Comparison of classifiers on the scale of sensitivity. by Shamik Tiwari (4490185)

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Comparison of classifiers on the scale of F-score. by Shamik Tiwari (4490185)

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Sample images from Kylberg texture image dataset. by Shamik Tiwari (4490185)

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Performance comparison of the proposed method with prominent work for classification on Kylberg Texture Dataset [26]. by Shamik Tiwari (4490185)

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A texture classification framework. by Shamik Tiwari (4490185)

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Comparison of classifiers on the scale of precision. by Shamik Tiwari (4490185)

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Image 4_Significant adverse prognostic events in patients with urosepsis: a machine learning based model development and validation study.tif by Yiqu Wei (22011386)

Image 1_A prognostic model of lung adenocarcinoma constructed based on circadian rhythm genes and its potential clinical significance.tif by Cong Fu (23214)

Image 1_Significant adverse prognostic events in patients with urosepsis: a machine learning based model development and validation study.tif by Yiqu Wei (22011386)

Image_1_Significance of monocyte infiltration in patients with gastric cancer: A combined study based on single cell sequencing and TCGA.jpeg by Wei Xu (28953)

Image 3_A prognostic model of lung adenocarcinoma constructed based on circadian rhythm genes and its potential clinical significance.tif by Cong Fu (23214)

Image 3_Significant adverse prognostic events in patients with urosepsis: a machine learning based model development and validation study.tif by Yiqu Wei (22011386)

Image1_Screening of pathologically significant diagnostic biomarkers in tears of thyroid eye disease based on bioinformatic analysis and machine learning.TIFF by Xingyi Shu (19966254)

Image 1_Integrative morpho-molecular delineation of five medically significant tick species: facilitating precision-based vector surveillance.pdf by Guangxin Shi (20299578)

Image 2_A prognostic model of lung adenocarcinoma constructed based on circadian rhythm genes and its potential clinical significance.tif by Cong Fu (23214)

Image 2_Significant adverse prognostic events in patients with urosepsis: a machine learning based model development and validation study.tif by Yiqu Wei (22011386)

Accuracy of large language models for text-based, image-based questions and the total sample. by Huy Cong Nguyen (20636383)

Data for subjects with significant slopes (regional progression or recovery colour coded, non-significant regions white) for the 4 data types over the study period. by Faran Sabeti (6166766)

“…<p>The only diabetic (non-DMO) person with significant thickness changes was mf87171 (row I). …”

Validation of genetic markers for risk of OA or knee OA for decrease in minJSW. by Mieke L. M. Bentvelzen (21594442)

Anthropometric characteristics of smokers and non-smokers. by Prasanna Herath (20714794)