AIMC Topic: Sample Size

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Not just "big" data: Importance of sample size, measurement error, and uninformative predictors for developing prognostic models for digital interventions.

Behaviour research and therapy Apr 14, 2022
There is strong interest in developing a more efficient mental health care system. Digital interventions and predictive models of treatment prognosis will likely play an important role in this endeavor. This article reviews the application of popular...
Prognosis Sample Size Linear Models Humans Machine Learning Algorithms
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A Cascade Flexible Neural Forest Model for Cancer Subtypes Classification on Gene Expression Data.

Computational intelligence and neuroscience Oct 5, 2021
The correct classification of cancer subtypes is of great significance for the in-depth study of cancer pathogenesis and the realization of accurate treatment for cancer patients. In recent years, the classification of cancer subtypes using deep neur...
Humans Neural Networks, Computer Neoplasms Sample Size Gene Expression
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Deep learning methods for automatic segmentation of lower leg muscles and bones from MRI scans of children with and without cerebral palsy.

NMR in biomedicine Sep 21, 2021
Cerebral palsy is a neurological condition that is known to affect muscle growth. Detailed investigations of muscle growth require segmentation of muscles from MRI scans, which is typically done manually. In this study, we evaluated the performance o...
Humans Female Muscle, Skeletal Adolescent Sample Size Male Bone and Bones Child, Preschool Cerebral Palsy Deep Learning Leg Child
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The impact of training sample size on deep learning-based organ auto-segmentation for head-and-neck patients.

Physics in medicine and biology Sep 14, 2021
To investigate the impact of training sample size on the performance of deep learning-based organ auto-segmentation for head-and-neck cancer patients, a total of 1160 patients with head-and-neck cancer who received radiotherapy were enrolled in this ...
Head and Neck Neoplasms Sample Size Organs at Risk Tomography, X-Ray Computed Humans Deep Learning Image Processing, Computer-Assisted
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Value of a deep learning-based algorithm for detecting Lung-RADS category 4 nodules on chest radiographs in a health checkup population: estimation of the sample size for a randomized controlled trial.

European radiology Jul 15, 2021
OBJECTIVE: To explore the value of a deep learning-based algorithm in detecting Lung CT Screening Reporting and Data System category 4 nodules on chest radiographs from an asymptomatic health checkup population.
Sensitivity and Specificity Lung Deep Learning Retrospective Studies Tomography, X-Ray Computed Radiography, Thoracic Lung Neoplasms Sample Size Radiographic Image Interpretation, Computer-Assisted Humans Algorithms
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Embryo selection with artificial intelligence: how to evaluate and compare methods?

Journal of assisted reproduction and genetics Jun 26, 2021
Embryo selection within in vitro fertilization (IVF) is the process of evaluating qualities of fertilized oocytes (embryos) and selecting the best embryo(s) available within a patient cohort for subsequent transfer or cryopreservation. In recent year...
Sample Size Blastocyst Calibration Decision Making, Computer-Assisted Humans Cryopreservation Artificial Intelligence Image Processing, Computer-Assisted Fertilization in Vitro Databases, Factual Pregnancy Embryo Transfer Area Under Curve Female Sensitivity and Specificity
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Risks of feature leakage and sample size dependencies in deep feature extraction for breast mass classification.

Medical physics Apr 12, 2021
PURPOSE: Transfer learning is commonly used in deep learning for medical imaging to alleviate the problem of limited available data. In this work, we studied the risk of feature leakage and its dependence on sample size when using pretrained deep con...
Mammography Sample Size Breast Humans Neural Networks, Computer Algorithms
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Residual wide-kernel deep convolutional auto-encoder for intelligent rotating machinery fault diagnosis with limited samples.

Neural networks : the official journal of the International Neural Network Society Apr 9, 2021
This paper deals with the development of a novel deep learning framework to achieve highly accurate rotating machinery fault diagnosis using residual wide-kernel deep convolutional auto-encoder. Unlike most existing methods, in which the input data i...
Deep Learning Signal Processing, Computer-Assisted Sample Size Rotation Equipment and Supplies
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Machine learning model for predicting severity prognosis in patients infected with COVID-19: Study protocol from COVID-AI Brasil.

PloS one Feb 1, 2021
The new coronavirus, which began to be called SARS-CoV-2, is a single-stranded RNA beta coronavirus, initially identified in Wuhan (Hubei province, China) and currently spreading across six continents causing a considerable harm to patients, with no ...
Sample Size Humans Artificial Intelligence Machine Learning Prognosis COVID-19 Brazil Severity of Illness Index Algorithms
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A random forest based biomarker discovery and power analysis framework for diagnostics research.

BMC medical genomics Nov 23, 2020
BACKGROUND: Biomarker identification is one of the major and important goal of functional genomics and translational medicine studies. Large scale -omics data are increasingly being accumulated and can provide vital means for the identification of bi...
Datasets as Topic Workflow Lipidomics Transcriptome Regression Analysis Algorithms Molecular Diagnostic Techniques Decision Trees Humans Biomarkers Metabolomics Sample Size Machine Learning Computer Simulation
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