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Cited by in F6Publishing
For: Zhang Y, Weng Y, Lund J. Applications of Explainable Artificial Intelligence in Diagnosis and Surgery. Diagnostics 2022;12:237. [DOI: 10.3390/diagnostics12020237] [Cited by in Crossref: 17] [Cited by in F6Publishing: 17] [Article Influence: 17.0] [Reference Citation Analysis]
Number Citing Articles
1 Guindo ML, Kabir MH, Chen R, Huang J, Liu F, Li X, Fang H. Chemometric Approach Based on Explainable AI for Rapid Assessment of Macronutrients in Different Organic Fertilizers Using Fusion Spectra. Molecules 2023;28:799. [PMID: 36677857 DOI: 10.3390/molecules28020799] [Reference Citation Analysis]
2 Goeckenjan M, Festag A, Kather JN. Entscheidungsfindungen in der Reproduktionsmedizin. Gynäkologische Endokrinologie 2023. [DOI: 10.1007/s10304-022-00489-9] [Reference Citation Analysis]
3 Li C, Zhang Y, Weng Y, Wang B, Li Z. Natural Language Processing Applications for Computer-Aided Diagnosis in Oncology. Diagnostics (Basel) 2023;13. [PMID: 36673096 DOI: 10.3390/diagnostics13020286] [Reference Citation Analysis]
4 Said M, Omar Y, Safwat S, Salem A. Explainable Artificial Intelligence Powered Model for Explainable Detection of Stroke Disease. Proceedings of the 8th International Conference on Advanced Intelligent Systems and Informatics 2022 2023. [DOI: 10.1007/978-3-031-20601-6_20] [Reference Citation Analysis]
5 Praveen S, Joshi K. Explainable Artificial Intelligence in Health Care: How XAI Improves User Trust in High-Risk Decisions. Explainable Edge AI: A Futuristic Computing Perspective 2023. [DOI: 10.1007/978-3-031-18292-1_6] [Reference Citation Analysis]
6 Sayed GI, Hassanien AE. Explainable AI and Slime Mould Algorithm for Classification of Pistachio Species. Artificial Intelligence: A Real Opportunity in the Food Industry 2023. [DOI: 10.1007/978-3-031-13702-0_3] [Reference Citation Analysis]
7 Chen Z, Xiao F, Guo F, Yan J. Interpretable machine learning for building energy management: A state-of-the-art review. Advances in Applied Energy 2023. [DOI: 10.1016/j.adapen.2023.100123] [Reference Citation Analysis]
8 Uzun Ozsahin D, Ikechukwu Emegano D, Uzun B, Ozsahin I. The Systematic Review of Artificial Intelligence Applications in Breast Cancer Diagnosis. Diagnostics (Basel) 2022;13. [PMID: 36611337 DOI: 10.3390/diagnostics13010045] [Reference Citation Analysis]
9 Procter R, Tolmie P, Rouncefield M. Holding AI to Account: Challenges for the Delivery of Trustworthy AI in Healthcare. ACM Trans Comput -Hum Interact 2022. [DOI: 10.1145/3577009] [Reference Citation Analysis]
10 Socia D, Brady CJ, West SK, Cockrell RC. Detection of trachoma using machine learning approaches. PLoS Negl Trop Dis 2022;16:e0010943. [DOI: 10.1371/journal.pntd.0010943] [Reference Citation Analysis]
11 Askr H, Elgeldawi E, Aboul Ella H, Elshaier YAMM, Gomaa MM, Hassanien AE. Deep learning in drug discovery: an integrative review and future challenges. Artif Intell Rev 2022. [DOI: 10.1007/s10462-022-10306-1] [Reference Citation Analysis]
12 Tsolakis IA, Kolokitha OE, Papadopoulou E, Tsolakis AI, Kilipiris EG, Palomo JM. Artificial Intelligence as an Aid in CBCT Airway Analysis: A Systematic Review. Life (Basel) 2022;12. [PMID: 36431029 DOI: 10.3390/life12111894] [Reference Citation Analysis]
13 Xu H, Gong T, Liu F, Chen H, Xiao Q, Hou Y, Huang Y, Sun H, Shi Y, Gao S, Lou Y, Chang Q, Zhao Y, Gao Q, Wu Q. Artificial intelligence performance in image-based ovarian cancer identification: A systematic review and meta-analysis. eClinicalMedicine 2022;53:101662. [DOI: 10.1016/j.eclinm.2022.101662] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
