Mining electronic health records (EHRs) A survey
The continuously increasing cost of the US healthcare system has received significant
attention. Central to the ideas aimed at curbing this trend is the use of technology in the form …
attention. Central to the ideas aimed at curbing this trend is the use of technology in the form …
Introduction to survival analysis in practice
F Emmert-Streib, M Dehmer - Machine Learning and Knowledge …, 2019 - mdpi.com
The modeling of time to event data is an important topic with many applications in diverse
areas. The collective of methods to analyze such data are called survival analysis, event …
areas. The collective of methods to analyze such data are called survival analysis, event …
Similarity network fusion for aggregating data types on a genomic scale
Recent technologies have made it cost-effective to collect diverse types of genome-wide
data. Computational methods are needed to combine these data to create a comprehensive …
data. Computational methods are needed to combine these data to create a comprehensive …
The Fibrillin‐1/VEGFR2/STAT2 signaling axis promotes chemoresistance via modulating glycolysis and angiogenesis in ovarian cancer organoids and cells
Z Wang, W Chen, L Zuo, M Xu, Y Wu… - Cancer …, 2022 - Wiley Online Library
Background Chemotherapy resistance is a primary reason of ovarian cancer therapy failure;
hence it is important to investigate the underlying mechanisms of chemotherapy resistance …
hence it is important to investigate the underlying mechanisms of chemotherapy resistance …
A survey on sparse learning models for feature selection
X Li, Y Wang, R Ruiz - IEEE transactions on cybernetics, 2020 - ieeexplore.ieee.org
Feature selection is important in both machine learning and pattern recognition.
Successfully selecting informative features can significantly increase learning accuracy and …
Successfully selecting informative features can significantly increase learning accuracy and …
[HTML][HTML] Prognostic gene expression signature for high-grade serous ovarian cancer
J Millstein, T Budden, EL Goode, MS Anglesio… - Annals of …, 2020 - Elsevier
Background Median overall survival (OS) for women with high-grade serous ovarian cancer
(HGSOC) is∼ 4 years, yet survival varies widely between patients. There are no well …
(HGSOC) is∼ 4 years, yet survival varies widely between patients. There are no well …
[HTML][HTML] Machine learning and bioinformatics models to identify gene expression patterns of ovarian cancer associated with disease progression and mortality
Ovarian cancer (OC) is a common cause of cancer death among women worldwide, so there
is a pressing need to identify factors influencing OC mortality. Much OC patient clinical data …
is a pressing need to identify factors influencing OC mortality. Much OC patient clinical data …
Network-based machine learning and graph theory algorithms for precision oncology
Network-based analytics plays an increasingly important role in precision oncology.
Growing evidence in recent studies suggests that cancer can be better understood through …
Growing evidence in recent studies suggests that cancer can be better understood through …
compound. Cox: univariate feature selection and compound covariate for predicting survival
T Emura, S Matsui, HY Chen - Computer methods and programs in …, 2019 - Elsevier
Background and objective Univariate feature selection is one of the simplest and most
commonly used techniques to develop a multigene predictor for survival. Presently, there is …
commonly used techniques to develop a multigene predictor for survival. Presently, there is …
Structured sparsity regularization for analyzing high-dimensional omics data
S Vinga - Briefings in Bioinformatics, 2021 - academic.oup.com
The development of new molecular and cell technologies is having a significant impact on
the quantity of data generated nowadays. The growth of omics databases is creating a …
the quantity of data generated nowadays. The growth of omics databases is creating a …