AIMC Topic: Multivariate Analysis

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Is there a competitive advantage to using multivariate statistical or machine learning methods over the Bross formula in the hdPS framework for bias and variance estimation?

PloS one Jan 1, 2025
PURPOSE: We aim to evaluate various proxy selection methods within the context of high-dimensional propensity score (hdPS) analysis. This study aimed to systematically evaluate and compare the performance of traditional statistical methods and machin...
Bias Multivariate Analysis Propensity Score Computer Simulation Nutrition Surveys Models, Statistical Humans Machine Learning Algorithms
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Accurate total consumer price index forecasting with data augmentation, multivariate features, and sentiment analysis: A case study in Korea.

PloS one Jan 1, 2025
The Consumer Price Index (CPI) is a key economic indicator used by policymakers worldwide to monitor inflation and guide monetary policy decisions. In Korea, the CPI significantly impacts decisions on interest rates, fiscal policy frameworks, and the...
Humans Models, Economic Neural Networks, Computer Consumer Behavior Forecasting Multivariate Analysis Republic of Korea Commerce Decision Making
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Leveraging multivariate analysis and adjusted mutual information to improve stroke prediction and interpretability.

Neurosciences (Riyadh, Saudi Arabia) Jul 1, 2024
OBJECTIVES: To develop a machine learning model to accurately predict stroke risk based on demographic and clinical data. It also sought to identify the most significant stroke risk factors and determine the optimal machine learning algorithm for str...
Cross-Sectional Studies Male Middle Aged Stroke Female Humans Risk Factors Multivariate Analysis Machine Learning Aged Adult
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Application of Medical Statistical and Machine Learning Methods in the Age Estimation of Living Individuals.

Fa yi xue za zhi Apr 25, 2024
In the study of age estimation in living individuals, a lot of data needs to be analyzed by mathematical statistics, and reasonable medical statistical methods play an important role in data design and analysis. The selection of accurate and appropri...
Humans Machine Learning Multivariate Analysis Age Determination by Teeth Age Determination by Skeleton
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Data scientists are predicting sports injuries with an algorithm.

Nature Apr 1, 2021
Male Data Science Adolescent Decision Trees Humans Machine Learning Forecasting Athletic Performance Athletes Multivariate Analysis Athletic Injuries
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Quantitative Longitudinal Predictions of Alzheimer's Disease by Multi-Modal Predictive Learning.

Journal of Alzheimer's disease : JAD Jan 1, 2021
BACKGROUND: Quantitatively predicting the progression of Alzheimer's disease (AD) in an individual on a continuous scale, such as the Alzheimer's Disease Assessment Scale-cognitive (ADAS-cog) scores, is informative for a personalized approach as oppo...
Humans Machine Learning Disease Progression Regression Analysis Alzheimer Disease Multivariate Analysis
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A statistically rigorous deep neural network approach to predict mortality in trauma patients admitted to the intensive care unit.

The journal of trauma and acute care surgery Oct 1, 2020
BACKGROUND: Trauma patients admitted to critical care are at high risk of mortality because of their injuries. Our aim was to develop a machine learning-based model to predict mortality using Fahad-Liaqat-Ahmad Intensive Machine (FLAIM) framework. We...
Wounds and Injuries Proportional Hazards Models Multivariate Analysis Injury Severity Score Organ Dysfunction Scores ROC Curve Sodium Critical Care Intensive Care Units Adult Machine Learning Humans Female Male Prognosis Neural Networks, Computer Middle Aged Hospitalization Retrospective Studies Sepsis Young Adult Critical Illness
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Next-Generation Radiogenomics Sequencing for Prediction of EGFR and KRAS Mutation Status in NSCLC Patients Using Multimodal Imaging and Machine Learning Algorithms.

Molecular imaging and biology Aug 1, 2020
PURPOSE: Considerable progress has been made in the assessment and management of non-small cell lung cancer (NSCLC) patients based on mutation status in the epidermal growth factor receptor (EGFR) and Kirsten rat sarcoma viral oncogene (KRAS). At the...
Multimodal Imaging Area Under Curve Mutation Positron-Emission Tomography High-Throughput Nucleotide Sequencing Multivariate Analysis ErbB Receptors Male Humans Lung Neoplasms Machine Learning Genomics Proto-Oncogene Proteins p21(ras) Algorithms Carcinoma, Non-Small-Cell Lung Female Aged
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Modeling and measurement of signaling outcomes affecting decision making in noisy intracellular networks using machine learning methods.

Integrative biology : quantitative biosciences from nano to macro May 21, 2020
Characterization of decision-making in cells in response to received signals is of importance for understanding how cell fate is determined. The problem becomes multi-faceted and complex when we consider cellular heterogeneity and dynamics of biochem...
Signal Transduction Decision Making DNA Damage Outcome Assessment, Health Care Humans Normal Distribution Probability Algorithms Machine Learning PTEN Phosphohydrolase Reproducibility of Results ROC Curve Tumor Suppressor Protein p53 Multivariate Analysis Genes, p53
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Multivariate Data Analysis and Machine Learning for Prediction of MCI-to-AD Conversion.

Advances in experimental medicine and biology Jan 1, 2020
There has always been a need for discovering efficient and dependable Alzheimer's disease (AD) diagnostic biomarkers. Like the majority of diseases, the earlier the diagnosis, the most effective the treatment. (Semi)-automated structural magnetic res...
Magnetic Resonance Imaging Case-Control Studies Multivariate Analysis Diagnosis, Computer-Assisted Bayes Theorem Humans Cognitive Dysfunction Alzheimer Disease Machine Learning Diagnostic Techniques, Neurological Support Vector Machine Brain
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