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For: 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: 105] [Cited by in F6Publishing: 111] [Article Influence: 105.0] [Reference Citation Analysis]
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8 Gerussi A, Scaravaglio M, Cristoferi L, Verda D, Milani C, De Bernardi E, Ippolito D, Asselta R, Invernizzi P, Kather JN, Carbone M. Artificial intelligence for precision medicine in autoimmune liver disease. Front Immunol 2022;13. [DOI: 10.3389/fimmu.2022.966329] [Reference Citation Analysis]
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10 Wagner P, Strodthoff N, Wurzel P, Marban A, Scharf S, Schäfer H, Seegerer P, Loth A, Hartmann S, Klauschen F, Müller K, Samek W, Hansmann M. New definitions of human lymphoid and follicular cell entities in lymphatic tissue by machine learning. Sci Rep 2022;12:18991. [DOI: 10.1038/s41598-022-18097-9] [Reference Citation Analysis]
11 Chung A, Nasralla D, Quaglia A. Understanding the Immunoenvironment of Primary Liver Cancer: A Histopathology Perspective. J Hepatocell Carcinoma 2022;9:1149-69. [PMID: 36349146 DOI: 10.2147/JHC.S382310] [Reference Citation Analysis]
12 Dolezal JM, Srisuwananukorn A, Karpeyev D, Ramesh S, Kochanny S, Cody B, Mansfield AS, Rakshit S, Bansal R, Bois MC, Bungum AO, Schulte JJ, Vokes EE, Garassino MC, Husain AN, Pearson AT. Uncertainty-informed deep learning models enable high-confidence predictions for digital histopathology. Nat Commun 2022;13:6572. [PMID: 36323656 DOI: 10.1038/s41467-022-34025-x] [Reference Citation Analysis]
13 Ji J, Wan T, Chen D, Wang H, Zheng M, Qin Z. A deep learning method for automatic evaluation of diagnostic information from multi-stained histopathological images. Knowledge-Based Systems 2022;256:109820. [DOI: 10.1016/j.knosys.2022.109820] [Reference Citation Analysis]
14 Lin Z, He Y, Qiu C, Yu Q, Huang H, Yiwen Zhang, Li W, Qiu T, Xiaoping Li. A multi-omics signature to predict the prognosis of invasive ductal carcinoma of the breast. Computers in Biology and Medicine 2022. [DOI: 10.1016/j.compbiomed.2022.106291] [Reference Citation Analysis]
15 Ho DJ, Chui MH, Vanderbilt CM, Jung J, Robson ME, Park C, Roh J, Fuchs TJ. Deep Interactive Learning-based ovarian cancer segmentation of H&E-stained whole slide images to study morphological patterns of BRCA mutation. Journal of Pathology Informatics 2022. [DOI: 10.1016/j.jpi.2022.100160] [Reference Citation Analysis]
16 Schuhmacher D, Schörner S, Küpper C, Großerueschkamp F, Sternemann C, Lugnier C, Kraeft A, Jütte H, Tannapfel A, Reinacher-schick A, Gerwert K, Mosig A. A framework for falsifiable explanations of machine learning models with an application in computational pathology. Medical Image Analysis 2022;82:102594. [DOI: 10.1016/j.media.2022.102594] [Reference Citation Analysis]
17 Li B, Nelson MS, Savari O, Loeffler AG, Eliceiri KW. Differentiation of pancreatic ductal adenocarcinoma and chronic pancreatitis using graph neural networks on histopathology and collagen fiber features. Journal of Pathology Informatics 2022. [DOI: 10.1016/j.jpi.2022.100158] [Reference Citation Analysis]
18 Yildiz S, Memis A, Varl S. Nuclei Segmentation in Colon Histology Images by Using the Deep CNNs: A U-Net Based Multi-class Segmentation Analysis. 2022 Medical Technologies Congress (TIPTEKNO) 2022. [DOI: 10.1109/tiptekno56568.2022.9960188] [Reference Citation Analysis]
