Results 81 to 90 of about 2,374,745 (297)

Imbalanced Data Parameter Optimization of Convolutional Neural Networks Based on Analysis of Variance

Applied Sciences
Classifying imbalanced data is important due to the significant practical value of accurately categorizing minority class samples, garnering considerable interest in many scientific domains.
Ruiao Zou, Nan Wang
doaj   +1 more source

Clinical performance of the urine‐based TERT promoter AbsoluteQ Digital PCR for non‐invasive detection of bladder cancer

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, Izabela Kubiak, Lena Rutkowska, Żaneta Kasprzyk, Łukasz Kępczyński, Michał Bednarek, Dariusz Sobieraj, Jacek Wilkosz, Piotr Kania, Adam Jędrzejczyk, Bogdan Kałużewski, Agnieszka Gach, Tadeusz Kałużewski   +12 more
wiley   +1 more source

Drilling Condition Identification Method for Imbalanced Datasets

Applied Sciences
To address the challenges posed by class imbalance and temporal dependency in drilling condition data and enhance the accuracy of condition identification, this study proposes an integrated method combining feature engineering, data resampling, and deep ...
Yibing Yu, Huilin Yang, Fengjia Peng, Xi Wang   +3 more
doaj   +1 more source

Exploring Early Prediction of Chronic Kidney Disease Using Machine Learning Algorithms for Small and Imbalanced Datasets

Applied Sciences, 2022
Chronic kidney disease (CKD) is a worldwide public health problem, usually diagnosed in the late stages of the disease. To alleviate such issue, investment in early prediction is necessary.
Andressa C. M. da Silveira, Álvaro Sobrinho, Leandro Dias da Silva, Evandro de Barros Costa, Maria Eliete Pinheiro, Angelo Perkusich   +5 more
doaj   +1 more source

Circulating microRNA signatures of cachexia and cancer in Canis familiaris as a comparative oncology model for human disease

Molecular Oncology, EarlyView.
Circulating microRNAs as biomarkers of cachexia and sex‐specific cancer in senior dogs. In 25 client‐owned dogs, four circulating miRNAs (miR‐15a, miR‐15b, miR‐16, miR‐140) were downregulated in cachexia, with miR‐16 the strongest individual biomarker (AUC = 0.899).
Soon‐Seok Park, Kyongman An, Gyeonghwa Kim, Soo‐Nyun Choi, Hong‐Ki Lee, Keun Hur, Kyu‐Shik Jeong   +6 more
wiley   +1 more source

Effective Class-Imbalance Learning Based on SMOTE and Convolutional Neural Networks

Applied Sciences, 2023
Imbalanced Data (ID) is a problem that deters Machine Learning (ML) models from achieving satisfactory results. ID is the occurrence of a situation where the quantity of the samples belonging to one class outnumbers that of the other by a wide margin ...
Javad Hassannataj Joloudari, Abdolreza Marefat, Mohammad Ali Nematollahi, Solomon Sunday Oyelere, Sadiq Hussain   +4 more
doaj   +1 more source

Targeting transcription factors associated with hemoglobinopathies: Lessons from successful interventions and implications for cancer

Molecular Oncology, EarlyView.
This review summarizes the transcription factors, repressive chromatin‐modifying complexes, and epigenetic mechanisms that control fetal hemoglobin repression. Notably, many regulators of γ‐globin silencing also function in transcriptional and epigenetic networks that drive cancer, highlighting opportunities to translate advances in hemoglobinopathy ...
Meigen Yu, Puspa Das, Xing Zhang, Xiaodong Cheng   +3 more
wiley   +1 more source

Granular Classification for Imbalanced Datasets: A Minkowski Distance-Based Method

Algorithms, 2021
The problem of classification for imbalanced datasets is frequently encountered in practical applications. The data to be classified in this problem are skewed, i.e., the samples of one class (the minority class) are much less than those of other classes
Chen Fu, Jianhua Yang
doaj   +1 more source

Exploring Data Augmentation and Active Learning Benefits in Imbalanced Datasets

Mathematics
Despite the increasing availability of vast amounts of data, the challenge of acquiring labeled data persists. This issue is particularly serious in supervised learning scenarios, where labeled data are essential for model training.
Luis Moles, Alain Andres, Goretti Echegaray, Fernando Boto   +3 more
semanticscholar   +1 more source

Accurate and noninvasive prostate cancer detection using plasma‐derived extracellular vesicle RNA

FEBS Open Bio, EarlyView.
Plasma extracellular vesicles were captured with WGA‐conjugated magnetic beads and profiled for RNA biomarkers. A three‐RNA panel (NM_024955, NR_047469, and NR_002564) distinguished prostate cancer from healthy controls and benign prostatic hyperplasia, supporting a simple, noninvasive approach to improve prostate cancer detection.
Hanping Wei, Haoran Wu, Wei Feng
wiley   +1 more source