Results 91 to 100 of about 103,585 (306)
ANN vs. SVM : which one performs better in classification of MCCs in mammogram imaging
, 2012 Classification of microcalcification clusters from mammograms plays essential roles in computer-aided diagnosis for early detection of breast cancer, where support vector machine (SVM) and artificial neural network (ANN) are two commonly used techniques.
Jinchang Ren, Ren, Jinchang
core +1 more source
Molecular Oncology, EarlyView.A urine‐based digital PCR assay targeting two hotspot TERT promoter variants detected bladder cancer with high sensitivity and no false positives in this case–control cohort. The streamlined AbsoluteQ workflow outperformed Sanger sequencing and supports non‐invasive molecular testing for bladder cancer detection.
Anna Nykel +12 more
wiley +1 more source
FEBS Open Bio, EarlyView.Erythropoietin administration suppresses hepatic soluble epoxide hydrolase (sEH) expression, leading to increased CYP‐derived epoxides. This is associated with a shift in hepatic macrophage polarization characterized by reduced M1 markers and increased M2 markers, along with reduced hepatic inflammation, suppressed hepatic lipogenesis, and attenuated ...
Takeshi Goda +12 more
wiley +1 more source
FEBS Open Bio, EarlyView.14‐day casting‐induced immobilization reduced gastrocnemius muscle mass and increased non‐heme iron and ferritin heavy chain levels. Despite iron accumulation, transferrin receptor 1 and iron regulatory protein 2 were paradoxically upregulated. Lipid peroxidation was elevated without compensatory antioxidant responses.
Haruka Yokogawa +2 more
wiley +1 more source
A Classification Method Based on Feature Selection for Imbalanced Data
IEEE Access, 2019 Imbalanced data are very common in the real world, and it may deteriorate the performance of the conventional classification algorithms. In order to resolve the imbalanced classification problems, we propose an ensemble classification method that ...
Yi Liu +4 more
doaj +1 more source
Gaussian mixture based semi supervised boosting for imbalanced data classification
, 2017 Semi supervised approaches are practical in problem domain where pattern clustering is supposed to provide good classification. Gaussian Mixture Model (GMM) can approximate arbitrary probability distribution, thus is considered as a dominant tool for ...
Paul, MK, Pal, B
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Multi-class Pattern Classification in Imbalanced Data [PDF]
, 2010 The majority of multi-class pattern classification techniques are proposed for learning from balanced datasets. However, in several real-world domains, the datasets have imbalanced data distribution, where some classes of data may have few training ...
Amal S. Ghanem +5 more
core +1 more source
, 2022 Imbalanced ClassTHIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE.
Mutrofin, S (via Mendeley Data)
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Why human connection is the true metric of research success
FEBS Open Bio, EarlyView.Human‐centred mentorship can be shaped by mentor attributes, actions, intrinsic drive and career ambition. Drawing on reflections across Singapore and France, as well as workshop insights from FEBS‐IUBMB ENABLE 2024, this article shows that human‐centred mentorship creates the conditions for sustainable growth, well‐being and retention in research ...
Timothy Lin Yun Tan +3 more
wiley +1 more source
FEBS Open Bio, EarlyView.Abruptly changing from aerobic to anaerobic conditions (sudden anaerobization) induced growth inhibition and a significant increase in intracellular labile ferrous iron in the aerotolerant anaerobe Amphibacillus xylanus. We found that free flavins mediate efficient electron transfer from NADH to ferric iron under anaerobic conditions, suggesting that ...
Shinya Kimata +13 more
wiley +1 more source