Binned multinomial logistic regression for integrative cell-type annotation. [PDF]
Ann Appl Stat, 2023 Categorizing individual cells into one of many known cell type categories, also known as cell type annotation, is a critical step in the analysis of single-cell genomics data. The current process of annotation is time-intensive and subjective, which has led to different studies describing cell types with labels of varying degrees of resolution.
Motwani K, Bacher R, Molstad AJ.
europepmc +7 more sources
Multinomial logistic regression method for early detection of autism spectrum disorders
Measurement: SensorsA child with autism spectrum syndrome may have diverse personality traits, making it a heterogeneous condition, with cognitive abilities, emotional types, and so on.
D. Jayaprakash, C.S. Kanimozhiselvi
doaj +2 more sources
Multinomial logistic regression algorithm for the classification of patients with parkinsonisms [PDF]
EJNMMI ResearchBackground Accurate differential diagnosis of neurodegenerative parkinsonisms is challenging due to overlapping early symptoms and high rates of misdiagnosis.
Eva Štokelj +4 more
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Youth’s Entrepreneurial Intention: A Multinomial Logistic Regression Analysis of the Factors Influencing Greek HEI Students in Time of Crisis [PDF]
Sustainability, 2022 Governments’ coronavirus disease (COVID-19) measures have forced the community to stay at home. During this period, youths have had time to think about their career paths.
Konstantina Ragazou +4 more
semanticscholar +2 more sources
SAGE Open, 2020 Financial risk tolerance is one of the important factors affecting the financial investment decisions of individuals and institutional investors and a crucial factor of financial planning and financial counseling.
Yılmaz Bayar +3 more
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Enhanced SNP genotyping with symmetric multinomial logistic regression [PDF]
Forensic Science International: GeneticsAbstractIn genotyping, determining Single Nucleotide Polymorphisms (SNPs) is standard practice, but it becomes difficult when analysing small quantities of input DNA, as is often required in forensic applications. Existing SNP genotyping methods, such as the HID SNP Genotyper Plugin (HSG) from Thermo Fisher Scientific, perform well with adequate DNA ...
Nielsen, Malte Bødkergaard +4 more
openaire +6 more sources
Can Multinomial Logistic Regression Predicts Research Group using Text Input?
Knowledge Engineering and Data Science, 2022 While submitting proposals in SISINTA, students often confuse or falsely submit their proposals to the less relevant or incorrect research group. There are 13 research groups for the students to choose from.
Harits Ar Rosyid +3 more
doaj +3 more sources
Determinants of decision-making among ever-married women in Indian households: A cross-sectional study based on binary logistic regression and multinomial logistic regression. [PDF]
PLoS ONEEmpowerment of women is intrinsically linked to their participation in household decision-making, a crucial component for achieving gender equality and improving family well-being.
Riti Deshmukh, Sabina Bano, Sakshi
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Approximate Sparse Multinomial Logistic Regression for Classification
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020 We propose a new learning rule for sparse multinomial logistic regression (SMLR). The new rule is the generalization of the one proposed in the pioneering work by Krishnapuram et al. In our proposed method, the parameters of SMLR are iteratively estimated from log-posterior by using some approximations.
K. Kayabol
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Navigating personal recovery: multinomial logistic regression analysis of schizophrenia outcomes in community-dwelling individuals [PDF]
General PsychiatryBackground Schizophrenia is a chronic mental disorder affecting individuals globally, emphasising the significance of personal recovery in mental healthcare.
Jintana Yunibhand +2 more
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