AIMC Topic: Sample Size

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Advancing proactive crash prediction: A discretized duration approach for predicting crashes and severity.

Accident; analysis and prevention Dec 5, 2023
Driven by advancements in data-driven methods, recent developments in proactive crash prediction models have primarily focused on implementing machine learning and artificial intelligence. However, from a causal perspective, statistical models are pr...
Artificial Intelligence Logistic Models Humans Sample Size Accidents, Traffic Rural Population Models, Statistical
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Sample size in quantitative instrument-based studies published in Scopus up to 2022: An artificial intelligence aided systematic review.

Acta psychologica Nov 28, 2023
Despite their popularity, quantitative instruments like Likert scales struggle with a practical issue for research projects - how many participants have to fill out the instrument? This study started with the data for 31,271 articles downloaded from ...
Humans Artificial Intelligence Sample Size Bibliometrics
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Sample size and predictive performance of machine learning methods with survival data: A simulation study.

Statistics in medicine Nov 10, 2023
Prediction models are increasingly developed and used in diagnostic and prognostic studies, where the use of machine learning (ML) methods is becoming more and more popular over traditional regression techniques. For survival outcomes the Cox proport...
Proportional Hazards Models Humans Neural Networks, Computer Computer Simulation Machine Learning Sample Size
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Multiple-instance ensemble for construction of deep heterogeneous committees for high-dimensional low-sample-size data.

Neural networks : the official journal of the International Neural Network Society Aug 22, 2023
Deep ensemble learning, where we combine knowledge learned from multiple individual neural networks, has been widely adopted to improve the performance of neural networks in deep learning. This field can be encompassed by committee learning, which in...
Neural Networks, Computer Sample Size
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MISPEL: A supervised deep learning harmonization method for multi-scanner neuroimaging data.

Medical image analysis Aug 9, 2023
Large-scale data obtained from aggregation of already collected multi-site neuroimaging datasets has brought benefits such as higher statistical power, reliability, and robustness to the studies. Despite these promises from growth in sample size, sub...
Deep Learning Sample Size Reproducibility of Results Pancreas Neuroimaging Humans
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Spatial-Spectral Unified Adaptive Probability Graph Convolutional Networks for Hyperspectral Image Classification.

IEEE transactions on neural networks and learning systems Jul 6, 2023
In hyperspectral image (HSI) classification task, semisupervised graph convolutional network (GCN)-based methods have received increasing attention. However, two problems still need to be addressed. The first is that the initial graph structure in th...
Probability Sample Size Benchmarking Learning Neural Networks, Computer
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A simulation study on missing data imputation for dichotomous variables using statistical and machine learning methods.

Scientific reports Jun 9, 2023
The problem of missing data, particularly for dichotomous variables, is a common issue in medical research. However, few studies have focused on the imputation methods of dichotomous data and their performance, as well as the applicability of these i...
Support Vector Machine Cluster Analysis Sample Size Machine Learning Computer Simulation
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Diagnostic performance of deep learning in infectious keratitis: a systematic review and meta-analysis protocol.

BMJ open May 10, 2023
INTRODUCTION: Infectious keratitis (IK) represents the fifth-leading cause of blindness worldwide. A delay in diagnosis is often a major factor in progression to irreversible visual impairment and/or blindness from IK. The diagnostic challenge is fur...
Keratitis Deep Learning Sample Size Systematic Reviews as Topic Artificial Intelligence Research Design Humans Meta-Analysis as Topic
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Leveraging Semantic Type Dependencies for Clinical Named Entity Recognition.

AMIA ... Annual Symposium proceedings. AMIA Symposium Apr 29, 2023
Previous work on clinical relation extraction from free-text sentences leveraged information about semantic types from clinical knowledge bases as a part of entity representations. In this paper, we exploit additional evidence by also making use of ....
Unified Medical Language System Sample Size Knowledge Bases Datasets as Topic Semantics Reproducibility of Results Humans Natural Language Processing
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Machine learning models trained on synthetic datasets of multiple sample sizes for the use of predicting blood pressure from clinical data in a national dataset.

PloS one Mar 16, 2023
INTRODUCTION: The potential for synthetic data to act as a replacement for real data in research has attracted attention in recent months due to the prospect of increasing access to data and overcoming data privacy concerns when sharing data. The fie...
Humans Artificial Intelligence Sample Size Machine Learning Bayes Theorem Blood Pressure
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