Cargando…

Identification of mortality-risk-related missense variant for renal clear cell carcinoma using deep learning

INTRODUCTION: Kidney renal clear cell carcinoma (KIRCC) is a highly heterogeneous and lethal cancer that can arise in patients with renal disease. DeepSurv combines a deep feed-forward neural network with a Cox proportional hazards function and could provide optimized survival results compared with...

Descripción completa

Detalles Bibliográficos
Autores principales:	Chen, Jin-Bor, Yang, Huai-Shuo, Moi, Sin-Hua, Chuang, Li-Yeh, Yang, Cheng-Hong
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	SAGE Publications 2021
Materias:	Original Research
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7890720/ https://www.ncbi.nlm.nih.gov/pubmed/33643601 http://dx.doi.org/10.1177/2040622321992624

Ejemplares similares

Machine learning approaches for the mortality risk assessment of patients undergoing hemodialysis
por: Yang, Cheng-Hong, et al.
Publicado: (2022)

Higher-order clinical risk factor interaction analysis for overall mortality in maintenance hemodialysis patients
por: Yang, Cheng-Hong, et al.
Publicado: (2020)

MVP predicts the pathogenicity of missense variants by deep learning
por: Qi, Hongjian, et al.
Publicado: (2021)

An association between time-varying serum albumin level and the mortality rate in maintenance haemodialysis patients: a five-year clinical cohort study
por: Chen, Jin-Bor, et al.
Publicado: (2016)

Accurate Prediction of Transcriptional Activity of Single Missense Variants in HIV Tat with Deep Learning
por: Derbel, Houssemeddine, et al.
Publicado: (2023)

Biofilm Formation in Acinetobacter Baumannii: Genotype-Phenotype Correlation
por: Yang, Cheng-Hong, et al.
Publicado: (2019)

LYRUS: a machine learning model for predicting the pathogenicity of missense variants
por: Lai, Jiaying, et al.
Publicado: (2021)

Application of deep learning to predict the low serum albumin in new hemodialysis patients
por: Yang, Cheng-Hong, et al.
Publicado: (2023)

Prevalence of Carbapenem Resistance Genes among Acinetobacter baumannii Isolated from a Teaching Hospital in Taiwan
por: Su, Pai-Wei, et al.
Publicado: (2023)

Identification of High-Order Single-Nucleotide Polymorphism Barcodes in Breast Cancer Using a Hybrid Taguchi-Genetic Algorithm: Case-Control Study
por: Chuang, Li-Yeh, et al.
Publicado: (2020)

MBOAT1 homozygous missense variant causes nonobstructive azoospermia
por: Wan, Yang-Yang, et al.
Publicado: (2021)

An integrated computational approach can classify VHL missense mutations according to risk of clear cell renal carcinoma
por: Gossage, Lucy, et al.
Publicado: (2014)

Association of proportion of the HDL-cholesterol subclasses HDL-2b and HDL-3 and macrovascular events among patients undergoing hemodialysis
por: Lee, Wen-Chin, et al.
Publicado: (2021)

Deep learning based prediction of prognosis in nonmetastatic clear cell renal cell carcinoma
por: Byun, Seok-Soo, et al.
Publicado: (2021)

Identification of missense MAB21L1 variants in microphthalmia and aniridia
por: Seese, Sarah E., et al.
Publicado: (2021)

Identification of Missense Variants Affecting Carcass Traits for Hanwoo Precision Breeding
por: Lee, Dong Jae, et al.
Publicado: (2023)

YARS2 Missense Variant in Belgian Shepherd Dogs with Cardiomyopathy and Juvenile Mortality
por: Gurtner, Corinne, et al.
Publicado: (2020)

Functional Impact of Missense Variants in BRCA1 Predicted by Supervised Learning
por: Karchin, Rachel, et al.
Publicado: (2007)

Successful Identification of Nasopharyngeal Carcinoma in Nasopharyngeal Biopsies Using Deep Learning
por: Chuang, Wen-Yu, et al.
Publicado: (2020)

Prediction of pathological staging and grading of renal clear cell carcinoma based on deep learning algorithms
por: Wen-zhi, Gao, et al.
Publicado: (2022)

Identification of a missense variant in SPDL1 associated with idiopathic pulmonary fibrosis
por: Dhindsa, Ryan S., et al.
Publicado: (2021)

Relationship between Clinicopathologic Variables in Breast Cancer Overall Survival Using Biogeography-Based Optimization Algorithm
por: Chuang, Li-Yeh, et al.
Publicado: (2019)

Identification of an immune-related risk signature for predicting prognosis in clear cell renal cell carcinoma
por: Hua, Xiaoliang, et al.
Publicado: (2020)

Deep Learning–Based Classification of Epithelial–Mesenchymal Transition for Predicting Response to Therapy in Clear Cell Renal Cell Carcinoma
por: Chen, Qiwei, et al.
Publicado: (2022)

Identification of genes and pathways involved in kidney renal clear cell carcinoma
por: Yang, William, et al.
Publicado: (2014)

Integrative Analysis of Germline Rare Variants in Clear and Non-Clear Cell Renal Cell Carcinoma
por: Han, Seunghun, et al.
Publicado: (2023)

A framework for exhaustively mapping functional missense variants
por: Weile, Jochen, et al.
Publicado: (2017)

Expanding the genetic spectrum of the pyruvate carboxylase deficiency with novel missense, deep intronic and structural variants
por: Tsygankova, Polina, et al.
Publicado: (2022)

The schizophrenia-associated missense variant rs13107325 regulates dendritic spine density
por: Li, Shiwu, et al.
Publicado: (2022)

Deep learning can predict survival directly from histology in clear cell renal cell carcinoma
por: Wessels, Frederik, et al.
Publicado: (2022)

Changes in Serum Concentrations of Fibroblast Growth Factor 23 and Soluble Klotho in Hemodialysis Patients after Total Parathyroidectomy
por: Liao, Shang-Chih, et al.
Publicado: (2016)

Effect of clinical factors on trajectory of functional performance in patients undergoing hemodialysis
por: Chen, Jin-Bor, et al.
Publicado: (2020)

A Profile of Nanoparticle-Based Plasma Neurodegenerative Biomarkers for Cognitive Function Among Patients Undergoing Hemodialysis
por: Chen, Jin-Bor, et al.
Publicado: (2022)

Identification of Potential Serum Proteomic Biomarkers for Clear Cell Renal Cell Carcinoma
por: Yang, Juan, et al.
Publicado: (2014)

Shifting landscapes of human MTHFR missense-variant effects
por: Weile, Jochen, et al.
Publicado: (2021)

Identification of microRNA editing sites in clear cell renal cell carcinoma
por: Liu, Yulong, et al.
Publicado: (2023)

MLb-LDLr: A Machine Learning Model for Predicting the Pathogenicity of LDLr Missense Variants
por: Larrea-Sebal, Asier, et al.
Publicado: (2021)

CHD7 missense variants and clinical characteristics of Chinese males with infertility
por: Li, Leilei, et al.
Publicado: (2020)

Deep Learning Using CT Images to Grade Clear Cell Renal Cell Carcinoma: Development and Validation of a Prediction Model
por: Xu, Lifeng, et al.
Publicado: (2022)

In silico comparative characterization of pharmacogenomic missense variants
por: Li, Biao, et al.
Publicado: (2014)

Cannot write session to /tmp/vufind_sessions/sess_n8sfvspm8h6mfu049g0p1q4um0