Diagnostische Radiologie

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Rofo 192(7):641–656 Olthof AW, Borstlap J, Roeloffzen WW, Callenbach PMC, van Ooijen PMA (2018) Improvement of radiology reporting in a clinical cancer network: impact of an optimised multidisciplinary workflow. Eur Radiol 28(10):4274–4280 Aerts HJWL, Velazquez ER, Leijenaar RTH, Parmar C, Grossmann P, Cavalho S et al (2014) Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach. Nat Commun 5:4006 Zhang KS, Schelb P, Kohl S, Radtke JP, Wiesenfarth M, Schimmöller L et al (2021) Improvement of PI-RADS-dependent prostate cancer classification by quantitative image assessment using radiomics or mean ADC. Magn Reson Imaging 82:9–17 Bonekamp D, Schlemmer H‑P (2021) Machine learning and multiparametric MRI for early diagnosis of prostate cancer. Urologe A 60(5):576–591 Baeßler B, Weiss K, dos Santos DP (2019) Robustness and reproducibility of radiomics in magnetic resonance imaging: a phantom study. Invest Radiol 54(4):221–228 Meyer M, Ronald J, Vernuccio F, Nelson RC, Ramirez-Giraldo JC, Solomon J et al (2019) Reproducibility of CT radiomic features within the same patient: influence of radiation dose and CT reconstruction settings. Radiology 293(3):583–591 Zwanenburg A, Vallières M, Abdalah MA, Aerts HJWL, Andrearczyk V, Apte A et al (2020) The image biomarker standardization initiative: standardized quantitative radiomics for high-throughput image-based phenotyping. Radiology 295(2):328–338 Bluemke DA, Moy L, Bredella MA, Ertl-Wagner BB, Fowler KJ, Goh VJ et al (2020) Assessing radiology research on artificial intelligence: a brief guide for authors, reviewers, and readers—from the radiology editorial board. Radiology 294(3):487–489 Benjamens S, Dhunnoo P, Meskó B (2020) The state of artificial intelligence-based FDA-approved medical devices and algorithms: an online database. NPJ Digit Med 3(1):118 Curtis C, Liu C, Bollerman TJ, Pianykh OS (2018) Machine learning for predicting patient wait times and appointment delays. J Am Coll Radiol 15(9):1310–1316 Singh R, Wu W, Wang G, Kalra MK (2020) Artificial intelligence in image reconstruction: the change is here. Phys Med 79:113–125 Arbabshirani MR, Fornwalt BK, Mongelluzzo GJ, Suever JD, Geise BD, Patel AA et al (2018) Advanced machine learning in action: identification of intracranial hemorrhage on computed tomography scans of the head with clinical workflow integration. NPJ Digit Med. https://doi.org/10.1038/s41746-017-0015-z Dratsch T, Korenkov M, Zopfs D, Brodehl S, Baessler B, Giese D et al (2021) Practical applications of deep learning: classifying the most common categories of plain radiographs in a PACS using a neural network. Eur Radiol 31(4):1812–1818 Bonekamp D, Schlemmer H‑P (2022) Artificial intelligence (AI) in radiology? : do we need as many radiologists in the future? Urologe A 61(4):392–399 Schlemmer H‑P, Hohenfellner M (2021) Chancen von KI in der Onkologie am Beispiel der individualisierten Diagnostik und Behandlung von Prostatakrebs = Opportunities of AI in oncology using the example of individualized diagnosis and treatment of prostate cancer. Z Med Ethik 67(3):309–326 Perry TS, Ng A (2021) X‑rays the AI hype (IEEE, Spectrum) Huisman M, Ranschaert E, Parker W, Mastrodicasa D, Koci M, Pinto de Santos D et al (2021) An international survey on AI in radiology in 1041 radiologists and radiology residents part 2: expectations, hurdles to implementation, and education. Eur Radiol 31(11):8797–8806. https://doi.org/10.1007/s00330-021-07782-4 Nagendran M, Chen Y, Lovejoy CA, Gordon AC, Komorowski M, Harvey H et al (2020) Artificial intelligence versus clinicians: systematic review of design, reporting standards, and claims of deep learning studies. BMJ. https://doi.org/10.1136/bmj.m689 McKinney SM, Sieniek M, Godbole V, Godwin J, Antropova N, Ashrafian H et al (2020) International evaluation of an AI system for breast cancer screening. Nature 577(7788):89–94. https://doi.org/10.1038/s41586-019-1799-6 BMBF (2021) Newsletter 101 – Gemeinsam im Bilde mit der Joint Imaging Platform Scherer J, Nolden M, Kleesiek J, Metzger J, Kades K, Schneider V et al (2020) Joint imaging platform for federated clinical data analytics. JCO Clin Cancer Inform 4:1027–1038 Iuga A‑I, Lossau T, Caldeira LL, Rinneburger M, Lennartz S, Große Hokamp N et al (2021) Automated mapping and N‑staging of thoracic lymph nodes in contrast-enhanced CT scans of the chest using a fully convolutional neural network. Eur J Radiol 139:109718 Lennartz S, Dratsch T, Zopfs D, Persigehl T, Maintz D, Große Hokamp N et al (2021) Use and control of artificial intelligence in patients across the medical workflow: single-center questionnaire study of patient perspectives. J Med Internet Res 23(2):e24221