[HTML][HTML] Small patient datasets reveal genetic drivers of non-small cell lung cancer subtypes using machine learning for hypothesis generation
M Cook, B Qorri, A Baskar, J Ziauddin… - Exploration of …, 2023 - explorationpub.com
Aim: Many small datasets of significant value exist in the medical space that are being
underutilized. Due to the heterogeneity of complex disorders found in oncology, systems …
underutilized. Due to the heterogeneity of complex disorders found in oncology, systems …
Small patient datasets reveal genetic drivers of non-small cell lung cancer subtypes using a novel machine learning approach
C Moses, Q Bessi, B Amruth, Z Jalal, P Luca… - medRxiv, 2021 - medrxiv.org
Background There are many small datasets of significant value in the medical space that are
being underutilized. Due to the heterogeneity of complex disorders found in oncology …
being underutilized. Due to the heterogeneity of complex disorders found in oncology …
Identification of Gene Biomarkers for Distinguishing Small‐Cell Lung Cancer from Non‐Small‐Cell Lung Cancer Using a Network‐Based Approach
F Long, JH Su, B Liang, LL Su… - BioMed research …, 2015 - Wiley Online Library
Lung cancer consists of two main subtypes: small‐cell lung cancer (SCLC) and non‐small‐
cell lung cancer (NSCLC) that are classified according to their physiological phenotypes. In …
cell lung cancer (NSCLC) that are classified according to their physiological phenotypes. In …
Prediction uncertainty estimates elucidate the limitation of current NSCLC subtype classification in representing mutational heterogeneity
The heterogeneous pathogenesis and treatment response of non-small cell lung cancer
(NSCLC) has led clinical treatment decisions to be guided by NSCLC subtypes, with lung …
(NSCLC) has led clinical treatment decisions to be guided by NSCLC subtypes, with lung …
An interpretable approach for lung cancer prediction and subtype classification using gene expression
B Ramos, T Pereira, J Moranguinho… - 2021 43rd Annual …, 2021 - ieeexplore.ieee.org
Lung cancer is the deadliest form of cancer, accounting for 20% of total cancer deaths. It
represents a group of histologically and molecularly heterogeneous diseases even within …
represents a group of histologically and molecularly heterogeneous diseases even within …
[HTML][HTML] Gene expression signature differentiates histology but not progression status of early-stage NSCLC
R Charkiewicz, J Niklinski, J Claesen, A Sulewska… - Translational …, 2017 - Elsevier
Advances in molecular analyses based on high-throughput technologies can contribute to a
more accurate classification of non–small cell lung cancer (NSCLC), as well as a better …
more accurate classification of non–small cell lung cancer (NSCLC), as well as a better …
Pipeline design to identify key features and classify the chemotherapy response on lung cancer patients using large-scale genetic data
Background During the last decade, the interest to apply machine learning algorithms to
genomic data has increased in many bioinformatics applications. Analyzing this type of data …
genomic data has increased in many bioinformatics applications. Analyzing this type of data …
An explainable AI-driven biomarker discovery framework for Non-Small Cell Lung Cancer classification
Abstract Non-Small Cell Lung Cancer (NSCLC) exhibits intrinsic heterogeneity at the
molecular level that aids in distinguishing between its two prominent subtypes—Lung …
molecular level that aids in distinguishing between its two prominent subtypes—Lung …
Six-Gene Signature for Differential Diagnosis and Therapeutic Decisions in Non-Small-Cell Lung Cancer—A Validation Study
R Charkiewicz, A Sulewska, P Karabowicz… - International Journal of …, 2024 - mdpi.com
Non-small-cell lung cancer (NSCLC) poses a challenge due to its heterogeneity,
necessitating precise histopathological subtyping and prognostication for optimal treatment …
necessitating precise histopathological subtyping and prognostication for optimal treatment …
Functional effects of four or fewer critical genes linked to lung cancers and new subtypes detected by a new machine learning classifier
Z Zhang - bioRxiv, 2021 - biorxiv.org
Finding genes biologically directly or indirectly related to lung cancer has been drawing
much attention, and many genes directly related to lung cancer have been reported …
much attention, and many genes directly related to lung cancer have been reported …
相关搜索
- patient datasets genetic drivers
- patient datasets machine learning
- machine learning genetic drivers
- patient datasets hypothesis generation
- hypothesis generation genetic drivers
- machine learning hypothesis generation
- lung cancer gene biomarkers
- functional effects lung cancers
- lung cancer therapeutic decisions
- subtype classification gene expression
- machine learning subgroup identification
- machine learning risk stratification
- lung cancer differential diagnosis
- critical genes lung cancers