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For: Kleppe A, Skrede OJ, De Raedt S, Liestøl K, Kerr DJ, Danielsen HE. Designing deep learning studies in cancer diagnostics. Nat Rev Cancer 2021;21:199-211. [PMID: 33514930 DOI: 10.1038/s41568-020-00327-9] [Cited by in Crossref: 6] [Cited by in F6Publishing: 5] [Article Influence: 6.0] [Reference Citation Analysis]
Number Citing Articles
1 Waljee AK, Weinheimer-Haus EM, Abubakar A, Ngugi AK, Siwo GH, Kwakye G, Singal AG, Rao A, Saini SD, Read AJ, Baker JA, Balis U, Opio CK, Zhu J, Saleh MN. Artificial intelligence and machine learning for early detection and diagnosis of colorectal cancer in sub-Saharan Africa. Gut 2022:gutjnl-2022-327211. [PMID: 35418482 DOI: 10.1136/gutjnl-2022-327211] [Reference Citation Analysis]
2 Sun X, Feinberg MW. Vascular Endothelial Senescence: Pathobiological Insights, Emerging Long Noncoding RNA Targets, Challenges and Therapeutic Opportunities. Front Physiol 2021;12:693067. [PMID: 34220553 DOI: 10.3389/fphys.2021.693067] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
3 Bradshaw TJ, McMillan AB. Anatomy and Physiology of Artificial Intelligence in PET Imaging. PET Clin 2021:S1556-8598(21)00042-0. [PMID: 34364817 DOI: 10.1016/j.cpet.2021.06.003] [Reference Citation Analysis]
4 Flouris K, Jimenez-Del-Toro O, Aberle C, Bach M, Schaer R, Obmann MM, Stieltjes B, Müller H, Depeursinge A, Konukoglu E. Assessing radiomics feature stability with simulated CT acquisitions. Sci Rep 2022;12:4732. [PMID: 35304508 DOI: 10.1038/s41598-022-08301-1] [Reference Citation Analysis]
5 Saldanha OL, Quirke P, West NP, James JA, Loughrey MB, Grabsch HI, Salto-Tellez M, Alwers E, Cifci D, Ghaffari Laleh N, Seibel T, Gray R, Hutchins GGA, Brenner H, van Treeck M, Yuan T, Brinker TJ, Chang-Claude J, Khader F, Schuppert A, Luedde T, Trautwein C, Muti HS, Foersch S, Hoffmeister M, Truhn D, Kather JN. Swarm learning for decentralized artificial intelligence in cancer histopathology. Nat Med 2022. [PMID: 35469069 DOI: 10.1038/s41591-022-01768-5] [Reference Citation Analysis]
6 Xue P, Wang J, Qin D, Yan H, Qu Y, Seery S, Jiang Y, Qiao Y. Deep learning in image-based breast and cervical cancer detection: a systematic review and meta-analysis. NPJ Digit Med 2022;5:19. [PMID: 35169217 DOI: 10.1038/s41746-022-00559-z] [Reference Citation Analysis]
7 Chen P, Chen Xu R, Chen N, Zhang L, Zhang L, Zhu J, Pan B, Wang B, Guo W. Detection of Metastatic Tumor Cells in the Bone Marrow Aspirate Smears by Artificial Intelligence (AI)-Based Morphogo System. Front Oncol 2021;11:742395. [PMID: 34646779 DOI: 10.3389/fonc.2021.742395] [Reference Citation Analysis]
8 Echle A, Ghaffari Laleh N, Quirke P, Grabsch HI, Muti HS, Saldanha OL, Brockmoeller SF, van den Brandt PA, Hutchins GGA, Richman SD, Horisberger K, Galata C, Ebert MP, Eckardt M, Boutros M, Horst D, Reissfelder C, Alwers E, Brinker TJ, Langer R, Jenniskens JCA, Offermans K, Mueller W, Gray R, Gruber SB, Greenson JK, Rennert G, Bonner JD, Schmolze D, Chang-Claude J, Brenner H, Trautwein C, Boor P, Jaeger D, Gaisa NT, Hoffmeister M, West NP, Kather JN. Artificial intelligence for detection of microsatellite instability in colorectal cancer-a multicentric analysis of a pre-screening tool for clinical application. ESMO Open 2022;7:100400. [PMID: 35247870 DOI: 10.1016/j.esmoop.2022.100400] [Reference Citation Analysis]
9 Qi W, Chen R, Chen M, Zhao M, Wang M, Sun L. Evaluation Analysis of the Nephrotoxicity of Tripterygium wilfordii Preparations with CONSORT Harms Statement Based on Deep Learning. Journal of Healthcare Engineering 2022;2022:1-7. [DOI: 10.1155/2022/5054932] [Reference Citation Analysis]
