Incidental pulmonary emboli are associated with a very high probability of progressive malignant disease on staging CT scans

Goh, Lu Hern; Tenant, Sean

doi:10.1007/s11604-022-01280-3

Cited by 2 publications

(1 citation statement)

References 25 publications

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“…PE carries a high burden of morbidity and mortality. There is also a report demonstrated that the detection of an incidental PE on a staging CT scan is associated with a very high risk of progressive malignancy [ 98 ]. Timely and precise diagnosis enables the acceleration of treatment, a crucial factor in potentially reducing mortality rates and enhancing patient outcomes [ 99 – 101 ].…”

Section: Methodsmentioning

confidence: 99%

New trend in artificial intelligence-based assistive technology for thoracic imaging

Yanagawa,

Ito,

Nozaki

et al. 2023

Radiol med

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Although there is no solid agreement for artificial intelligence (AI), it refers to a computer system with intelligence similar to that of humans. Deep learning appeared in 2006, and more than 10 years have passed since the third AI boom was triggered by improvements in computing power, algorithm development, and the use of big data. In recent years, the application and development of AI technology in the medical field have intensified internationally. There is no doubt that AI will be used in clinical practice to assist in diagnostic imaging in the future. In qualitative diagnosis, it is desirable to develop an explainable AI that at least represents the basis of the diagnostic process. However, it must be kept in mind that AI is a physician-assistant system, and the final decision should be made by the physician while understanding the limitations of AI. The aim of this article is to review the application of AI technology in diagnostic imaging from PubMed database while particularly focusing on diagnostic imaging in thorax such as lesion detection and qualitative diagnosis in order to help radiologists and clinicians to become more familiar with AI in thorax.

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Section: Methodsmentioning

confidence: 99%