Matches in SemOpenAlex for { <https://semopenalex.org/work/W2891484462> ?p ?o ?g. }
- W2891484462 abstract "Identification of nodal metastasis and tumor extranodal extension (ENE) is crucial for head and neck cancer management, but currently only can be diagnosed via postoperative pathology. Pretreatment, radiographic identification of ENE, in particular, has proven extremely difficult for clinicians, but would be greatly influential in guiding patient management. Here, we show that a deep learning convolutional neural network can be trained to identify nodal metastasis and ENE with excellent performance that surpasses what human clinicians have historically achieved. We trained a 3-dimensional convolutional neural network using a dataset of 2,875 CT-segmented lymph node samples with correlating pathology labels, cross-validated and fine-tuned on 124 samples, and conducted testing on a blinded test set of 131 samples. On the blinded test set, the model predicted ENE and nodal metastasis each with area under the receiver operating characteristic curve (AUC) of 0.91 (95%CI: 0.85-0.97). The model has the potential for use as a clinical decision-making tool to help guide head and neck cancer patient management." @default.
- W2891484462 created "2018-09-27" @default.
- W2891484462 creator A5001470616 @default.
- W2891484462 creator A5001660012 @default.
- W2891484462 creator A5006355506 @default.
- W2891484462 creator A5018154366 @default.
- W2891484462 creator A5023000705 @default.
- W2891484462 creator A5025519576 @default.
- W2891484462 creator A5027831083 @default.
- W2891484462 creator A5039233998 @default.
- W2891484462 creator A5041938643 @default.
- W2891484462 creator A5042314992 @default.
- W2891484462 creator A5061395570 @default.
- W2891484462 creator A5072379548 @default.
- W2891484462 date "2018-09-19" @default.
- W2891484462 modified "2023-10-17" @default.
- W2891484462 title "Pretreatment Identification of Head and Neck Cancer Nodal Metastasis and Extranodal Extension Using Deep Learning Neural Networks" @default.
- W2891484462 cites W1522734439 @default.
- W2891484462 cites W1576642972 @default.
- W2891484462 cites W1677182931 @default.
- W2891484462 cites W1821700304 @default.
- W2891484462 cites W1917623384 @default.
- W2891484462 cites W1964786618 @default.
- W2891484462 cites W1968328487 @default.
- W2891484462 cites W1985651817 @default.
- W2891484462 cites W1985862224 @default.
- W2891484462 cites W1991396678 @default.
- W2891484462 cites W1993295404 @default.
- W2891484462 cites W2019607817 @default.
- W2891484462 cites W2048427607 @default.
- W2891484462 cites W2048787136 @default.
- W2891484462 cites W2069224380 @default.
- W2891484462 cites W2090990325 @default.
- W2891484462 cites W2093474403 @default.
- W2891484462 cites W2103004421 @default.
- W2891484462 cites W2128646736 @default.
- W2891484462 cites W2141125852 @default.
- W2891484462 cites W2142213598 @default.
- W2891484462 cites W2142222095 @default.
- W2891484462 cites W2147300476 @default.
- W2891484462 cites W2148250174 @default.
- W2891484462 cites W2158728032 @default.
- W2891484462 cites W2167331143 @default.
- W2891484462 cites W2168011129 @default.
- W2891484462 cites W2235523093 @default.
- W2891484462 cites W2328176404 @default.
- W2891484462 cites W2426463718 @default.
- W2891484462 cites W2469257540 @default.
- W2891484462 cites W2512096955 @default.
- W2891484462 cites W2513587258 @default.
- W2891484462 cites W2592355735 @default.
- W2891484462 cites W2599693381 @default.
- W2891484462 cites W2600642189 @default.
- W2891484462 cites W2608353599 @default.
- W2891484462 cites W2618230854 @default.
- W2891484462 cites W2742279182 @default.
- W2891484462 cites W2767128594 @default.
- W2891484462 cites W2770261599 @default.
- W2891484462 cites W2919115771 @default.
- W2891484462 cites W49700977 @default.
- W2891484462 doi "https://doi.org/10.1038/s41598-018-32441-y" @default.
- W2891484462 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/6145900" @default.
- W2891484462 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/30232350" @default.
- W2891484462 hasPublicationYear "2018" @default.
- W2891484462 type Work @default.
- W2891484462 sameAs 2891484462 @default.
- W2891484462 citedByCount "127" @default.
- W2891484462 countsByYear W28914844622019 @default.
- W2891484462 countsByYear W28914844622020 @default.
- W2891484462 countsByYear W28914844622021 @default.
- W2891484462 countsByYear W28914844622022 @default.
- W2891484462 countsByYear W28914844622023 @default.
- W2891484462 crossrefType "journal-article" @default.
- W2891484462 hasAuthorship W2891484462A5001470616 @default.
- W2891484462 hasAuthorship W2891484462A5001660012 @default.
- W2891484462 hasAuthorship W2891484462A5006355506 @default.
- W2891484462 hasAuthorship W2891484462A5018154366 @default.
- W2891484462 hasAuthorship W2891484462A5023000705 @default.
- W2891484462 hasAuthorship W2891484462A5025519576 @default.
- W2891484462 hasAuthorship W2891484462A5027831083 @default.
- W2891484462 hasAuthorship W2891484462A5039233998 @default.
- W2891484462 hasAuthorship W2891484462A5041938643 @default.
- W2891484462 hasAuthorship W2891484462A5042314992 @default.
- W2891484462 hasAuthorship W2891484462A5061395570 @default.
- W2891484462 hasAuthorship W2891484462A5072379548 @default.
- W2891484462 hasBestOaLocation W28914844621 @default.
- W2891484462 hasConcept C108583219 @default.
- W2891484462 hasConcept C116834253 @default.
- W2891484462 hasConcept C119857082 @default.
- W2891484462 hasConcept C121608353 @default.
- W2891484462 hasConcept C126322002 @default.
- W2891484462 hasConcept C126838900 @default.
- W2891484462 hasConcept C141071460 @default.
- W2891484462 hasConcept C142724271 @default.
- W2891484462 hasConcept C154945302 @default.
- W2891484462 hasConcept C169903167 @default.
- W2891484462 hasConcept C2776530083 @default.
- W2891484462 hasConcept C2779013556 @default.
- W2891484462 hasConcept C2780849966 @default.
- W2891484462 hasConcept C3018411727 @default.