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ChatGPT outperforms clinicians in post-negative test disease probability

AuntMinnie

ChatGPT-4 outperformed human clinicians in determining pretest and post-test disease probability after a negative test result involving chest radiographs and mammograms, according to a research letter published December 11 in JAMA Network Open.

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Can AI help chest DDR achieve clinical adoption?

AuntMinnie

Chest dynamic digital radiography (DDR) may have received a boost toward clinical use in patients with lung disorders, with researchers developing AI to perform time-consuming analysis involved in the technology, according to researchers in New York City. a) Raw example of a dynamic digital radiograph. (b)

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PSMA-PET provides long-term benefits

AuntMinnie

Although studies have shown that PSMA-PET is highly effective for detecting prostate cancer, the long-term consequences of widely implementing the technique in patients with recurrent disease are unknown, the authors explained. population and was informed by data from real-world settings.

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Can AI help rule out ‘unremarkable’ chest x-rays?

AuntMinnie

These included chest radiographs that displayed abnormalities of no clinical significance, which are typically treated as normal. In addition, a thoracic radiologist graded the missed findings by AI and/or the radiology reports as critical, clinically significant, or clinically insignificant.

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Road to RSNA 2023: AI Preview

AuntMinnie

RSNA attendees focused on practical AI matters will likely appreciate the RSNA's Imaging AI in Practice interoperability demonstration, which will demonstrate at the AI Showcase how the technology can be integrated into radiology workflow in real-world clinical scenarios. 9:40 a.m. | 9:40 a.m. | 10:00 a.m. | 2:00 p.m. | 2:00 p.m. |

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Radiologists Must Monitor Novel Alzheimer’s Treatment Side Effect

Imaging Technology

Alzheimer disease is a progressive, irreversible brain disorder that slowly degrades memory and cognitive function. While previous treatment methods focused on addressing Alzheimer disease symptoms, recent approvals of monoclonal antibodies have provided a path to target the underlying disease itself. In June 2021, the U.S.

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Deep learning combines breast imaging data to predict cancer prognosis

AuntMinnie

Deep-learning models could have potential as predictive tools for breast cancer prognosis, a study published January 17 in Clinical Breast Cancer has found. From there, the team used clinical data and imaging characteristics to select independent prognostic factors to establish a clinical model.