FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2893683567> ?p ?o ?g. }

• W2893683567 endingPage "2456" @default.
• W2893683567 startingPage "2447" @default.
• W2893683567 abstract "Objective: Ultrahigh-resolution optical coherence microscopy (OCM) has recently demonstrated its potential for accurate diagnosis of human cervical diseases. One major challenge for clinical adoption, however, is the steep learning curve clinicians need to overcome to interpret OCM images. Developing an intelligent technique for computer-aided diagnosis (CADx) to accurately interpret OCM images will facilitate clinical adoption of the technology and improve patient care. Methods: 497 high-resolution three-dimensional (3-D) OCM volumes (600 cross-sectional images each) were collected from 159 ex vivo specimens of 92 female patients. OCM image features were extracted using a convolutional neural network (CNN) model, concatenated with patient information [e.g., age and human papillomavirus (HPV) results], and classified using a support vector machine classifier. Ten-fold cross-validations were utilized to test the performance of the CADx method in a five-class classification task and a binary classification task. Results: An 88.3 ± 4.9% classification accuracy was achieved for five fine-grained classes of cervical tissue, namely normal, ectropion, low-grade and high-grade squamous intraepithelial lesions (LSIL and HSIL), and cancer. In the binary classification task [low-risk (normal, ectropion, and LSIL) versus high-risk (HSIL and cancer)], the CADx method achieved an area-under-the-curve value of 0.959 with an 86.7 ± 11.4% sensitivity and 93.5 ± 3.8% specificity. Conclusion: The proposed deep-learning-based CADx method outperformed four human experts. It was also able to identify morphological characteristics in OCM images that were consistent with histopathological interpretations. Significance: Label-free OCM imaging, combined with deep-learning-based CADx methods, holds a great promise to be used in clinical settings for the effective screening and diagnosis of cervical diseases." @default.
• W2893683567 created "2018-10-05" @default.
• W2893683567 creator A5000467703 @default.
• W2893683567 creator A5002843429 @default.
• W2893683567 creator A5009122132 @default.
• W2893683567 creator A5011131284 @default.
• W2893683567 creator A5015623750 @default.
• W2893683567 creator A5032125778 @default.
• W2893683567 creator A5047305591 @default.
• W2893683567 creator A5054720229 @default.
• W2893683567 creator A5061727903 @default.
• W2893683567 creator A5063116224 @default.
• W2893683567 creator A5063245694 @default.
• W2893683567 creator A5071030446 @default.
• W2893683567 creator A5089839414 @default.
• W2893683567 date "2019-09-01" @default.
• W2893683567 modified "2023-10-15" @default.
• W2893683567 title "Computer-Aided Diagnosis of Label-Free 3-D Optical Coherence Microscopy Images of Human Cervical Tissue" @default.
• W2893683567 cites W1884191083 @default.
• W2893683567 cites W1965301399 @default.
• W2893683567 cites W1974601308 @default.
• W2893683567 cites W1975879668 @default.
• W2893683567 cites W1976193075 @default.
• W2893683567 cites W2012193454 @default.
• W2893683567 cites W2018958726 @default.
• W2893683567 cites W2032403778 @default.
• W2893683567 cites W2036163000 @default.
• W2893683567 cites W2067322808 @default.
• W2893683567 cites W2071957599 @default.
• W2893683567 cites W2076063813 @default.
• W2893683567 cites W2078600175 @default.
• W2893683567 cites W2085528444 @default.
• W2893683567 cites W2094006622 @default.
• W2893683567 cites W2102605133 @default.
• W2893683567 cites W2116584074 @default.
• W2893683567 cites W2117539524 @default.
• W2893683567 cites W2121732950 @default.
• W2893683567 cites W2132853584 @default.
• W2893683567 cites W2145339207 @default.
• W2893683567 cites W2145751021 @default.
• W2893683567 cites W2162445884 @default.
• W2893683567 cites W2174023915 @default.
• W2893683567 cites W2294798173 @default.
• W2893683567 cites W2346062110 @default.
• W2893683567 cites W2418802570 @default.
• W2893683567 cites W2557738935 @default.
• W2893683567 cites W2560322684 @default.
• W2893683567 cites W2570618306 @default.
• W2893683567 cites W2580421856 @default.
• W2893683567 cites W2581082771 @default.
• W2893683567 cites W2582821003 @default.
• W2893683567 cites W2592929672 @default.
• W2893683567 cites W2618530766 @default.
• W2893683567 cites W2732547613 @default.
• W2893683567 cites W2788633781 @default.
• W2893683567 cites W2803991685 @default.
• W2893683567 cites W2919115771 @default.
• W2893683567 cites W4239510810 @default.
• W2893683567 cites W4361868505 @default.
• W2893683567 doi "https://doi.org/10.1109/tbme.2018.2890167" @default.
• W2893683567 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/6724217" @default.
• W2893683567 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/30605087" @default.
• W2893683567 hasPublicationYear "2019" @default.
• W2893683567 type Work @default.
• W2893683567 sameAs 2893683567 @default.
• W2893683567 citedByCount "23" @default.
• W2893683567 countsByYear W28936835672019 @default.
• W2893683567 countsByYear W28936835672020 @default.
• W2893683567 countsByYear W28936835672021 @default.
• W2893683567 countsByYear W28936835672022 @default.
• W2893683567 countsByYear W28936835672023 @default.
• W2893683567 crossrefType "journal-article" @default.
• W2893683567 hasAuthorship W2893683567A5000467703 @default.
• W2893683567 hasAuthorship W2893683567A5002843429 @default.
• W2893683567 hasAuthorship W2893683567A5009122132 @default.
• W2893683567 hasAuthorship W2893683567A5011131284 @default.
• W2893683567 hasAuthorship W2893683567A5015623750 @default.
• W2893683567 hasAuthorship W2893683567A5032125778 @default.
• W2893683567 hasAuthorship W2893683567A5047305591 @default.
• W2893683567 hasAuthorship W2893683567A5054720229 @default.
• W2893683567 hasAuthorship W2893683567A5061727903 @default.
• W2893683567 hasAuthorship W2893683567A5063116224 @default.
• W2893683567 hasAuthorship W2893683567A5063245694 @default.
• W2893683567 hasAuthorship W2893683567A5071030446 @default.
• W2893683567 hasAuthorship W2893683567A5089839414 @default.
• W2893683567 hasBestOaLocation W28936835671 @default.
• W2893683567 hasConcept C108583219 @default.
• W2893683567 hasConcept C121608353 @default.
• W2893683567 hasConcept C12267149 @default.
• W2893683567 hasConcept C123860398 @default.
• W2893683567 hasConcept C126322002 @default.
• W2893683567 hasConcept C126838900 @default.
• W2893683567 hasConcept C153180895 @default.
• W2893683567 hasConcept C154945302 @default.
• W2893683567 hasConcept C2778220009 @default.
• W2893683567 hasConcept C2778818243 @default.
• W2893683567 hasConcept C2779549770 @default.
• W2893683567 hasConcept C41008148 @default.

• next