AIMC Topic: Models, Statistical

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Don't Let Your Analysis Go to Seed: On the Impact of Random Seed on Machine Learning-based Causal Inference.

Epidemiology (Cambridge, Mass.) Aug 16, 2024
Machine learning techniques for causal effect estimation can enhance the reliability of epidemiologic analyses, reducing their dependence on correct model specifications. However, the stochastic nature of many machine learning algorithms implies that...
Reproducibility of Results Causality Models, Statistical Epidemiologic Methods Humans Machine Learning Algorithms Computer Simulation
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Comparison of machine learning and conventional statistical modeling for predicting readmission following acute heart failure hospitalization.

American heart journal Jul 31, 2024
INTRODUCTION: Developing accurate models for predicting the risk of 30-day readmission is a major healthcare interest. Evidence suggests that models developed using machine learning (ML) may have better discrimination than conventional statistical mo...
Male Middle Aged Risk Assessment Ontario Models, Statistical Acute Disease Heart Failure Female Patient Readmission Hospitalization Aged Aged, 80 and over Humans Machine Learning Retrospective Studies
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Development and Validation of an Explainable Machine Learning Model for Identification of Hyper-Functioning Parathyroid Glands from High-Frequency Ultrasonographic Images.

Ultrasound in medicine & biology Jul 25, 2024
OBJECTIVE: To develop and validate a machine learning (ML) model based on high-frequency ultrasound (HFUS) images with the aim to identify the functional status of parathyroid glands (PTGs) in secondary hyper-parathyroidism (SHPT) patients.
Adult Male Middle Aged Ultrasonography Humans Machine Learning Computer Simulation Female Tomography, Emission-Computed, Single-Photon Parathyroid Diseases Models, Statistical Predictive Value of Tests Random Forest Parathyroid Glands
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Development and validation of radiology-clinical statistical and machine learning model for stroke-associated pneumonia after first intracerebral haemorrhage.

BMC pulmonary medicine Jul 24, 2024
BACKGROUND: Society is burdened with stroke-associated pneumonia (SAP) after intracerebral haemorrhage (ICH). Cerebral small vessel disease (CSVD) complicates clinical manifestations of stroke. In this study, we redefined the CSVD burden score and in...
Middle Aged Logistic Models Models, Statistical Cerebral Hemorrhage Pneumonia Stroke Cerebral Small Vessel Diseases Risk Factors Aged Aged, 80 and over Male Humans Retrospective Studies Machine Learning Tomography, X-Ray Computed Female
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Outcome risk model development for heterogeneity of treatment effect analyses: a comparison of non-parametric machine learning methods and semi-parametric statistical methods.

BMC medical research methodology Jul 23, 2024
BACKGROUND: In randomized clinical trials, treatment effects may vary, and this possibility is referred to as heterogeneity of treatment effect (HTE). One way to quantify HTE is to partition participants into subgroups based on individual's risk of e...
Humans Decision Trees Randomized Controlled Trials as Topic Risk Assessment Outcome Assessment, Health Care United States Aspirin Treatment Outcome Proportional Hazards Models Models, Statistical Machine Learning Female Aged Male
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A systematic literature review of predicting patient discharges using statistical methods and machine learning.

Health care management science Jul 22, 2024
Discharge planning is integral to patient flow as delays can lead to hospital-wide congestion. Because a structured discharge plan can reduce hospital length of stay while enhancing patient satisfaction, this topic has caught the interest of many hea...
Patient Discharge Length of Stay Time Factors Models, Statistical Humans Machine Learning Forecasting
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Analyzing speed-difference impact on freeway joint injury severities of Leading-Following vehicles using statistical and data-driven models.

Accident; analysis and prevention Jul 6, 2024
Rear-end (RE) crashes are notably prevalent and pose a substantial risk on freeways. This paper explores the correlation between speed difference among the following and leading vehicles (Δν) and RE crash risk. Three joint models, comprising both unc...
Models, Statistical Accidents, Traffic Humans Wounds and Injuries Neural Networks, Computer Trauma Severity Indices Support Vector Machine
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Exploring spatial heterogeneity in factors associated with injury severity in speeding-related crashes: An integrated machine learning and spatial modeling approach.

Accident; analysis and prevention Jul 4, 2024
Speeding, a risky act of driving a vehicle at a speed exceeding the posted limit, has consistently emerged as a leading contributor to traffic fatalities. Identifying the risk factors associated with injury severity in speeding-related crashes is ess...
Humans Machine Learning Female Risk Factors Adult Male Middle Aged Models, Statistical Accidents, Traffic Automobile Driving Spatial Analysis Wounds and Injuries
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A hybrid Machine learning and statistical modeling approach for analyzing the crash severity of mobility scooter users considering temporal instability.

Accident; analysis and prevention Jul 3, 2024
One of the main objectives in improving the quality of life for individuals with disabilities, especially those experiencing mobility issues such as the elderly, is to enhance their day-to-day mobility. Enabling easy mobility contributes to their ind...
Aged Adult Male Middle Aged Humans Machine Learning COVID-19 Female Persons with Disabilities Models, Statistical Accidents, Traffic United Kingdom
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Discovery of urinary biosignatures for tuberculosis and nontuberculous mycobacteria classification using metabolomics and machine learning.

Scientific reports Jul 3, 2024
Nontuberculous mycobacteria (NTM) infection diagnosis remains a challenge due to its overlapping clinical symptoms with tuberculosis (TB), leading to inappropriate treatment. Herein, we employed noninvasive metabolic phenotyping coupled with comprehe...
Tuberculosis Humans Mycobacterium Infections, Nontuberculous Machine Learning Down-Regulation Phenotype Up-Regulation Biomarkers Diagnosis, Differential Area Under Curve Amino Acids Random Forest Metabolomics Models, Statistical Liquid Chromatography-Mass Spectrometry Metabolome Aged Male Middle Aged ROC Curve
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