Editorial for "Performance of Artificial Intelligence-Aided Diagnosis System for Clinically Significant Prostate Cancer with MRI: A Diagnostic Comparison Study".

التفاصيل البيبلوغرافية
العنوان:	Editorial for "Performance of Artificial Intelligence-Aided Diagnosis System for Clinically Significant Prostate Cancer with MRI: A Diagnostic Comparison Study".
المؤلفون:	Nather JC; Department of Medical Images, Oncology and Hematology, Ribeirao Preto Medical School, University of Sao Paulo, Ribeirao Preto, São Paulo, Brazil., Muglia VF; Department of Medical Images, Oncology and Hematology, Ribeirao Preto Medical School, University of Sao Paulo, Ribeirao Preto, São Paulo, Brazil.
المصدر:	Journal of magnetic resonance imaging : JMRI [J Magn Reson Imaging] 2023 May; Vol. 57 (5), pp. 1365-1366. Date of Electronic Publication: 2022 Sep 23.
نوع المنشور:	Editorial; Comment
اللغة:	English
بيانات الدورية:	Publisher: Wiley-Liss Country of Publication: United States NLM ID: 9105850 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1522-2586 (Electronic) Linking ISSN: 10531807 NLM ISO Abbreviation: J Magn Reson Imaging Subsets: MEDLINE
أسماء مطبوعة:	Publication: <2005-> : Hoboken , N.J. : Wiley-Liss Original Publication: Chicago, IL : Society for Magnetic Resonance Imaging, c1991-
مواضيع طبية MeSH:	Artificial Intelligence* , Prostatic Neoplasms*, Male ; Humans ; Magnetic Resonance Imaging
التعليقات:	Comment on: J Magn Reson Imaging. 2023 May;57(5):1352-1364. (PMID: 36222324)
References:	Culp MB, Soerjomataram I, Efstathiou JA, Bray F, Jemal A. Recent global patterns in prostate cancer incidence and mortality rates. Eur Urol 2020;77:38-52. Mottet N, van den Bergh RCN, Briers E, et al. EAU-EANM-ESTRO-ESUR-SIOG guidelines on prostate Cancer-2020 update. Part 1: Screening, diagnosis, and local treatment with curative intent. Eur Urol 2021;79(2):243-262. Epub ahead of Print. Barrett T, Ghafoor S, Gupta RT, et al. Prostate MRI qualification: AJR Expert Panel Narrative Review. Am J Roentgen 2022;1-12. https://doi.org/10.2214/AJR.22.27615. Smith CP, Harmon SA, Barrett T, et al. Intra- and interreader reproducibility of PI-RADSv2: A multireader study. J Magn Reson Imaging 2019;49:1694-1703. Sunoqrot MR, Saha A, Hosseinzadeh M, Elschot M, Huisman H. Artificial intelligence for prostate MRI: Open datasets, available applications, and grand challenges. Eur Radiol Exp 2022;6:35-47. Westphalen AC, McCulloch CE, Anaokar JM, et al. Variability of the positive predictive value of PI-RADS for prostate MRI across 26 centers: Experience of the Society of Abdominal Radiology prostate cancer disease-focused panel. Radiology 2020;296(1):76-84. Jiang K-W, Song Y, Hou Y, et al. Performance of artificial intelligence-aided diagnosis system for clinically significant prostate cancer with MRI: a diagnostic comparison study. J Magn Reson Imaging 2023;57(5):1352-1364. Sanford T, Harmon SA, Turkbey EB, et al. Deep-learning-based artificial intelligence for PI-RADS classification to assist multiparametric prostate MRI interpretation: A development study. J Magn Reson Imaging 2020;52:1499-1507.
تواريخ الأحداث:	Date Created: 20220923 Date Completed: 20230407 Latest Revision: 20230622
رمز التحديث:	20230623
DOI:	10.1002/jmri.28428
PMID:	36148974
قاعدة البيانات:	MEDLINE

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تدمد:	1522-2586
DOI:	10.1002/jmri.28428