The promise and limitations of artificial intelligence in CTPA-based pulmonary embolism detection

Frontiers in Medicine, Год журнала: 2025, Номер 12

Опубликована: Март 19, 2025

Computed tomography pulmonary angiography (CTPA) is an essential diagnostic tool for identifying embolism (PE). The integration of AI has significantly advanced CTPA-based PE detection, enhancing accuracy and efficiency. This review investigates the growing role in diagnosis using CTPA imaging. examines capabilities algorithms, particularly deep learning models, analyzing images detection. It assesses their sensitivity specificity compared to human radiologists. systems, large datasets complex neural networks, demonstrate remarkable proficiency subtle signs PE, aiding clinicians timely accurate diagnosis. In addition, AI-powered analysis shows promise risk stratification, prognosis prediction, treatment optimization patients. Automated image interpretation quantitative facilitate rapid triage suspected cases, enabling prompt intervention reducing delays. Despite these advancements, several limitations remain, including algorithm bias, interpretability issues, necessity rigorous validation, which hinder widespread adoption clinical practice. Furthermore, integrating into existing healthcare systems requires careful consideration regulatory, ethical, legal implications. conclusion, AI-driven detection presents unprecedented opportunities enhance precision However, addressing associated critical safe effective implementation routine Successful utilization revolutionizing care necessitates close collaboration among researchers, medical professionals, regulatory organizations.

Язык: Английский

Ethical and Regulatory Considerations of AI in Nuclear Medicine

Advances in computational intelligence and robotics book series, Год журнала: 2025, Номер unknown, С. 29 - 50

Опубликована: Фев. 28, 2025

Healthcare, where its integration into nuclear medicine is redefining how diseases are diagnosed, treated, and managed. Nuclear medicine, which uses small amounts of radioactive materials for diagnostic imaging therapeutic purposes, has long been pivotal in detecting conditions neurological incorporation AI this field promises to revolutionize practice by optimizing workflows enhancing despite potential, also comes with benefits. precision. Analyze data remarkable accuracy, often surpassing human performance subtle patterns. For example, can identify minute abnormalities that might overlooked observers. This precision survival rates. Furthermore, AI's capacity quantitative analysis allows it provide objective measurements tracer uptake target tissues, reducing variability interpretation ensuring consistent outcomes. potentially streamlines clinical workflows.

Язык: Английский

Imaging Tumor Metabolism and Its Heterogeneity: Special Focus on Radiomics and AI

Interdisciplinary cancer research, Год журнала: 2024, Номер unknown

Опубликована: Янв. 1, 2024

Язык: Английский