Results 51 to 60 of about 3,742,082 (296)
Predicting Customer’s Satisfaction (Dissatisfaction) Using Logistic Regression [PDF]
Customer satisfaction is a metric of how products and services offered by companies meet customer expectations. This performance indicator assists companies in managing and monitoring their business effectively.
Adarsh Anand, Gunjan Bansal
doaj +1 more source
Group Logistic Regression Models with lp,q Regularization
In this paper, we proposed a logistic regression model with lp,q regularization that could give a group sparse solution. The model could be applied to variable-selection problems with sparse group structures. In the context of big data, the solutions for
Yanfang Zhang, Chuanhua Wei, Xiaolin Liu
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Circulating microRNA profiles distinguish nonmalignant Lynch syndrome from cancer‐associated Lynch syndrome, sporadic colorectal cancer, and healthy controls. Age‐stratified analysis reveals disease‐specific regulatory states, and a six‐miRNA panel shows concordant separation in an independent colorectal tissue cohort.
Ramadhani Salum Chambuso +5 more
wiley +1 more source
Deforestation modelling using logistic regression and GIS
A methodology has been used by means of which modellers and planners can quantify the certainty in predicting the location of deforestation. Geographic information system and logistic regression analyses were employed to predict the spatial distribution ...
M. Pir Bavaghar
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Tumour‐proximal deep serum proteomics identifies biomarkers associated with ovarian cancer
New biomarkers are needed for early ovarian cancer detection. Ovarian (tumour‐proximal) and peripheral vein serum from healthy women and patients with benign or malignant tumours underwent nanoparticle‐enriched deep proteomics. Ovarian serum yielded more protein identifications and revealed tumour‐reflective signatures.
Darren Lau +9 more
wiley +1 more source
Kubu Raya Regency is a regency in the province of West Kalimantan which has a wetland ecosystem including a high-density swamp or peatland ecosystem along with an extensive area of mangroves.
Alfa Nugraha Pradana +2 more
doaj +1 more source
Logistic Regression Diagnostics
A maximum likelihood fit of a logistic regression model (and other similar models) is extremely sensitive to outlying responses and extreme points in the design space. We develop diagnostic measures to aid the analyst in detecting such observations and in quantifying their effect on various aspects of the maximum likelihood fit.
openaire +3 more sources
Attitudes of cancer patients toward ctDNA‐based liquid biopsy for follow‐up
This mixed‐methods study explored cancer patients' experiences, knowledge, and preferences regarding ctDNA‐based liquid biopsy for follow‐up. Awareness of ctDNA was low and recall of previous liquid biopsy was imperfect, yet acceptance was high.
Siddharth Chhajlani +7 more
wiley +1 more source
Ionomycin suppresses cancer cell growth by disrupting mitochondrial transcription
In this study, we identify a new function for the selective Ca2+ ionophore, ionomycin, as an inhibitor of mitochondrial transcription. Both total and nascent RNA analyses revealed that ionomycin treatment reduces the transcription of mitochondrial genes.
Lishen Wang +10 more
wiley +1 more source
Targeting: Logistic Regression, Special Cases and Extensions
Logistic regression is a classical linear model for logit-transformed conditional probabilities of a binary target variable. It recovers the true conditional probabilities if the joint distribution of predictors and the target is of log-linear form ...
Helmut Schaeben
doaj +1 more source

