Results 61 to 70 of about 326,273 (311)

Circulating tumor cell viability during and after radiotherapy mirrors treatment response in cancer patients

open access: yesMolecular Oncology, EarlyView.
Radiotherapy (RT) response depends on the DNA repair capacity of tumor and host cells. We show that circulating tumor cell (CTC) counts and apoptosis rates before and after RT predict treatment response and outcome, which can be accessed via easily accessible liquid biopsy approaches. Created in BioRender. Wikman, H.
Yvonne Goy   +10 more
wiley   +1 more source

Drowsiness Estimation Using Electroencephalogram and Recurrent Support Vector Regression

open access: yesInformation, 2019
As a cause of accidents, drowsiness can cause economical and physical damage. A range of drowsiness estimation methods have been proposed in previous studies to aid accident prevention and address this problem.
Izzat Aulia Akbar, Tomohiko Igasaki
doaj   +1 more source

Using Support Vector Machine for Prediction Dynamic Voltage Collapse in an Actual Power System [PDF]

open access: yes, 2008
—This paper presents dynamic voltage collapse prediction on an actual power system using support vector machines. Dynamic voltage collapse prediction is first determined based on the PTSI calculated from information in dynamic simulation
Mohamed , Azah   +2 more
core  

Finding novel vulnerabilities of hypomorphic BRCA1 alleles

open access: yesMolecular Oncology, EarlyView.
Synthetic lethality screens performed to identify novel vulnerabilities often model complete gene loss, thereby overlooking patient‐derived hypomorphic mutations. In this study, we have performed genome‐wide CRISPR screens on BRCA1 hypomorphic mutations, showing BRCA1I26A behaves like wild‐type, while BRCA1R1699Q mimics deficiency. Furthermore, we have
Anne Schreuder   +10 more
wiley   +1 more source

Multi-Output Bayesian Support Vector Regression Considering Dependent Outputs

open access: yesMathematics
Multi-output regression aims to utilize the correlation between outputs to achieve information transfer between dependent outputs, thus improving the accuracy of predictive models.
Yanlin Wang, Zhijun Cheng, Zichen Wang
doaj   +1 more source

Statistical mechanics of support vector regression

open access: yesPhysical Review E
A key problem in deep learning and computational neuroscience is relating the geometrical properties of neural representations to task performance. Here, we consider this problem for continuous decoding tasks where neural variability may affect task precision.
Abdulkadir Canatar, SueYeon Chung
openaire   +3 more sources

Longitudinal genome‐wide aneuploidy measurements in circulating cell‐free DNA to predict lack of benefit from pembrolizumab in patients with metastatic urothelial cancer

open access: yesMolecular Oncology, EarlyView.
Many patients with urothelial cancer do not benefit from treatment with pembrolizumab, while at risk of severe side effects. Changes in the levels of circulating tumor DNA early during treatment, measured by a simple and affordable assay that can be easily implemented in the clinic, can be used as a prognostic tool to identify these patients.
Youssra Salhi   +14 more
wiley   +1 more source

Orthogonal least squares regression with tunable kernels [PDF]

open access: yes, 2005
A novel technique is proposed to construct sparse regression models based on the orthogonal least squares method with tunable kernels. The proposed technique tunes the centre vector and diagonal covariance matrix of individual regressor by incrementally ...
Wang, X. X.   +4 more
core   +1 more source

MITF maintains genome stability in nonmelanocyte lineages

open access: yesMolecular Oncology, EarlyView.
MITF is essential for melanocyte survival and acts as an oncogene in 10%–20% of melanomas. We show that MITF depletion causes genome instability in nonmelanocytic cells, leading to LATS2‐mediated P53 activation, cell cycle arrest, and apoptosis. This study highlights the role of MITF as a genome maintenance factor beyond the melanocyte lineage. Created
Drifa H. Gudmundsdottir   +13 more
wiley   +1 more source

Approximation Analysis of Learning Algorithms for Support Vector Regression and Quantile Regression

open access: yesJournal of Applied Mathematics, 2012
We study learning algorithms generated by regularization schemes in reproducing kernel Hilbert spaces associated with an ϵ-insensitive pinball loss. This loss function is motivated by the ϵ-insensitive loss for support vector regression and the pinball ...
Dao-Hong Xiang, Ting Hu, Ding-Xuan Zhou
doaj   +1 more source

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