Dataset Information

Deep Semi-Supervised Learning Improves Universal Peptide Identification of Shotgun Proteomics Data

ABSTRACT: Data and results for paper, "Deep Semi-Supervised Learning Improves Universal Peptide Identification of Shotgun Proteomics Data," found at: https://doi.org/10.1101/2020.11.12.380881 Deep learning software for PSM recalibration, called ProteoTorch-DNN, available at: https://github.com/proteoTorch/proteoTorch with documentation: https://proteotorch.readthedocs.io/en/latest/

INSTRUMENT(S): Orbitrap Fusion ETD, LTQ Orbitrap Velos, Orbitrap Fusion, LTQ Orbitrap Elite

ORGANISM(S): Sars Coronavirus (ncbitaxon:227859) Homo Sapiens (ncbitaxon:9606) Plasmodium (ncbitaxon:5820)

SUBMITTER: John Timothy Halloran

PROVIDER: MSV000087402 | MassIVE | Tue May 11 09:39:00 BST 2021

SECONDARY ACCESSION(S): PXD025941

REPOSITORIES: MassIVE

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Project description:International guidelines recommend deciding the treatment of colorectal lesions based on the estimated histology by endoscopic optical diagnosis. However, the theoretical and practical knowledge on optical diagnosis is not widely expanded The mail goal of this randomised controlled trial is to compare the pooled sensitivity of optical diagnosis for predicting deep submucosal invasion in large non-pedunculated polyps > 20 mm assessed in routine colonoscopies of gastroenterologists attending a e-learning module (intervention group) vs gastroenterologists who do not (control group) The main questions the study aims to answer are: * Is the pooled sensitivity of optical diagnosis for predicting deep submucosal invasion in large non-pedunculated polyps assessed in routine colonoscopies increased in those gastroenterologists participating in the e-learning module? * Is the pooled diagnostic accuracy of optical diagnosis for predicting deep sm invasion in large non-pedunculated polyps ≥ 20 mm assessed in routine colonoscopies increased in those gastroenterologists participating in the e-learning module? * In lesions with submucosal invasion, is the en bloc and complete resection rate (R0) increased in those gastroenterologists participating in the e-learning module? * In lesions referred to surgery, is the pooled benign polyps rate decreased in those gastroenterologists participating in the e-learning module? * In lesions treated with advanced en bloc procedures (ESD, TAMIS, fullthickness resection), is the pooled rate of histology with high-grade dysplasia, intramucosal cancer or submucosal invasion increased in those gastroenterologists participating in the e-learning module? * In lesions treated with piecemeal endoscopic resection, is the pooled rate of histology with high-grade dysplasia, intramucosal cancer or submucosal invasion decreased in those gastroenterologists participating in the e-learning module? * Is the diagnostic accuracy for predicting deep submucosal invasion in a test with pictures increased after participating in the e-learning module? The participants (or subjects of study) are gastroenterologists. They will be randomised to do the e-learning course (intervention group) or not (control group). Researchers will compare clinical outcomes of gastroenterologists participating in the e-learning module vs gastroenterologists not participating in the e-learning module to see if: * the pooled sensitivity of optical diagnosis for predicting deep submucosal invasion in large non-pedunculated polyps > 20 mm assessed in routine colonoscopies is increased. * the pooled diagnostic accuracy of optical diagnosis for predicting deep sm invasion in large non-pedunculated polyps > 20 mm is increased. * the en bloc and complete resection rate (R0) is increased in lesions with submucosal invasion. * the pooled benign polyps rate decreased in lesions referred to surgery. * the pooled rate of histology with high-grade dysplasia, intramucosal cancer or submucosal invasion increased in lesions treated with advanced en bloc procedures (ESD, TAMIS, fullthickness resection). * the pooled rate of histology with high-grade dysplasia, intramucosal cancer or submucosal invasion decreased in lesions treated with piecemeal endoscopic resection. * the diagnostic accuracy for predicting deep submucosal invasion in a test with pictures after participating is increased.

Dataset Information

Deep Semi-Supervised Learning Improves Universal Peptide Identification of Shotgun Proteomics Data

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