19 Rasmussen SA, Taylor VJ, Surette AP, Barnes PJ, Bethune GC. Using Deep Learning to Predict Final HER2 Status in Invasive Breast Cancers That are Equivocal (2+) by Immunohistochemistry. Appl Immunohistochem Mol Morphol 2022. [PMID: 36251973 DOI: 10.1097/PAI.0000000000001079] [Reference Citation Analysis]
20 Lipkova J, Chen RJ, Chen B, Lu MY, Barbieri M, Shao D, Vaidya AJ, Chen C, Zhuang L, Williamson DF, Shaban M, Chen TY, Mahmood F. Artificial intelligence for multimodal data integration in oncology. Cancer Cell 2022;40:1095-1110. [DOI: 10.1016/j.ccell.2022.09.012] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
21 Mckinnon BD, Nirgianakis K, Ma L, Wotzkow CA, Steiner S, Blank F, Mueller MD. Computer-Aided Histopathological Characterisation of Endometriosis Lesions. JPM 2022;12:1519. [DOI: 10.3390/jpm12091519] [Reference Citation Analysis]
22 Tiu E, Talius E, Patel P, Langlotz CP, Ng AY, Rajpurkar P. Expert-level detection of pathologies from unannotated chest X-ray images via self-supervised learning. Nat Biomed Eng. [DOI: 10.1038/s41551-022-00936-9] [Reference Citation Analysis]
23 Jung J, Kim E, Lee H, Lee SH, Ahn S. Automated Hybrid Model for Detecting Perineural Invasion in the Histology of Colorectal Cancer. Applied Sciences 2022;12:9159. [DOI: 10.3390/app12189159] [Reference Citation Analysis]
24 Liu X, Wang J, Rui X, Zhang J, Sun G. Application of GIS Technology-Supported Cross Media Fusion Method Based on Deep Learning in Landscape Performance Evaluation. Computational Intelligence and Neuroscience 2022;2022:1-8. [DOI: 10.1155/2022/8339895] [Reference Citation Analysis]
25 Jiang P, Sinha S, Aldape K, Hannenhalli S, Sahinalp C, Ruppin E. Big data in basic and translational cancer research. Nat Rev Cancer 2022. [PMID: 36064595 DOI: 10.1038/s41568-022-00502-0] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
26 Berbís MA, Mcclintock DS, Bychkov A, Cheng JY, Delahunt B, Egevad L, Eloy C, Farris AB, Fraggetta F, García del Moral R, Hartman DJ, Herrmann MD, Hollemans E, Iczkowski KA, Karsan A, Kriegsmann M, Lennerz JK, Pantanowitz L, Salama ME, Sinard J, Tuthill M, Van der Laak J, Williams B, Casado-sánchez C, Sánchez-turrión V, Luna A, Aneiros-fernández J, Shen J. The future of computational pathology: expectations regarding the anticipated role of artificial intelligence in pathology by 2030.. [DOI: 10.1101/2022.09.02.22279476] [Reference Citation Analysis]
27 Yang W, Xu J, Xiang J, Yan Z, Zhou H, Wen B, Kong H, Zhu R, Li W. Diagnosis of cardiac abnormalities based on phonocardiogram using a novel fuzzy matching feature extraction method. BMC Med Inform Decis Mak 2022;22:230. [PMID: 36056352 DOI: 10.1186/s12911-022-01976-6] [Reference Citation Analysis]
28 Schwenck J, Kneilling M, Riksen NP, la Fougère C, Mulder DJ, Slart RJHA, Aarntzen EHJG. A role for artificial intelligence in molecular imaging of infection and inflammation. European J Hybrid Imaging 2022;6:17. [DOI: 10.1186/s41824-022-00138-1] [Reference Citation Analysis]
29 Xie H, Tsang YP. Digitized Visual Transformation of Grotto Art Using Deep Learning and Virtual Reality Technology. Scientific Programming 2022;2022:1-10. [DOI: 10.1155/2022/5106036] [Reference Citation Analysis]
