AIMC Topic: Pathology, Molecular

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DeePathology: Deep Multi-Task Learning for Inferring Molecular Pathology from Cancer Transcriptome.

Scientific reports Nov 11, 2019
Despite great advances, molecular cancer pathology is often limited to the use of a small number of biomarkers rather than the whole transcriptome, partly due to computational challenges. Here, we introduce a novel architecture of Deep Neural Network...
Humans Neural Networks, Computer Gene Expression Profiling Transcriptome Deep Learning Algorithms Reproducibility of Results Neoplasms Pathology, Molecular Data Mining Computational Biology Disease Susceptibility Gene Expression Regulation, Neoplastic Organ Specificity
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An integrated molecular diagnostic report for heart transplant biopsies using an ensemble of diagnostic algorithms.

The Journal of heart and lung transplantation : the official publication of the International Society for Heart Transplantation Feb 6, 2019
BACKGROUND: We previously reported a microarray-based diagnostic system for heart transplant endomyocardial biopsies (EMBs), using either 3-archetype (3AA) or 4-archetype (4AA) unsupervised algorithms to estimate rejection. In the present study we ex...
ROC Curve Predictive Value of Tests Graft Rejection Myocardium Humans Machine Learning Heart Failure Algorithms Cohort Studies Child, Preschool Adult Child Male Risk Assessment Middle Aged Adolescent Female Aged Young Adult Heart Transplantation Pathology, Molecular
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Deep transfer learning-based hologram classification for molecular diagnostics.

Scientific reports Nov 19, 2018
Lens-free digital in-line holography (LDIH) is a promising microscopic tool that overcomes several drawbacks (e.g., limited field of view) of traditional lens-based microcopy. However, extensive computation is required to reconstruct object images fr...
Holography Neoplasms Machine Learning Humans Algorithms Pathology, Molecular Deep Learning Neural Networks, Computer Biomarkers, Tumor Image Processing, Computer-Assisted Image Enhancement Tumor Cells, Cultured
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General Applicability of Existing College of American Pathologists Accreditation Requirements to Clinical Implementation of Machine Learning-Based Methods in Molecular Oncology Testing.

Archives of pathology & laboratory medicine Apr 1, 2025
CONTEXT.—: The College of American Pathologists (CAP) accreditation requirements for clinical laboratory testing help ensure laboratories implement and maintain systems and processes that are associated with quality. Machine learning (ML)-based model...
Machine Learning Neoplasms United States Humans Pathology, Molecular Accreditation Laboratories, Clinical Pathologists Medical Oncology Societies, Medical
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[Next-generation diagnostic pathology].

Zhonghua bing li xue za zhi = Chinese journal of pathology Jan 8, 2022
With the technological progresses and applications of human genome sequencing, bioinformatics analysis and data mining, and molecular pathology and artificial intelligence-assisted pathological diagnosis, the development of clinical medicine is movin...
Pathology, Molecular Humans Artificial Intelligence China Computational Biology
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Obtaining Knowledge in Pathology Reports Through a Natural Language Processing Approach With Classification, Named-Entity Recognition, and Relation-Extraction Heuristics.

JCO clinical cancer informatics Aug 1, 2019
PURPOSE: Robust institutional tumor banks depend on continuous sample curation or else subsequent biopsy or resection specimens are overlooked after initial enrollment. Curation automation is hindered by semistructured free-text clinical pathology no...
Pathology, Molecular Research Report Medical Informatics User-Computer Interface Natural Language Processing Neoplasm Staging Workflow Heuristics Middle Aged Neoplasms Adolescent Adult Algorithms Male Electronic Health Records Female Aged Aged, 80 and over Young Adult Humans Machine Learning Software
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