| Editor's Choice: Artificial Intelligence | | Artificial intelligence (AI) tools should always be tested across “a wide range of populations,” according to new research published in PLOS Medicine. The authors shared this warning after seeing some models perform worse when tested on data from an outside health system. Artificial intelligence (AI) tools should always be tested across “a wide range of populations,” according to new research published in PLOS Medicine. The authors shared this warning after seeing some models perform worse when tested on data from an outside health system. | |
| Machine learning (ML) has become one of the hottest topics in radiology and all of healthcare, but reading the latest and greatest ML research can be difficult, even for experienced medical professionals. A new analysis published in the American Journal of Roentgenology was written with that very problem in mind. Machine learning (ML) has become one of the hottest topics in radiology and all of healthcare, but reading the latest and greatest ML research can be difficult, even for experienced medical professionals. A new analysis published in the American Journal of Roentgenology was written with that very problem in mind. | |
| | MaxQ AI’s Accipio Ix intracranial hemorrhage (ICH) detection software has gained FDA clearance, the company announced this week. MaxQ AI’s Accipio Ix intracranial hemorrhage (ICH) detection software has gained FDA clearance, the company announced this week. | |
| A deep learning algorithm developed using imaging data from more than 1,000 Alzheimer’s disease (AD) patients can accurately predict the presence of AD more than six years before a doctor finalizes a diagnosis, researchers reported in Radiology Nov. 6. A deep learning algorithm developed using imaging data from more than 1,000 Alzheimer’s disease (AD) patients can accurately predict the presence of AD more than six years before a doctor finalizes a diagnosis, researchers reported in Radiology Nov. 6. | |
| Convolutional neural networks (CNNs) trained with 20,000 labeled images can accurately classify chest x-rays as normal or abnormal, according to new findings published in Radiology. Training the CNN with an additional 180,000 images, the authors noted, only yielded “marginal” benefits. Convolutional neural networks (CNNs) trained with 20,000 labeled images can accurately classify chest x-rays as normal or abnormal, according to new findings published in Radiology. Training the CNN with an additional 180,000 images, the authors noted, only yielded “marginal” benefits. | |
| As AI-related medical devices continue to saturate the healthcare market, regulatory agencies like the FDA are struggling to keep up with a new category of technology. As AI-related medical devices continue to saturate the healthcare market, regulatory agencies like the FDA are struggling to keep up with a new category of technology. | |
| Artificial intelligence (AI) can help predict how a breast tumor will respond to neoadjuvant chemotherapy (NAC), according to new findings published in the Journal of Digital Imaging. Artificial intelligence (AI) can help predict how a breast tumor will respond to neoadjuvant chemotherapy (NAC), according to new findings published in the Journal of Digital Imaging. | |
| On Oct. 26, the American College of Radiology Data Science Institute (ACR DSI) announced the release of standardized artificial intelligence (AI) use cases designed to improve AI adoption in radiology. Why, exactly, are these use cases so vital to the specialty? On Oct. 26, the American College of Radiology Data Science Institute (ACR DSI) announced the release of standardized artificial intelligence (AI) use cases designed to improve AI adoption in radiology. Why, exactly, are these use cases so vital to the specialty? | |
| A deep learning algorithm can automatically detect lumbar vertebrae in MRI images, according to findings published in the Journal of Digital Imaging. This, the authors noted, has potential to improve clinician efficiency. A deep learning algorithm can automatically detect lumbar vertebrae in MRI images, according to findings published in the Journal of Digital Imaging. This, the authors noted, has potential to improve clinician efficiency. | |
| A natural language processing (NLP) and machine learning algorithm was trained to evaluate variability in both free-text radiology reports and structured radiology reports, according to new research published in Current Problems in Diagnostic Radiology. The variation was more prevalent in free-text reports. A natural language processing (NLP) and machine learning algorithm was trained to evaluate variability in both free-text radiology reports and structured radiology reports, according to new research published in Current Problems in Diagnostic Radiology. The variation was more prevalent in free-text reports. | |
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