30 Sandarenu P, Millar EKA, Song Y, Browne L, Beretov J, Lynch J, Graham PH, Jonnagaddala J, Hawkins N, Huang J, Meijering E. Survival prediction in triple negative breast cancer using multiple instance learning of histopathological images. Sci Rep 2022;12:14527. [PMID: 36008541 DOI: 10.1038/s41598-022-18647-1] [Reference Citation Analysis]
31 Zhang T, Chen J, Lu Y, Yang X, Ouyang Z. Identification of technology frontiers of artificial intelligence-assisted pathology based on patent citation network. PLoS ONE 2022;17:e0273355. [DOI: 10.1371/journal.pone.0273355] [Reference Citation Analysis]
32 Bridge CP, Gorman C, Pieper S, Doyle SW, Lennerz JK, Kalpathy-Cramer J, Clunie DA, Fedorov AY, Herrmann MD. Highdicom: a Python Library for Standardized Encoding of Image Annotations and Machine Learning Model Outputs in Pathology and Radiology. J Digit Imaging 2022. [PMID: 35995898 DOI: 10.1007/s10278-022-00683-y] [Reference Citation Analysis]
33 Li B, Nelson M, Savari O, Loeffler A, Eliceiri K. Differentiation of Pancreatic Ductal Adenocarcinoma and Chronic Pancreatitis using Graph Neural Networks on Histopathology and Collagen Fiber Features.. [DOI: 10.21203/rs.3.rs-1951132/v1] [Reference Citation Analysis]
34 Wang Y, Zhang W, Yip H, Qu C, Hu H, Chen X, Lee T, Yang X, Yang B, Kumar P, Lee SY, Casimiro JJ, Zhang J, Lam KS, Wang A. SIC50: Determination of IC50 by an optimized Sobel operator and a vision transformer.. [DOI: 10.1101/2022.08.12.503661] [Reference Citation Analysis]
35 Yin X, Liao H, Yun H, Lin N, Li S, Xiang Y, Ma X. Artificial intelligence-based prediction of clinical outcome in immunotherapy and targeted therapy of lung cancer. Semin Cancer Biol 2022:S1044-579X(22)00182-1. [PMID: 35963564 DOI: 10.1016/j.semcancer.2022.08.002] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
36 Wong ANN, He Z, Leung KL, To CCK, Wong CY, Wong SCC, Yoo JS, Chan CKR, Chan AZ, Lacambra MD, Yeung MHY. Current Developments of Artificial Intelligence in Digital Pathology and Its Future Clinical Applications in Gastrointestinal Cancers. Cancers 2022;14:3780. [DOI: 10.3390/cancers14153780] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
37 Munari E, Querzoli G, Brunelli M, Marconi M, Sommaggio M, Cocchi MA, Martignoni G, Netto GJ, Caliò A, Quatrini L, Mariotti FR, Luchini C, Girolami I, Eccher A, Segala D, Ciompi F, Zamboni G, Moretta L, Bogina G. Comparison of three validated PD-L1 immunohistochemical assays in urothelial carcinoma of the bladder: interchangeability and issues related to patient selection. Front Immunol 2022;13:954910. [DOI: 10.3389/fimmu.2022.954910] [Reference Citation Analysis]
38 Dawson H. Digital pathology – Rising to the challenge. Front Med 2022;9. [DOI: 10.3389/fmed.2022.888896] [Reference Citation Analysis]
39 Gutiérrez Pérez JC, Otero Baguer D, Maass P. StainCUT: Stain Normalization with Contrastive Learning. J Imaging 2022;8:202. [DOI: 10.3390/jimaging8070202] [Reference Citation Analysis]
40 Liu Z, Su W, Ao J, Wang M, Jiang Q, He J, Gao H, Lei S, Nie J, Yan X, Guo X, Zhou P, Hu H, Ji M. Instant diagnosis of gastroscopic biopsy via deep-learned single-shot femtosecond stimulated Raman histology. Nat Commun 2022;13:4050. [PMID: 35831299 DOI: 10.1038/s41467-022-31339-8] [Cited by in Crossref: 1] [Cited by in F6Publishing: 5] [Article Influence: 1.0] [Reference Citation Analysis]
