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TIBCO
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Image Search Results
Journal: Multimedia Tools and Applications
Article Title: A critical review on diagnosis of diabetic retinopathy using machine learning and deep learning
doi: 10.1007/s11042-022-12642-4
Figure Lengend Snippet: Literature Review on ML and DL models for early detection of DR
Article Snippet: Gardner et al. [ ] , EyePACS-1 MESSIDOR-2 , HE and MA ,
Techniques: Biomarker Discovery
Journal: Journal of Clinical Medicine
Article Title: Evaluation of the Progression of Periodontitis with the Use of Neural Networks
doi: 10.3390/jcm11164667
Figure Lengend Snippet: ANN construction. Source: https://www.periodontalchart-online.com/uk/ (accessed on 1 May 2020). Periodontal chart with input layer (n = 543), hidden layer (n = 19) and output layer (n = 4) which refers to periodontitis grading. Sex, age, smoking, approximal plaque index, bleeding on probing, periodontal pocket depth, and maximal interproximal loss of connective tissue attachment were all taken into account by the artificial neural network. For each patient, a set of 543 inputs was produced. By the use of the Statistica Automated Neural Networks, TIBCO Software Inc. (2017). Statistica (data analysis software system), version 13. http://statistica.io (accessed on 1 September 2021) the output layer has been received. The output layer consists of three grades (A,B,C) and a group of healthy patients.
Article Snippet: All calculations were performed in the
Techniques: Produced, Software
Journal: Computational and Structural Biotechnology Journal
Article Title: Emerging artificial intelligence applications in Spatial Transcriptomics analysis
doi: 10.1016/j.csbj.2022.05.056
Figure Lengend Snippet: Summary of AI methods in Spatial Transcriptomics Analysis.
Article Snippet:
Techniques: Software, Gene Expression, Comparison, Expressing, Generated, Introduce
Journal: Computational and Structural Biotechnology Journal
Article Title: Emerging artificial intelligence applications in Spatial Transcriptomics analysis
doi: 10.1016/j.csbj.2022.05.056
Figure Lengend Snippet: General schematic of (a) the fully connected neural network, (b) the convolutional neural network, (c) the graph convolutional neural network, and (d) the autoencoder.
Article Snippet:
Techniques: