A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
Filters
Unsupervised Extraction of Phenotypes from Cancer Clinical Notes for Association Studies
[article]
2019
arXiv
pre-print
Preserved Fulltext
Other Versions
To demonstrate the utility of our approach, we perform an association study of clinical features with somatic mutation profiles from 4,007 cancer patients and their tumors. ...
In this work, we develop the methodology to automatically extract clinical features from clinical narratives from large EHR corpora without the need for prior knowledge. ...
Acknowledgements: This study was supported by the MSK Cancer Center Support Grant (P30 CA008748). ...
arXiv:1904.12973v2
fatcat:t4v6liyfyzbodg7bba4lc6tqmi
Natural Language Processing for EHR-Based Computational Phenotyping
2018
IEEE/ACM Transactions on Computational Biology & Bioinformatics
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
adverse drug event (ADE) detection, as well as genome-wide and phenome-wide association studies. ...
Recently, deep learning and unsupervised learning have received growing attention, with the former favored for its performance and the latter for its ability to find novel phenotypes. ...
Acknowledgment This work was supported in part by NIH Grant 1R21LM012618-01, NLM Biomedical Informatics Training Grant 2T15 LM007092-22, and the Intel Science and Technology Center for Big Data. ...
doi:10.1109/tcbb.2018.2849968
pmid:29994486
pmcid:PMC6388621
fatcat:wsksxvr7lfbgjowrsymghld64u
Natural Language Processing for EHR-Based Computational Phenotyping
[article]
2018
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Other Versions
adverse drug event (ADE) detection, as well as genome-wide and phenome-wide association studies. ...
Recently, deep learning and unsupervised learning have received growing attention, with the former favored for its performance and the latter for its ability to find novel phenotypes. ...
[187] proposed using unsupervised methods for both entity and relation extraction from clinical notes. Clustering was applied to all the entity pairs for possible relations discovery. ...
arXiv:1806.04820v2
fatcat:fo5ck7rpgzhb7dgmqfjc3bdw7y
Imaging phenotypes of breast cancer heterogeneity in pre-operative breast Dynamic Contrast Enhanced Magnetic Resonance Imaging (DCE-MRI) scans predict 10-year recurrence
2019
Clinical Cancer Research
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Intrinsic phenotypes of tumor heterogeneity were identified via unsupervised hierarchical clustering of the extracted features. ...
For each woman, a signal enhancement ratio (SER) map was generated for the entire segmented primary lesion volume from which 60 radiomic features of texture and morphology were extracted. ...
Acknowledgments This study was supported by the NCI at the NIH: 5R01CA197000-03 (to R.D. ...
doi:10.1158/1078-0432.ccr-18-4067
pmid:31732521
pmcid:PMC7024654
fatcat:uwjv4b3zmjbrlnf2uxnpyclmgy
DNA Methylation Status of Epithelial-Mesenchymal Transition (EMT) - Related Genes Is Associated with Severe Clinical Phenotypes in Ulcerative Colitis (UC)
2014
PLoS ONE
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
Conclusions: Our data suggest that variability in the methylation status of EMT-related genes is associated with more severe clinical phenotypes in UC. ...
Results: Using an unsupervised hierarchical clustering analysis, inflamed rectal mucosa was well separated from mucosa that appeared normal. ...
same specimens used for DNA extraction. ...
doi:10.1371/journal.pone.0107947
pmid:25303049
pmcid:PMC4193736
fatcat:rk2x3fzajnb35a7vu2clttncpm
Artificial Intelligence toward Personalized Medicine
2021
Pharmaceutical Sciences and Research
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
of multi-modalities data, (3) disease specialist to guide the development of AI model, (4) investigation of AI-finding by clinical community, and (5) follow-up of AI-finding by the large clinical trial ...
From the analysis, we concluded that AI for personalized medicine could benefit by five factors: (1) standardization and pooling of genetics and health data, nationally and internationally, (2) the use ...
Both human and ML model can "learn" from each other. As last note, we saw that most AI finding are retrospective, meaning the data was extracted from previous clinical trials in other studies. ...
doi:10.7454/psr.v8i2.1199
fatcat:gt33f5iucrdltppu5wxawmhg4e
Chronic Lymphocytic Leukemia Progression Diagnosis with Intrinsic Cellular Patterns via Unsupervised Clustering
2022
Cancers
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
The outcome of this study serves as proof of principle using an unsupervised machine learning scheme to enhance the diagnostic accuracy of the heterogeneous histology patterns that pathologists might not ...
We further validate the reproducibility and robustness of unsupervised feature extraction via stability and repeated splitting analysis, supporting its utility as a diagnostic aid in identifying CLL patients ...
Conflicts of Interest: The authors declare no conflict of interest. Cancers 2022, 14, 2398 ...
doi:10.3390/cancers14102398
fatcat:hiwc4ltnsrafvativi5h6ap2ge
A Novel Prostate Cell Type-Specific Gene Signature to Interrogate Prostate Tumor Differentiation Status and Monitor Therapeutic Response (Running Title: Phenotypic Classification of Prostate Tumors)
2020
Cancers
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
We found also an association of LumE score with tumor phenotype in genetically engineered mouse models (GEMMs) of prostate cancer. ...