41 Ogony J, de Bel T, Radisky DC, Kachergus J, Thompson EA, Degnim AC, Ruddy KJ, Hilton T, Stallings-Mann M, Vachon C, Hoskin TL, Heckman MG, Vierkant RA, White LJ, Moore RM, Carter J, Jensen M, Pacheco-Spann L, Henry JE, Storniolo AM, Winham SJ, van der Laak J, Sherman ME. Towards defining morphologic parameters of normal parous and nulliparous breast tissues by artificial intelligence. Breast Cancer Res 2022;24:45. [PMID: 35821041 DOI: 10.1186/s13058-022-01541-z] [Reference Citation Analysis]
42 Lou P, Wang C, Guo R, Yao L, Zhang G, Yang J, Yuan Y, Dong Y, Gao Z, Gong T, Li C. HistoML, a markup language for representation and exchange of histopathological features in pathology images. Sci Data 2022;9:387. [PMID: 35803960 DOI: 10.1038/s41597-022-01505-0] [Reference Citation Analysis]
43 Zhao PY, Han K, Yao RQ, Ren C, Du XH. Application Status and Prospects of Artificial Intelligence in Peptic Ulcers. Front Surg 2022;9:894775. [PMID: 35784921 DOI: 10.3389/fsurg.2022.894775] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
44 Du H, Wen S, Guo Y, Jin F, Gallas BD. Single reader between-cases AUC estimator with nested data. Stat Methods Med Res 2022;:9622802221111539. [PMID: 35790462 DOI: 10.1177/09622802221111539] [Reference Citation Analysis]
45 Seo H, Brand L, Barco LS, Wang H. Scaling multi-instance support vector machine to breast cancer detection on the BreaKHis dataset. Bioinformatics 2022;38:i92-i100. [PMID: 35758811 DOI: 10.1093/bioinformatics/btac267] [Reference Citation Analysis]
46 Yang Y. Security Evaluation of Financial and Insurance and Ruin Probability Analysis Integrating Deep Learning Models. Comput Intell Neurosci 2022;2022:1857100. [PMID: 35720881 DOI: 10.1155/2022/1857100] [Reference Citation Analysis]
47 Mund A, Brunner AD, Mann M. Unbiased spatial proteomics with single-cell resolution in tissues. Mol Cell 2022;82:2335-49. [PMID: 35714588 DOI: 10.1016/j.molcel.2022.05.022] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 3.0] [Reference Citation Analysis]
48 Litjens G, Ciompi F, van der Laak J. A Decade of GigaScience: The Challenges of Gigapixel Pathology Images. Gigascience 2022;11:giac056. [PMID: 35701372 DOI: 10.1093/gigascience/giac056] [Reference Citation Analysis]
49 Huang SC, Chen CC, Lan J, Hsieh TY, Chuang HC, Chien MY, Ou TS, Chen KH, Wu RC, Liu YJ, Cheng CT, Huang YJ, Tao LW, Hwu AF, Lin IC, Hung SH, Yeh CY, Chen TC. Deep neural network trained on gigapixel images improves lymph node metastasis detection in clinical settings. Nat Commun 2022;13:3347. [PMID: 35688834 DOI: 10.1038/s41467-022-30746-1] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
50 Esteva A, Feng J, van der Wal D, Huang S, Simko JP, Devries S, Chen E, Schaeffer EM, Morgan TM, Sun Y, Ghorbani A, Naik N, Nathawani D, Socher R, Michalski JM, Roach M, Pisansky TM, Monson JM, Naz F, Wallace J, Ferguson MJ, Bahary J, Zou J, Lungren M, Yeung S, Ross AE, Kucharczyk M, Souhami L, Ballas L, Peters CA, Liu S, Balogh AG, Randolph-jackson PD, Schwartz DL, Girvigian MR, Saito NG, Raben A, Rabinovitch RA, Katato K, Sandler HM, Tran PT, Spratt DE, Pugh S, Feng FY, Mohamad O; NRG Prostate Cancer AI Consortium. Prostate cancer therapy personalization via multi-modal deep learning on randomized phase III clinical trials. npj Digit Med 2022;5. [DOI: 10.1038/s41746-022-00613-w] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
