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Most radiologists have heard of Moore’s Law. A close colleague observed that radiologists are affected by a type of Moore’s Law. The amount of scans a radiologist is expected to shift per day is increasing year on year. Today’s radiologist is expected to shift work at an eye-watering rate. Paul McCoubrie, MBBS.
Only two previous studies have addressed the issue of whether enhancements in visual perception abilities of radiologists are a product of specialist professional training, with mixed results, the authors explained.
While radiographers are concerned about job security, they are also optimistic about AI’s role in their future workflows, according to a presentation given March 1 at ECR 2024. Radiographers appear optimistic about the future of radiographer job roles and responsibilities,” Walsh said. Of the total respondents, 31.3%
An AI model that detects low bone mineral density (BMD) on ankle and foot x-rays could be useful for screening for osteoporosis, according to radiologists at MD Anderson Cancer Center in Houston. First, the team culled a dataset from 907 patients over 50 years old who had undergone both DEXA scans and x-rays within 12 months.
million chest radiographs. The team reported that the algorithm could successfully triage pairs of chest radiographs showing no change while detecting urgent interval changes during longitudinal follow-up. Julianna Czum, MD, from Johns Hopkins University wrote an editorial accompanying the study.
In a reader study involving five radiologists interpreting 758 chest x-rays, use of the model (AIRead, Soombit.ai) reduced average reading times by 14 seconds per image and increased sensitivities for certain findings. To that end, Hong and colleagues, including researchers from Seoul-based companies Soombit.ai
The voters also zeroed in on the ongoing shortage of radiologists as the Biggest Threat to Radiology. Fishman concedes that there are barriers to educational pursuits in the radiology sphere -- not the least of which is pressure on radiologists to generate high relative value units. I'm a radiographer,' " Stewart recalled.
. | S1-SSCH01-5 | E451A This scientific paper may increase overall confidence in the potential of using multimodal AI for tuberculosis (TB) detection, and potentially autonomous reporting, on chest radiographs in certain clinical settings. respectively, where that of three radiologists' ranged between 91.9% to 94.7%, 89.4%
AI for thoracic imaging includes using it for reading chest radiographs and low-dose chest CT scans for lung cancer screening and for triaging pulmonary embolism on chest CT scans, the group noted.
for abnormal radiographs and 99.8% for critical radiographs—better than two board-certified radiologists who also interpreted the exams. The tool’s sensitivity was recorded as 99.1%
Radiographers have difficulty communicating with and caring for patients wh. Read more on AuntMinnie.com Related Reading: Radiologists seeing declines in reimbursement per beneficiary Was burnout really worse for radiologists during the pandemic? Could phone tree system help with radiologist burnout?
Their performance was compared to reads by 17 radiologists and radiology residents with varying experience. A) Radiograph in a man (age, 72 years) with a nodule present (reference standard score, 100) shows a true-positive result based on the average algorithm scores. (B) years) for estimating bone age compared with human readers (0.68
Among questions that remain unanswered about AI is whether the quality of its mistakes is different than those of radiologists and if AI mistakes, on average, are objectively worse than human mistakes. These included chest radiographs that displayed abnormalities of no clinical significance, which are typically treated as normal.
In a study described as a “competition between radiologists,” participants tasked with identifying abnormal findings on chest x-rays performed better with AI assistance than without AI assistance – though not by much and not in all cases, according to a group in Nanjing, Jiangsu, China.
Radiologists routinely compare the current and previous chest radiographs during interpretation to enhance the sensitivity for change detection and provide information for differential diagnosis. Example of triage of no change in a pair of chest radiographs in the emergency department. (A) to 100% in the ED images and 85.5%
AI assistance can improve the detection accuracy of thoracic abnormalities on chest x-rays across radiologists with varying levels of expertise, according to a study published December 12 in Radiology. In a retrospective study, a commercially available algorithm (ChestView, v. About 50% of the x-rays had abnormal findings.
An Australian radiologist fired after a colleague claimed he "performed a pelvic thrust" at her at a Christmas party has been awarded more than 350,000 Australian dollars ($237,000 U.S.) in damages, according to a report posted on news.com.au. The complaints were lodged after a December 2021 Christmas party and Daynes sought damages of 4.3
Two radiographers and two radiologists performed unblinded paired comparisons of images from both paddle types, using standard image quality criteria. points compared with the sham-paddle group (p However, the radiologists and radiographers differed in preference when it came to image quality.
AI algorithms appear to have clinical value based on detecting normal x-rays – that is, by flagging chest x-rays as normal versus abnormal, they may reduce reading times for radiologists, according to research presented recently at the RSNA meeting in Chicago. In a session on chest imaging, scientists from AI developers Lunit and DeepTek.ai
Its impact on radiographer workflow ranges from detecting poor image quality on x-ray; automating CT imaging protocols; and for MRI, streamlining workflows for faster scan times, image reconstruction, and using synthetic MRI sequences.
