Optimize Neural Fuzzy Systems for High‐Dimensional Breast Cancer Data Analysis: A Deep Learning Approach
Sign Up to like & getrecommendations! Published in 2025 at "International Journal of Imaging Systems and Technology"
DOI: 10.1002/ima.70117
Abstract: Accurate and timely analysis of breast cancer data is crucial for the successful deployment and advancement of intelligent healthcare systems. Traditional health status prediction methods, which often rely on shallow models, fall short in complex… read more here.
Keywords: deep learning; breast cancer; cancer data; analysis ... See more keywords
Domain expertise-agnostic feature selection for the analysis of breast cancer data*
Sign Up to like & getrecommendations! Published in 2020 at "Artificial intelligence in medicine"
DOI: 10.1016/j.artmed.2020.101928
Abstract: Progress in proteomics has enabled biologists to accurately measure the amount of protein in a tumor. This work is based on a breast cancer data set, result of the proteomics analysis of a cohort of… read more here.
Keywords: domain expertise; feature selection; cancer data; cancer ... See more keywords
Reparametrized generalized gamma partially linear regression with application to breast cancer data
Sign Up to like & getrecommendations! Published in 2024 at "Journal of Applied Statistics"
DOI: 10.1080/02664763.2024.2337086
Abstract: We construct a new partially linear regression based on a reparametrized generalized gamma distribution with two systematic components that can be easily interpreted. Its parameters are estimated by penalized maximum likelihood. For different parameter settings,… read more here.
Keywords: breast cancer; cancer data; generalized gamma; linear regression ... See more keywords
Tightly integrated multiomics-based deep tensor survival model for time-to-event prediction
Sign Up to like & getrecommendations! Published in 2022 at "Bioinformatics"
DOI: 10.1093/bioinformatics/btac286
Abstract: MOTIVATION Multiomics cancer profiles provide essential signals for predicting cancer survival. It is challenging to reveal the complex patterns from multiple types of data and link them to survival outcomes. We aim to develop a… read more here.
Keywords: integrated multiomics; tensor; prediction; tightly integrated ... See more keywords
Synggen: fast and data-driven generation of synthetic heterogeneous NGS cancer data
Sign Up to like & getrecommendations! Published in 2022 at "Bioinformatics"
DOI: 10.1093/bioinformatics/btac792
Abstract: Abstract Summary Whole-exome and targeted sequencing are widely utilized both in translational cancer genomics and in the setting of precision medicine. The benchmarking of computational methods and tools that are in continuous development is fundamental… read more here.
Keywords: synggen; generation; synggen fast; fast data ... See more keywords
The childhood cancer data initiative: enabling data sharing to drive research advances and transform pediatric cancer diagnosis and treatment
Sign Up to like & getrecommendations! Published in 2024 at "Current Opinion in Pediatrics"
DOI: 10.1097/mop.0000000000001422
Abstract: Purpose of review With growing emphasis on data-driven research in pediatric oncology, particularly in the context of advances in molecular characterization and precision medicine, there is an urgent need for comprehensive data-sharing initiatives. This review… read more here.
Keywords: oncology; cancer; cancer data; data sharing ... See more keywords
A Robust Enhanced Ensemble Learning Method for Breast Cancer Data Diagnosis on Imbalanced Data
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Access"
DOI: 10.1109/access.2024.3516376
Abstract: Early breast cancer diagnosis is crucial for improving treatment outcomes for women. Addressing class imbalance in breast cancer data is essential for enhancing detection accuracy, yet traditional machine learning methods often overlook this imbalance, limiting… read more here.
Keywords: diagnosis; breast cancer; method; cancer ... See more keywords
Cohort profile: Bladder Cancer Data Base Sweden (BladderBaSe) 2.0
Sign Up to like & getrecommendations! Published in 2022 at "BMJ Open"
DOI: 10.1136/bmjopen-2022-064898
Abstract: Purpose We constructed Bladder Cancer Data Base Sweden (BladderBaSe) 2.0 to expand studies in BladderBaSe on incidence, treatment outcomes, side effects, survival and health economic aspects of men and women with cancer in the urinary… read more here.
Keywords: bladder; data base; bladderbase; bladder cancer ... See more keywords
Abstract 1170: Socioeconomic disparities in patients with esophageal cancer at time of diagnosis: A national cancer data base analysis
Sign Up to like & getrecommendations! Published in 2020 at "Epidemiology"
DOI: 10.1158/1538-7445.am2020-1170
Abstract: Introduction: There have been noted to be significant gender and socioeconomic disparities in the incidence, prognosis, and clinical outcomes of patients with esophageal cancer. The purpose of this study was to characterize disparities amongst patients… read more here.
Keywords: cancer data; esophageal cancer; patients esophageal; cancer ... See more keywords
Cancer in Saudi Arabia (CSA): Web-Based Application to Study Cancer Data Among Saudis Using Waterfall Model
Sign Up to like & getrecommendations! Published in 2021 at "Journal of Multidisciplinary Healthcare"
DOI: 10.2147/jmdh.s326168
Abstract: Background Information technology (IT) has emerged as a promising enabler to address the issue of big data in health care. Despite the urgent need for an IT-based tool to tackle this issue, one is not… read more here.
Keywords: saudi; application; csa; cancer data ... See more keywords
Variational Autoencoders for Cancer Data Integration: Design Principles and Computational Practice
Sign Up to like & getrecommendations! Published in 2019 at "Frontiers in Genetics"
DOI: 10.3389/fgene.2019.01205
Abstract: International initiatives such as the Molecular Taxonomy of Breast Cancer International Consortium are collecting multiple data sets at different genome-scales with the aim to identify novel cancer bio-markers and predict patient survival. To analyze such… read more here.
Keywords: cancer data; autoencoders cancer; variational autoencoders; data integration ... See more keywords