reportedly facilitate scanning times that are three times faster than conventional magnetic resonance image (MRI) scanners.

An updated machine learning model demonstrated a 23 percent improvement in accuracy and a 36.1 percent improvement in sensitivity over visual radiologist assessment of ultrasound images for differentiating malignant lymph nodes and benign COVID-19 vaccination-related changes to lymph nodes.

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The study, involving 500 patients, showed that artificial intelligence (AI) assistance enhanced fracture diagnosis on radiographs and reduced reading time for radiologists of varying experience levels.

The new magnetic resonance imaging (MRI) device reportedly offers deep learning technologies and advanced processing of whole-body images in a cost-effective and lightweight model.

Ambient speech capabilities in emerging voice recognition products and software updates may convert the clinical context of conversational speech into structured data for radiology reports.

Calantric™ Digital Solutions reportedly offers artificial intelligence (AI)-powered apps, bolsters lesion detection, facilitates triage priorities and enhances workflow efficiency.

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New research suggests that an emerging predictive biomarker, derived from a combination of magnetic resonance imaging (MRI) brain scans and a machine learning algorithm, has significantly greater accuracy than previously established measurements for diagnosing Alzheimer’s disease.

In a recent video interview, abdominal radiologist Sonia Gupta, MD discussed key principles in assessing potential alliances with artificial intelligence (AI) vendors and the potential of AI to alleviate the time-consuming, administrative aspects of patient care.

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Noting that an AI software platform could save radiologists up to an hour a day in interpreting chest computed tomography (CT) scans, the authors of a prospective study found shorter mean interpretation times with non-contrast and contrast-enhanced CT as well as positive CT scans with and without significant new findings.

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The deep learning model may offer enhanced sensitivity and specificity on MRI for patients with glioblastoma, according to preliminary research presented at the Society for Imaging Informatics in Medicine (SIIM) conference.

A 3D whole brain convolutional neural network could provide enhanced sensitivity and specificity for diagnosing intracranial hemorrhages on computed tomography, according to new research presented at the Society for Imaging Informatics in Medicine (SIIM) conference in Kissimmee, Fla.

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Deep radiomics models that included deep learning features had a 40 percent or greater increase in the specificity rate for diagnosing osteoporosis on hip radiographs in comparison to models that only emphasized clinical and/or textural features.

The new artificial intelligence-powered software reportedly helps detect central pulmonary embolism (PE) on computed tomography pulmonary angiogram (CTPA) images and streamlines communication among interventional teams to bolster treatment outcomes.

A new study revealed that an emerging artificial intelligence (AI)-enabled software tool led to improved sensitivity, specificity and inter-observer agreement for the diagnosis of indeterminate pulmonary nodules on chest computed tomography (CT) scans.

Could the emerging artificial intelligence platforms Saige-Dx and Quantib Prostate 2.0 improve cancer detection with mammography and prostate MRI?

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While some have raised questions and concerns about a possible loss of autonomy with the increasing presence of private equity in radiology, this author says potential benefits of such an alliance, including access to new technologies, career development and a strong patient focus, go beyond the expected economies of scale.

Offering integrated artificial intelligence (AI) and seamless multi-nuclei imaging capabilities, the new magnetic resonance imaging (MRI) system reportedly enhances image quality and workflow efficiency.

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The AI-powered dental algorithm, Video Caries Assist, reduced missed cavities by 43%.

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The new artificial intelligence-powered software from Nanox reportedly identifies findings suggestive of compression fractures and low density on computed tomography (CT) images and facilitates more precise measurement of these fractures.

A new study suggests that deep learning algorithms with multimodal ultrasound have comparable specificity and sensitivity to subjective expert assessment and use of the O-RADS classification to distinguish between benign and malignant ovarian tumors.