Immunohistochemistry for COL4A1, a low-luminal marker, sustained the association of attenuated luminal phenotype with metastatic disease. ...
Clinical evolution of prostate cancer is highly heterogeneous ranging from indolent phenotype might predispose to castration resistance. ...
doi:10.3390/cancers12010176
pmid:31936761
fatcat:tjx6nzmcwjhqbbpojaeaf7qnfq
An Unsupervised Approach to Identify Molecular Phenotypic Components Influencing Breast Cancer Features
2004
Cancer Research
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
These results provide a molecular phenotypic basis for the existence of a biologically unique subgroup comprising ER (؉) breast cancers from African-American patients. ...
To discover a biological basis for clinical subgroupings within breast cancers, we applied principal components (PCs) analysis to cDNA microarray data from 36 breast cancers. ...
Therefore, in the current study, we analyzed global gene expression data from breast cancers using an unsupervised bioinformatics approach, principal components analysis (PCA). ...
doi:10.1158/0008-5472.can-03-3208
pmid:14996713
fatcat:lstyfrawefeljaoquk4fvfrn2a
Deep Phenotyping: Embracing Complexity and Temporality—Towards Scalability, Portability, and Interoperability
2020
Journal of Biomedical Informatics
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. ...
These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. ...
Acknowledgments The editors acknowledge funding support from the United States National Institutes of Health grants R01LM009886-10, R01LM006910-19, U01HG008680-05 and R01LM011369-07. ...
doi:10.1016/j.jbi.2020.103433
pmid:32335224
pmcid:PMC7179504
fatcat:53xsdcycxvgq5h6wkfivz4azei
Combining radiomic phenotypes of non-small cell lung cancer with liquid biopsy data may improve prediction of response to EGFR inhibitors
2021
Scientific Reports
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Clinical data included age, smoking status, and ECOG performance status. Baseline chest CT scans were analyzed to extract 429 radiomic features from each primary tumor. ...
For OS, adding radiomic phenotypes resulted in c-statistic of 0.83 versus 0.80 when using clinical and ctDNA variables (LRT p = 0.08). ...
of care, and radiomic features extracted from clinically acquired chest CT scans. ...
doi:10.1038/s41598-021-88239-y
pmid:33976268
pmcid:PMC8113313
fatcat:nq4q7wbcxnhsxpzsn24ch7mway
A Review of Automatic Phenotyping Approaches using Electronic Health Records
2019
Electronics
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
This review summarizes and offers a critical evaluation of the literature relating to studies conducted into the development of EHR phenotyping systems. ...
In order to utilize EHRs for medical observational research a range of algorithms for automatically identifying individuals with a specific phenotype have been developed. ...
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/electronics8111235
fatcat:6wygemixhvgoxkhjqrmmjs3ynq
Radiomic Phenotypes of Mammographic Parenchymal Complexity: Toward Augmenting Breast Density in Breast Cancer Risk Assessment
2019
Radiology
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
(from 140 of 291 [48.1%] in the high-complexity phenotype to 275 of 511 [53.8%] in the low-complexity phenotype). ...
Purpose To identify phenotypes of mammographic parenchymal complexity by using radiomic features and to evaluate their associations with breast density and other breast cancer risk factors. ...
Activities not related to the present article: is inventor of patents licensed to Gamma Medica (acquired by CMR Naviscan); received royalties for technologies licensed to Gamma Medica. ...
doi:10.1148/radiol.2018180179
pmid:30375931
pmcid:PMC6314515
fatcat:uu7oh7tf6reldhhlvjb7eoeype
Radiomic Phenotypes for Improving Early Prediction of Survival in Stage III Non-Small Cell Lung Cancer Adenocarcinoma after Chemoradiation
2022
Cancers
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
A binary radiomic phenotype to predict OS was derived through the unsupervised hierarchical clustering of the first principal components explaining 85% of the variance of the radiomic features. ...
We evaluate radiomic phenotypes derived from CT scans as early predictors of overall survival (OS) after chemoradiation in stage III primary lung adenocarcinoma. ...
In this study, we investigate the association between OS and radiomic features extracted from chest CT scans of a relatively homogeneous cohort of stage III NSCLC adenocarcinoma patients at our institution ...
doi:10.3390/cancers14030700
pmid:35158971
pmcid:PMC8833400
fatcat:rvngwzsvibfhnflodw7wcok7hm
Graph-based signal integration for high-throughput phenotyping
2012
BMC Bioinformatics
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
Conclusions: We conclude that our approach is a promising alternative for unsupervised high-throughput phenotyping. ...
Our unsupervised graph-based high-throughput phenotyping had accuracy of 84.1%; recall=46.3%, precision=61.2%, and F 1 =52.8%. ...
This article has been published as part of BMC Bioinformatics Volume 13 Supplement 13, 2012: Selected articles from The 8th Annual Biotechnology and Bioinformatics Symposium (BIOT-2011). ...
doi:10.1186/1471-2105-13-s13-s2
pmid:23320851
pmcid:PMC3426800
fatcat:sbh2odhx2vaqnn3s4oscyoobha
« Previous
Showing results 1 — 15 out of 7,726 results