51 Wang X, Barrera C, Bera K, Viswanathan VS, Azarianpour-Esfahani S, Koyuncu C, Velu P, Feldman MD, Yang M, Fu P, Schalper KA, Mahdi H, Lu C, Velcheti V, Madabhushi A. Spatial interplay patterns of cancer nuclei and tumor-infiltrating lymphocytes (TILs) predict clinical benefit for immune checkpoint inhibitors. Sci Adv 2022;8:eabn3966. [PMID: 35648850 DOI: 10.1126/sciadv.abn3966] [Cited by in Crossref: 2] [Cited by in F6Publishing: 3] [Article Influence: 2.0] [Reference Citation Analysis]
52 Lee C, Park S, Song H, Ryu J, Kim S, Kim H, Pereira S, Yoo D. Interactive Multi-Class Tiny-Object Detection. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2022. [DOI: 10.1109/cvpr52688.2022.01374] [Reference Citation Analysis]
53 Ricciuto A, Rauter I, McGovern DPB, Mader RM, Reinisch W. Precision Medicine in Inflammatory Bowel Diseases: Challenges and Considerations for the Path Forward. Gastroenterology 2022;162:1815-21. [PMID: 35278416 DOI: 10.1053/j.gastro.2022.02.049] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
54 Guan Y, Zhang J, Tian K, Yang S, Dong P, Xiang J, Yang W, Huang J, Zhang Y, Han X. Node-aligned Graph Convolutional Network for Whole-slide Image Representation and Classification. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2022. [DOI: 10.1109/cvpr52688.2022.01825] [Reference Citation Analysis]
55 Zhang S, Lakshmanna K. Feasibility of Music Composition Using Deep Learning-Based Quality Classification Models. Wireless Communications and Mobile Computing 2022;2022:1-9. [DOI: 10.1155/2022/8123671] [Reference Citation Analysis]
56 Zheng X, Wang R, Zhang X, Sun Y, Zhang H, Zhao Z, Zheng Y, Luo J, Zhang J, Wu H, Huang D, Zhu W, Chen J, Cao Q, Zeng H, Luo R, Li P, Lan L, Yun J, Xie D, Zheng WS, Luo J, Cai M. A deep learning model and human-machine fusion for prediction of EBV-associated gastric cancer from histopathology. Nat Commun 2022;13:2790. [PMID: 35589792 DOI: 10.1038/s41467-022-30459-5] [Reference Citation Analysis]
57 Wagner SJ, Matek C, Boushehri SS, Boxberg M, Lamm L, Sadafi A, Waibel DJE, Marr C, Peng T. Built to last? Reproducibility and Reusability of Deep Learning Algorithms in Computational Pathology.. [DOI: 10.1101/2022.05.15.22275108] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
58 Stadlbauer A, Marhold F, Oberndorfer S, Heinz G, Buchfelder M, Kinfe TM, Meyer-Bäse A. Radiophysiomics: Brain Tumors Classification by Machine Learning and Physiological MRI Data. Cancers (Basel) 2022;14:2363. [PMID: 35625967 DOI: 10.3390/cancers14102363] [Reference Citation Analysis]
59 Sherman ME, de Bel T, Heckman MG, White LJ, Ogony J, Stallings-Mann M, Hilton T, Degnim AC, Vierkant RA, Hoskin T, Jensen MR, Pacheco-Spann L, Henry JE, Storniolo AM, Carter JM, Winham SJ, Radisky DC, van der Laak J. Serum hormone levels and normal breast histology among premenopausal women. Breast Cancer Res Treat 2022. [PMID: 35503494 DOI: 10.1007/s10549-022-06600-9] [Reference Citation Analysis]
60 Hassan T, Javed S, Mahmood A, Qaiser T, Werghi N, Rajpoot N. Nucleus Classification in Histology Images Using Message Passing Network. Medical Image Analysis 2022. [DOI: 10.1016/j.media.2022.102480] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
61 Konstantinov A, Utkin L. Multiple Instance Learning through Explanation by Using a Histopathology Example. 2022 31st Conference of Open Innovations Association (FRUCT) 2022. [DOI: 10.23919/fruct54823.2022.9770901] [Reference Citation Analysis]