14 Utama C, Karg B, Meske C, Lucia S. Explainable artificial intelligence for deep learning-based model predictive controllers. 2022 26th International Conference on System Theory, Control and Computing (ICSTCC) 2022. [DOI: 10.1109/icstcc55426.2022.9931794] [Reference Citation Analysis]
15 Aljameel SS. A Proactive Explainable Artificial Neural Network Model for the Early Diagnosis of Thyroid Cancer. Computation 2022;10:183. [DOI: 10.3390/computation10100183] [Reference Citation Analysis]
16 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]
17 Khan MS, Nayebpour M, Li MH, El-Amine H, Koizumi N, Olds JL. Explainable AI: A Neurally-Inspired Decision Stack Framework. Biomimetics (Basel) 2022;7:127. [PMID: 36134931 DOI: 10.3390/biomimetics7030127] [Reference Citation Analysis]
18 Iliadou E, Su Q, Kikidis D, Bibas T, Kloukinas C. Profiling hearing aid users through big data explainable artificial intelligence techniques. Front Neurol 2022;13:933940. [DOI: 10.3389/fneur.2022.933940] [Reference Citation Analysis]
19 Park JY, Seo EH, Yoon H, Won S, Lee KH. Automating Rey Complex Figure Test scoring using a deep learning-based approach: A potential large-scale screening tool for congnitive decline.. [DOI: 10.21203/rs.3.rs-1973305/v1] [Reference Citation Analysis]
20 Gevaert CM. Explainable AI for earth observation: A review including societal and regulatory perspectives. International Journal of Applied Earth Observation and Geoinformation 2022;112:102869. [DOI: 10.1016/j.jag.2022.102869] [Reference Citation Analysis]
21 Adak A, Pradhan B, Shukla N, Alamri A. Unboxing Deep Learning Model of Food Delivery Service Reviews Using Explainable Artificial Intelligence (XAI) Technique. Foods 2022;11:2019. [DOI: 10.3390/foods11142019] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
22 Thurzo A, Urbanová W, Novák B, Czako L, Siebert T, Stano P, Mareková S, Fountoulaki G, Kosnáčová H, Varga I. Where Is the Artificial Intelligence Applied in Dentistry? Systematic Review and Literature Analysis. Healthcare (Basel) 2022;10:1269. [PMID: 35885796 DOI: 10.3390/healthcare10071269] [Cited by in Crossref: 5] [Cited by in F6Publishing: 5] [Article Influence: 5.0] [Reference Citation Analysis]
23 Suri JS, Agarwal S, Chabert GL, Carriero A, Paschè A, Danna PSC, Saba L, Mehmedović A, Faa G, Singh IM, Turk M, Chadha PS, Johri AM, Khanna NN, Mavrogeni S, Laird JR, Pareek G, Miner M, Sobel DW, Balestrieri A, Sfikakis PP, Tsoulfas G, Protogerou AD, Misra DP, Agarwal V, Kitas GD, Teji JS, Al-Maini M, Dhanjil SK, Nicolaides A, Sharma A, Rathore V, Fatemi M, Alizad A, Krishnan PR, Nagy F, Ruzsa Z, Fouda MM, Naidu S, Viskovic K, Kalra MK. COVLIAS 2.0-cXAI: Cloud-Based Explainable Deep Learning System for COVID-19 Lesion Localization in Computed Tomography Scans. Diagnostics (Basel) 2022;12:1482. [PMID: 35741292 DOI: 10.3390/diagnostics12061482] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 3.0] [Reference Citation Analysis]
24 Painuli D, Bhardwaj S, Köse U. Recent advancement in cancer diagnosis using machine learning and deep learning techniques: A comprehensive review. Comput Biol Med 2022;146:105580. [PMID: 35551012 DOI: 10.1016/j.compbiomed.2022.105580] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 3.0] [Reference Citation Analysis]
25 Mohamed E, Sirlantzis K, Howells G. A review of visualisation-as-explanation techniques for convolutional neural networks and their evaluation. Displays 2022. [DOI: 10.1016/j.displa.2022.102239] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
26 Saraswat D, Bhattacharya P, Verma A, Prasad VK, Tanwar S, Sharma G, Bokoro PN, Sharma R. Explainable AI for Healthcare 5.0: Opportunities and Challenges. IEEE Access 2022;10:84486-517. [DOI: 10.1109/access.2022.3197671] [Reference Citation Analysis]