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AI can predict malignancy for multiple pulmonary nodules


A team of researchers from China and South Korea developed a machine-learning model that utilizes nodule characteristics on CT and pairs it with sociodemographic information to predict malignancy risk in patients with multiple pulmonary nodules. In testing, the algorithm called PKU-M yielded better results than previous models and also outperformed three thoracic surgeons and a radiologist in a prospective evaluation.
Our prediction model, which was exclusively established for patients with multiple nodules, can help not only mitigate unnecessary surgery but also facilitate the diagnosis and treatment of lung cancer, said co-author Dr. Young Tae Kim, PhD, of Seoul National University Hospital in a statement from the American Association for Cancer Research (AACR). ....

Soult Ukpyolsi , South Korea , United States , Jun Wang , Kezhong Chen , Seoul National University Hospital , American Association For Cancer Research , University People Hospital , Clinical Cancer Research , Clinical Cancer , Kyoung Tae Kim , American Association , Cancer Research , Peking University People , Medical Imaging , Artificial Intelligence , Deep Learning , Machine Learning , Pulmonary Nodules , Lung Nodules , Lung Cancer , Multiple Nodules , தெற்கு கொரியா , ஒன்றுபட்டது மாநிலங்களில் , ஜூன் வாங் , சியோல் தேசிய பல்கலைக்கழகம் மருத்துவமனை ,

Machine learning tool can predict malignancy in patients with multiple pulmonary nodules


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PHILADELPHIA - A machine learning-based tool was able to predict the risk of malignancy among patients presenting with multiple pulmonary nodules and outperformed human experts, previously validated mathematical models, and a previously established artificial intelligence tool, according to results published in
Clinical Cancer Research, a journal of the American Association for Cancer Research.
Tools currently available can predict malignancy in patients with single nodules; predictive tools for patients presenting with multiple nodules are limited.
With the adoption of widespread use of thoracic computed tomography (CT) for lung cancer screening, the detection of multiple pulmonary nodules has become increasingly common, said study author Kezhong Chen, MD, vice professor in the Department of Thoracic Surgery at Peking University People s Hospital in China. Among patients presenting with a pulmonary nodule on a CT scan in a previous lung cancer screeni ....

Soult Ukpyolsi , South Korea , United States , Jun Wang , Republic Of Korea , Richard Lobb , Kezhong Chen , American Association For Cancer Research , National Natural Science Foundation Of China , Cardiovascular Surgery At Seoul National University Hospital , Seoul National University College Of Medicine , University People Hospital , Department Of Thoracic , Clinical Cancer Research , American Association , Thoracic Surgery , Peking University People , Kyoung Tae Kim , Cardiovascular Surgery , Seoul National University Hospital , Seoul National University College , National Natural Science Foundation , Cancer Research , Scientific Partner , Stand Up To Cancer , Medicine Health ,