10 Cyll K, Kleppe A, Kalsnes J, Vlatkovic L, Pradhan M, Kildal W, Tobin KAR, Reine TM, Wæhre H, Brennhovd B, Askautrud HA, Skaaheim Haug E, Hveem TS, Danielsen HE. PTEN and DNA Ploidy Status by Machine Learning in Prostate Cancer. Cancers (Basel) 2021;13:4291. [PMID: 34503100 DOI: 10.3390/cancers13174291] [Reference Citation Analysis]
11 Ramesh S, Chokkara S, Shen T, Major A, Volchenboum SL, Mayampurath A, Applebaum MA. Applications of Artificial Intelligence in Pediatric Oncology: A Systematic Review. JCO Clin Cancer Inform 2021;5:1208-19. [PMID: 34910588 DOI: 10.1200/CCI.21.00102] [Reference Citation Analysis]
12 Kleppe A. Area under the curve may hide poor generalisation to external datasets. ESMO Open 2022;7:100429. [PMID: 35397433 DOI: 10.1016/j.esmoop.2022.100429] [Reference Citation Analysis]
13 Budhwani KI, Patel ZH, Guenter RE, Charania AA. A hitchhiker’s guide to cancer models. Trends in Biotechnology 2022. [DOI: 10.1016/j.tibtech.2022.04.003] [Reference Citation Analysis]
14 Alabi RO, Almangush A, Elmusrati M, Mäkitie AA. Deep Machine Learning for Oral Cancer: From Precise Diagnosis to Precision Medicine. Front Oral Health 2022;2:794248. [DOI: 10.3389/froh.2021.794248] [Reference Citation Analysis]
15 Boehm KM, Khosravi P, Vanguri R, Gao J, Shah SP. Harnessing multimodal data integration to advance precision oncology. Nat Rev Cancer 2021. [PMID: 34663944 DOI: 10.1038/s41568-021-00408-3] [Cited by in Crossref: 2] [Article Influence: 2.0] [Reference Citation Analysis]
16 Delaune A, Valmary-degano S, Loménie N, Zryouil K, Benyahia N, Trassard O, Eraville V, Bergeron C, Devouassoux-shisheboran M, Glaser C, Bataillon G, Bacry E, Combes S, Prevot S, Bertheau P. Le premier data challenge organisé par la Société Française de Pathologie : une compétition internationale en 2020, un outil de recherche en intelligence artificielle pour l’avenir ? Annales de Pathologie 2022. [DOI: 10.1016/j.annpat.2021.10.002] [Reference Citation Analysis]
17 Huang X, Huang K, Johnson T, Radovich M, Zhang J, Ma J, Wang Y. ParsVNN: parsimony visible neural networks for uncovering cancer-specific and drug-sensitive genes and pathways. NAR Genom Bioinform 2021;3:lqab097. [PMID: 34729476 DOI: 10.1093/nargab/lqab097] [Reference Citation Analysis]
18 Mertens S, Krois J, Cantu AG, Arsiwala LT, Schwendicke F. Artificial intelligence for caries detection: Randomized trial. J Dent 2021;115:103849. [PMID: 34656656 DOI: 10.1016/j.jdent.2021.103849] [Reference Citation Analysis]
19 Amouheidari A, Alirezaei Z, Rauh S, Hassanpour M, Kanat O. PrACTiC: A Predictive Algorithm for Chemoradiotherapy-Induced Cytopenia in Glioblastoma Patients. Journal of Oncology 2022;2022:1-7. [DOI: 10.1155/2022/1438190] [Reference Citation Analysis]
20 Wang Y, Tan H, Yu T, Ma X, Chen X, Jing F, Zou L, Shi H. The identification of gene signatures in patients with extranodal NK/T-cell lymphoma from a pair of twins. BMC Cancer 2021;21:1303. [PMID: 34872521 DOI: 10.1186/s12885-021-09023-9] [Reference Citation Analysis]
21 van der Laak J, Litjens G, Ciompi F. Deep learning in histopathology: the path to the clinic. Nat Med 2021;27:775-84. [PMID: 33990804 DOI: 10.1038/s41591-021-01343-4] [Cited by in Crossref: 4] [Cited by in F6Publishing: 10] [Article Influence: 4.0] [Reference Citation Analysis]
22 Nam D, Chapiro J, Paradis V, Seraphin TP, Kather JN. Artificial intelligence in liver diseases: improving diagnostics, prognostics and response prediction. JHEP Reports 2022. [DOI: 10.1016/j.jhepr.2022.100443] [Reference Citation Analysis]
23 Schwendicke F, Mertens S, Cantu AG, Chaurasia A, Meyer-Lueckel H, Krois J. Cost-effectiveness of AI for Caries Detection: Randomized Trial. J Dent 2022;:104080. [PMID: 35245626 DOI: 10.1016/j.jdent.2022.104080] [Reference Citation Analysis]