Osteologie, Table of Contents Osteologie 2021; 30(03): 261-263DOI: 10.1055/a-1534-3346 Gesellschaftsnachrichten Informationen der Arbeitsgemeinschaft Knochentumoren e. V. Artificial Intelligence (AI) for Radiological Diagnostics of Bone Tumors: Potential Approaches, Possibilities, and Limitations Claudio E. von Schacky Department of Radiology at Klinikum rechts der Isar, Technische Universität München, Ismaninger Str 22, 81675 Munich, Germany › Author Affiliations Recommend Article Abstract Buy Article Full Text References 1 Choy G, Khalilzadeh O, Michalski M. et al. Current Applications and Future Impact of Machine Learning in Radiology. Radiology 2018; 288: 318-328 2 Gillies RJ, Kinahan PE, Hricak H. Radiomics: Images Are More than Pictures, They Are Data. Radiology 2016; 278: 563-577 3 Fletcher CDM. WHO Classification of Tumours of Soft Tissue and Bone; 4th ed.: World Health Organization; 2013 4 Paszke A, Gross S, Chintala S et al. Automatic differentiation in PyTorch. In: NIPS-W; 2017 5 Lalam R, Bloem JL, Noebauer-Huhmann IM. et al. ESSR Consensus Document for Detection, Characterization, and Referral Pathway for Tumors and Tumorlike Lesions of Bone. Seminars in musculoskeletal radiology. 2017; 21: 630-647
