ArticleIEEE transactions on pattern analysis and machine intelligence2020
Logistic Regression Confined by Cardinality-Constrained Sample and Feature Selection.
Article in IEEE transactions on pattern analysis and machine intelligence, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed.
- Differentiating the differentiation degree of gastric cancer based on MRI radiomics.BMC medical imaging · 2025Article
- Subject Harmonization of Digital Biomarkers: Improved Detection of Mild Cognitive Impairment from Language Markers.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2024Article
- Determination of Survival of Gastric Cancer Patients With Distant Lymph Node Metastasis Using Prealbumin Level and Prothrombin Time: Contour Plots Based on Random Survival Forest Algorithm on High-Dimensionality Clinical and Laboratory Datasets.Journal of gastric cancer · 2022Article
- Automatic detection of multiple types of pneumonia: Open dataset and a multi-scale attention network.Biomedical signal processing and control · 2022Article
- A machine learning method based on the genetic and world competitive contests algorithms for selecting genes or features in biological applications.Scientific reports · 2021Article
- Circulating tRNA-derived small RNAs (tsRNAs) signature for the diagnosis and prognosis of breast cancer.NPJ breast cancer · 2021Article
- A data mining based clinical decision support system for survival in lung cancer.Reports of practical oncology and radiotherapy : journal of Greatpoland Cancer Center in Poznan and Polish Society of Radiation Oncology · 2021Article
- Joint prediction and time estimation of COVID-19 developing severe symptoms using chest CT scan.Medical image analysis · 2021Article
- Evaluation of Feature Selection Methods for Mammographic Breast Cancer Diagnosis in a Unified Framework.BioMed research international · 2021Article
- Training confounder-free deep learning models for medical applications.Nature communications · 2020Article
- Novel Machine Learning Identifies Brain Patterns Distinguishing Diagnostic Membership of Human Immunodeficiency Virus, Alcoholism, and Their Comorbidity of Individuals.Biological psychiatry. Cognitive neuroscience and neuroimaging · 2019Article
- A novel diagnostic model for early-stage high-grade serous ovarian cancer based on serum tRNA-derived fragments.Cancer biomarkers : section A of Disease markersArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Many vision-based applications rely on logistic regression for embedding classification within a probabilistic context, such as recognition in images and videos or identifying disease-specific image phenotypes from neuroimages. Logistic regression, however, often performs poorly when trained on data that is noisy, has irrelevant features, or when the samples are distributed across the classes in an imbalanced setting; a common occurrence in visual recognition tasks. To deal with those issues, researchers generally rely on ad-hoc regularization techniques or model a subset of these issues. We instead propose a mathematically sound logistic regression model that selects a subset of (relevant) features and (informative and balanced) set of samples during the training process. The model does so by applying cardinality constraints (via l
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.