AI sharply reduces radiologist reading times on chest CT Monday, November 27 | 1:30 p.m.-1:40 M6-SSNPM01-1 | Room E351 With help from an AI algorithm, radiologists can detect and classify lung nodules on routine clinical chest CT exams faster and more effectively, according to this new study. 1:40 p.m. | 1:50 p.m. | 3:50 p.m. |
The first scans have been performed in the Olympic imaging polyclinic ahead of Friday's opening ceremony, and the 68-strong squad of radiologists and radiographers are primed and ready for action, according to musculoskeletal (MSK) expert Jérôme Renoux, MD. Bring it on!
Understanding the mechanics of flow artifacts on CT or CT angiography (CTA) and how these artifacts are created is key to better disease diagnosis, according to a review published April 25 in RadioGraphics. At first glance, flow artifacts may appear as a simple distractor to the discerning eye of a radiologist," Robb and colleagues noted.
Radiologists and X-ray technologists are required to manage increasingly demanding caseloads while facing challenges from long hours and repetitive heavy lifting. X-rays are the most widely used diagnostic tests, accounting for 60% of all imaging studies conducted. one of the largest weight capacities on the market.
Performing MRI scans on young children can be challenging for radiologists. Communication among practitioners: Effective communication between radiographers, radiologists, and child-life specialists is needed to discuss scan protocols, streamline the exam, and minimize table time.
Bersu Ozcan, MD, and Jessica Porembka, MD, both from the University of Texas Southwestern Medical Center, recently co-authored a comprehensive piece in RadioGraphics outlining the challenges breast radiologists face in this area. They also highlighted opportunities to successfully remove barriers for women.
Radiologists can help reduce unnecessary follow-up work in patients with suspected oropharynx cancer by analyzing certain metrics on PET/CT scans, according to a team of head and neck surgeons at the Mayo Clinic in Rochester, MN. The study was published August 29 in JAMA Otolaryngology-Head & Neck Surgery.
They posed the same questions to ChatGPT and then recruited 12 experts (four radiologists, four medical physicists, and four radiographers) from the U.S. and Europe to evaluate both sets of answers, blinded to the source.
AI and deep learning continue to be explored by radiologists for their potential to improve breast cancer diagnosis and prognosis. The researchers found that the combined model using images from both modalities, as well as pathological, clinical, and radiographic characteristics, had the highest predictive performance of the models analyzed.
Shamie Kumar describes how AI fits into a radiology clinical workflow and her perspective on how a clinical radiographer could use this to learn from and enhance their skills. If the AI findings are seen in PACS, how many radiographers actually log into PACS after taking a scan or X-ray? Can Radiographers Up-Skill?
Healthcare disparities continue to plague medical imaging, but there are concrete measures radiologists can take to mitigate them, according to a paper published on October 12 in RadioGraphics. Histopathologic biopsy results demonstrated invasive mammary carcinoma with metastatic disease in a right axillary lymph node.
“So we were thinking and asking ourselves, ‘can nonradiologists benefit from AI and chest radiography analysis in this emergency unit set.’ ” Per year, LMU receives between 5,000 and 6,000 orders for chest radiographs for primary diagnosis from the emergency unit alone.
Others on the team include lead investigator David Baldwin, MD, chair of NHS England’s Clinical Expert Group for Lung Cancer and a respiratory consultant at Nottingham University Hospitals, cardiothoracic radiologist Indrajeet Das, MD, and Prof. Neal Navani and Arjun Nair, MD, radiologists at UCLH.
Imaging was so important [for cardiac indications], that I decided to become a radiologist," he said. Together with our radiographers, I learned to scan cardiac patients and learned special anatomy from pediatric cardiologists and pediatric cardiac surgeons." How can radiologists become successful cardiac imagers? Just do it!"
Spirometry values were below predicted values and a standard chest radiograph depicted an elevated right hemidiaphragm that was not present on a prior CT examination during his SARS-CoV-2 infection. With the dynamic functional imaging capability of DDR, the authors could visualize thoracic and pulmonary motion and track diaphragm movement.
Dubai-based Zscale Labs is launching Neuromorphic AI, an AI software application for multilabel classification of chest radiographs. Neuromorphic AI leverages the firm's hyperdimensional computing and deep-learning technologies to assist radiologists and healthcare providers in diagnosing multiple chest conditions from x-ray images.
The team's review of MRI's role for this indication was published January 3 in RadioGraphics. Radiologists who interpret pelvic endometriosis studies should identify the pelvic nerves involved in endometriosis and report this information to the clinician for treatment planning and improved patient outcomes."
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