Results 81 to 90 of about 1,120,836 (288)
CURE: Flexible Categorical Data Representation by Hierarchical Coupling Learning [PDF]
, 2019 © 1989-2012 IEEE. The representation of categorical data with hierarchical value coupling relationships (i.e., various value-to-value cluster interactions) is very critical yet challenging for capturing complex data characteristics in learning tasks ...
Jian, S +9 more
core +1 more source
Optimal coding of high-cardinality categorical data in machine learning
, 2023 Analyzing categorical data in machine learning generally requires a coding strategy. This problem is common to multivariate statistical techniques, and several approaches have been suggested in the literature.
Agostino Di Ciaccio
core +1 more source
Interrogating the immune landscape of microsatellite stable RAS‐mutated colon cancer
Molecular Oncology, EarlyView.COLOSSUS project RAS‐mutated MSS colon cancer study explored transcriptomics and immune cell density by immunohistochemistry (IHC), Immunoscore (IS), ISIC/TuLIS scores, mutation counts, and detected different prevalences but similar microenvironment composition across immune markers with clinical relevance for future immunotherapy combination ...
Rodrigo Dienstmann +61 more
wiley +1 more source
An Overview of Methods in the Analysis of Dependent ordered catagorical Data: Assumptions and Implications [PDF]
Subjective assessments of pain, quality of life, ability etc. measured by rating scales and questionnaires are common in clinical research. The resulting responses are categorical with an ordered structure and the statistical methods must take account of
Högberg, Hans, Svensson, Elisabeth
core
Somatic mutational landscape in von Hippel–Lindau familial hemangioblastoma
Molecular Oncology, EarlyView.The causes of central nervous system (CNS) hemangioblastoma in Von Hippel–Lindau (vHL) disease are unclear. We used Whole Exome Sequencing (WES) on familial hemangioblastoma to investigate events that underlie tumor development. Our findings suggest that VHL loss creates a permissive environment for tumor formation, while additional alterations ...
Maja Dembic +5 more
wiley +1 more source
Understanding and Enhancement of Internal Clustering Validation Indexes for Categorical Data
Algorithms, 2018 Clustering is one of the main tasks of machine learning. Internal clustering validation indexes (CVIs) are used to measure the quality of several clustered partitions to determine the local optimal clustering results in an unsupervised manner, and can ...
Xuedong Gao, Minghan Yang
doaj +1 more source
Molecular Oncology, EarlyView.We have established a humanized orthotopic patient‐derived xenograft (Hu‐oPDX) mouse model of high‐grade serous ovarian cancer (HGSOC) that recapitulates human tumor–immune interactions. Using combined anti‐PD‐L1/anti‐CD73 immunotherapy, we demonstrate the model's improved biological relevance and enhanced translational value for preclinical ...
Luka Tandaric +10 more
wiley +1 more source
Comparison of methods in the analysis of dependent ordered catagorical data [PDF]
Rating scales for outcome variables produce categorical data which are often ordered and measurements from rating scales are not standardized. The purpose of this study is to apply commonly used and novel methods for paired ordered categorical data to ...
Högberg, Hans, Svensson, Elisabeth
core
Molecular Oncology, EarlyView.Pancreatic sensory neurons innervating healthy and PDAC tissue were retrogradely labeled and profiled by single‐cell RNA sequencing. Tumor‐associated innervation showed a dominant neurofilament‐positive subtype, altered mitochondrial gene signatures, and reduced non‐peptidergic neurons.
Elena Genova +14 more
wiley +1 more source
Optimal Coding of Categorical Data in Machine Learning
, 2023 Analyzing categorical data in machine learning generally requires a coding strategy. This problem is common to multivariate statistical techniques and several approaches have been suggested in the literature. This article proposes a method for analyzing
Agostino Di Ciaccio
core