Results 21 to 30 of about 1,212,418 (284)

Predicting the Future Burden of Renal Replacement Therapy in Türkiye Using National Registry Data and Comparative Modeling Approaches

open access: yesTherapeutic Apheresis and Dialysis, EarlyView.
ABSTRACT Background Chronic kidney disease is a growing public health problem worldwide, and the number of patients requiring renal replacement therapy is steadily increasing. Türkiye has experienced a similar rise in both the incidence and prevalence of renal replacement therapy over the past decades; however, national‐level projections of future ...
Arzu Akgül   +2 more
wiley   +1 more source

Improving PARP inhibitor efficacy in bladder cancer without genetic BRCAness by combination with PLX51107

open access: yesMolecular Oncology, EarlyView.
Clinical trials on PARP inhibitors in urothelial carcinoma (UC) showed limited efficacy and a lack of predictive biomarkers. We propose SLFN5, SLFN11, and OAS1 as UC‐specific response predictors. We suggest Talazoparib as the better PARP inhibitor for UC than Olaparib.
Jutta Schmitz   +15 more
wiley   +1 more source

Methylation biomarkers can distinguish pleural mesothelioma from healthy pleura and other pleural pathologies

open access: yesMolecular Oncology, EarlyView.
We developed and validated a DNA methylation–based biomarker panel to distinguish pleural mesothelioma from other pleural conditions. Using the IMPRESS technology, we translated this panel into a clinically applicable assay. The resulting two classifier models demonstrated excellent performance, achieving high AUC values and strong diagnostic accuracy.
Janah Vandenhoeck   +12 more
wiley   +1 more source

Evaluation metrics and statistical tests for machine learning

open access: yesScientific Reports
Research on different machine learning (ML) has become incredibly popular during the past few decades. However, for some researchers not familiar with statistics, it might be difficult to understand how to evaluate the performance of ML models and ...
O. Rainio, J. Teuho, R. Klén
semanticscholar   +1 more source

Next‐generation proteomics improves lung cancer risk prediction

open access: yesMolecular Oncology, EarlyView.
This is one of very few studies that used prediagnostic blood samples from participants of two large population‐based cohorts. We identified, evaluated, and validated an innovative protein marker model that outperformed an established risk prediction model and criteria employed by low‐dose computed tomography in lung cancer screening trials.
Megha Bhardwaj   +4 more
wiley   +1 more source

Developing evidence‐based, cost‐effective P4 cancer medicine for driving innovation in prevention, therapeutics, patient care and reducing healthcare inequalities

open access: yesMolecular Oncology, EarlyView.
The cancer problem is increasing globally with projections up to the year 2050 showing unfavourable outcomes in terms of incidence and cancer‐related deaths. The main challenges are prevention, improved therapeutics resulting in increased cure rates and enhanced health‐related quality of life.
Ulrik Ringborg   +43 more
wiley   +1 more source

Machine-learning-revealed statistics of the particle-carbon/binder detachment in lithium-ion battery cathodes

open access: yesNature Communications, 2020
The microstructure of a composite electrode determines how individual battery particles are charged and discharged in a lithium-ion battery. It is a frontier challenge to experimentally visualize and, subsequently, to understand the electrochemical ...
Zhisen Jiang   +10 more
semanticscholar   +1 more source

Tumor mutational burden as a determinant of metastatic dissemination patterns

open access: yesMolecular Oncology, EarlyView.
This study performed a comprehensive analysis of genomic data to elucidate whether metastasis in certain organs share genetic characteristics regardless of cancer type. No robust mutational patterns were identified across different metastatic locations and cancer types.
Eduardo Candeal   +4 more
wiley   +1 more source

RaMBat: Accurate identification of medulloblastoma subtypes from diverse data sources with severe batch effects

open access: yesMolecular Oncology, EarlyView.
To integrate multiple transcriptomics data with severe batch effects for identifying MB subtypes, we developed a novel and accurate computational method named RaMBat, which leveraged subtype‐specific gene expression ranking information instead of absolute gene expression levels to address batch effects of diverse data sources.
Mengtao Sun, Jieqiong Wang, Shibiao Wan
wiley   +1 more source

A Survey on Nonconvex Regularization-Based Sparse and Low-Rank Recovery in Signal Processing, Statistics, and Machine Learning [PDF]

open access: yesIEEE Access, 2018
In the past decade, sparse and low-rank recovery has drawn much attention in many areas such as signal/image processing, statistics, bioinformatics, and machine learning.
Fei Wen, L. Chu, Peilin Liu, R. Qiu
semanticscholar   +1 more source

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