Artificial intelligence solution to classify pulmonary nodules on CT

Blanc, D; Racine, Victor; Khalil, Antoine; Deloche, M.; Broyelle, J.-A.; Hammouamri, I.; Sinitambirivoutin, E.; Fiammante, M.; Verdier, E.; Besson, T.; Sadate, Alexandre; Léderlin, Mathieu; Laurent, François; Chassagnon, Guillaume; Ferretti, G.; Diascorn, Yann; Brillet, Pierre Yves; Cassagnes, L.; Caramella, Caroline; Loubet, Antoine; Abassebay, N.; Cuingnet, Philippe; Ohana, Mickaël; Behr, Julien; Ginzac, Angeline; Veyssière, Hugo; Durando, Xavier; Bousaid, Imad; Lassau, Nathalie; Brehant, J

doi:10.1016/j.diii.2020.10.004

Cited by 35 publications

(10 citation statements)

References 31 publications

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“…Nowadays, the superiority of computers over humans is not a matter of debate; rather, the question is centered around how the practice of medicine can benefit from these capabilities [ 18 ]. The detection of pulmonary nodules and wrist fractures has been shown to be enhanced by the use of AI [ 19 , 20 , 21 ]. Nevertheless, this may lead to a concern in regard to biasing the physician’s decision [ 22 ].…”

Section: Discussionmentioning

confidence: 99%

Radiology Community Attitude in Saudi Arabia about the Applications of Artificial Intelligence in Radiology

et al. 2021

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Artificial intelligence (AI) is a broad, umbrella term that encompasses the theory and development of computer systems able to perform tasks normally requiring human intelligence. The aim of this study is to assess the radiology community’s attitude in Saudi Arabia toward the applications of AI. Methods: Data for this study were collected using electronic questionnaires in 2019 and 2020. The study included a total of 714 participants. Data analysis was performed using SPSS Statistics (version 25). Results: The majority of the participants (61.2%) had read or heard about the role of AI in radiology. We also found that radiologists had statistically different responses and tended to read more about AI compared to all other specialists. In addition, 82% of the participants thought that AI must be included in the curriculum of medical and allied health colleges, and 86% of the participants agreed that AI would be essential in the future. Even though human–machine interaction was considered to be one of the most important skills in the future, 89% of the participants thought that it would never replace radiologists. Conclusion: Because AI plays a vital role in radiology, it is important to ensure that radiologists and radiographers have at least a minimum understanding of the technology. Our finding shows an acceptable level of knowledge regarding AI technology and that AI applications should be included in the curriculum of the medical and health sciences colleges.

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Section: Discussionmentioning

confidence: 99%

Radiology Community Attitude in Saudi Arabia about the Applications of Artificial Intelligence in Radiology

et al. 2021

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“… 44 CAD systems based on DL algorithms detect more pulmonary nodules on CT scans compared to double reading by radiologists 45 and allow to classify the detected nodules based on selected features. 46 Another DL-based CAD algorithm outperformed thoracic radiologists for the detection of malignant pulmonary nodules on chest x-rays and improved radiologists’ performance when used as a second reader. 47 …”

Section: Lesion Detection and Screeningmentioning

confidence: 99%

Artificial Intelligence in the Era of Precision Oncological Imaging

Cellina

Cè

Khenkina

et al. 2022

Technol Cancer Res Treat

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Rapid-paced development and adaptability of artificial intelligence algorithms have secured their almost ubiquitous presence in the field of oncological imaging. Artificial intelligence models have been created for a variety of tasks, including risk stratification, automated detection, and segmentation of lesions, characterization, grading and staging, prediction of prognosis, and treatment response. Soon, artificial intelligence could become an essential part of every step of oncological workup and patient management. Integration of neural networks and deep learning into radiological artificial intelligence algorithms allow for extrapolating imaging features otherwise inaccessible to human operators and pave the way to truly personalized management of oncological patients. Although a significant proportion of currently available artificial intelligence solutions belong to basic and translational cancer imaging research, their progressive transfer to clinical routine is imminent, contributing to the development of a personalized approach in oncology. We thereby review the main applications of artificial intelligence in oncological imaging, describe the example of their successful integration into research and clinical practice, and highlight the challenges and future perspectives that will shape the field of oncological radiology.

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“…AI technology is actively used in the medical field as well, and its effectiveness has been demonstrated in various results such as medical image analysis and omics analysis [1,[32][33][34][35][36][37][38][39]. In the field of oncology, the introduction of AI is also being actively studied in tumor screening, including lung and breast cancer [40,41]. Practically, as of 2020, more than 60 AI-powered medical devices have been approved by the US FDA (Table 1).…”

Section: The Third Ai Boom and Era Of Deep Learningmentioning

confidence: 99%

Application of Artificial Intelligence Technology in Oncology: Towards the Establishment of Precision Medicine

Hamamoto

Suvarna

Yamada³

et al. 2020

Cancers

132

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In recent years, advances in artificial intelligence (AI) technology have led to the rapid clinical implementation of devices with AI technology in the medical field. More than 60 AI-equipped medical devices have already been approved by the Food and Drug Administration (FDA) in the United States, and the active introduction of AI technology is considered to be an inevitable trend in the future of medicine. In the field of oncology, clinical applications of medical devices using AI technology are already underway, mainly in radiology, and AI technology is expected to be positioned as an important core technology. In particular, “precision medicine,” a medical treatment that selects the most appropriate treatment for each patient based on a vast amount of medical data such as genome information, has become a worldwide trend; AI technology is expected to be utilized in the process of extracting truly useful information from a large amount of medical data and applying it to diagnosis and treatment. In this review, we would like to introduce the history of AI technology and the current state of medical AI, especially in the oncology field, as well as discuss the possibilities and challenges of AI technology in the medical field.

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Artificial intelligence solution to classify pulmonary nodules on CT

Cited by 35 publications

References 31 publications

Radiology Community Attitude in Saudi Arabia about the Applications of Artificial Intelligence in Radiology

Radiology Community Attitude in Saudi Arabia about the Applications of Artificial Intelligence in Radiology

Artificial Intelligence in the Era of Precision Oncological Imaging

Application of Artificial Intelligence Technology in Oncology: Towards the Establishment of Precision Medicine

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