62 de Almeida JG, Gudgin E, Besser M, Dunn WG, Cooper J, Haferlach T, Vassiliou GS, Gerstung M. Computational analysis of peripheral blood smears detects disease-associated cytomorphologies.. [DOI: 10.1101/2022.04.19.22273757] [Reference Citation Analysis]
63 Flach RN, Fransen NL, Sonnen AFP, Nguyen TQ, Breimer GE, Veta M, Stathonikos N, van Dooijeweert C, van Diest PJ. Implementation of Artificial Intelligence in Diagnostic Practice as a Next Step after Going Digital: The UMC Utrecht Perspective. Diagnostics 2022;12:1042. [DOI: 10.3390/diagnostics12051042] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
64 Sandeman K, Blom S, Koponen V, Manninen A, Juhila J, Rannikko A, Ropponen T, Mirtti T. AI Model for Prostate Biopsies Predicts Cancer Survival. Diagnostics 2022;12:1031. [DOI: 10.3390/diagnostics12051031] [Reference Citation Analysis]
65 Konstantinov AV, Utkin LV. Multi-attention multiple instance learning. Neural Comput & Applic. [DOI: 10.1007/s00521-022-07259-5] [Reference Citation Analysis]
66 Li R, Mei G. MCU Simulation Software Algorithm based on Deep Learning from Single Network Model to Multiple Layer Scenarios. 2022 International Conference on Sustainable Computing and Data Communication Systems (ICSCDS) 2022. [DOI: 10.1109/icscds53736.2022.9760923] [Reference Citation Analysis]
67 Mirjahanmardi S, Dawe M, Fyles A, Shi W, Liu F, Done S, Khademi A. Preserving dense features for Ki67 nuclei detection. Medical Imaging 2022: Digital and Computational Pathology 2022. [DOI: 10.1117/12.2611212] [Reference Citation Analysis]
68 Bouaoud J, Bossi P, Elkabets M, Schmitz S, van Kempen LC, Martinez P, Jagadeeshan S, Breuskin I, Puppels GJ, Hoffmann C, Hunter KD, Simon C, Machiels J, Grégoire V, Bertolus C, Brakenhoff RH, Koljenović S, Saintigny P. Unmet Needs and Perspectives in Oral Cancer Prevention. Cancers 2022;14:1815. [DOI: 10.3390/cancers14071815] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 4.0] [Reference Citation Analysis]
69 Krajňanský V, Gallo M, Nenutil R, Němeček M, Holub P, Brázdil T. Shedding Light on the Black Box of a Neural Network Used to Detect Prostate Cancer in Whole Slide Images by Occlusion-Based Explainability.. [DOI: 10.1101/2022.03.31.486599] [Reference Citation Analysis]
70 Javed S, Mahmood A, Dias J, Werghi N. Multi-level feature fusion for nucleus detection in histology images using correlation filters. Computers in Biology and Medicine 2022;143:105281. [DOI: 10.1016/j.compbiomed.2022.105281] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 3.0] [Reference Citation Analysis]
71 Davri A, Birbas E, Kanavos T, Ntritsos G, Giannakeas N, Tzallas AT, Batistatou A. Deep Learning on Histopathological Images for Colorectal Cancer Diagnosis: A Systematic Review. Diagnostics (Basel) 2022;12:837. [PMID: 35453885 DOI: 10.3390/diagnostics12040837] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 4.0] [Reference Citation Analysis]
72 Ilié M, Benzaquen J, Tourniaire P, Heeke S, Ayache N, Delingette H, Long-Mira E, Lassalle S, Hamila M, Fayada J, Otto J, Cohen C, Gomez-Caro A, Berthet JP, Marquette CH, Hofman V, Bontoux C, Hofman P. Deep Learning Facilitates Distinguishing Histologic Subtypes of Pulmonary Neuroendocrine Tumors on Digital Whole-Slide Images. Cancers (Basel) 2022;14:1740. [PMID: 35406511 DOI: 10.3390/cancers14071740] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
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