AI Medical Compendium Topic

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Models, Statistical

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Statistical models versus machine learning for competing risks: development and validation of prognostic models.

BMC medical research methodology
BACKGROUND: In health research, several chronic diseases are susceptible to competing risks (CRs). Initially, statistical models (SM) were developed to estimate the cumulative incidence of an event in the presence of CRs. As recently there is a growi...

Comprehensive AI-assisted tool for ankylosing spondylitis based on multicenter research outperforms human experts.

Frontiers in public health
INTRODUCTION: The diagnosis and treatment of ankylosing spondylitis (AS) is a difficult task, especially in less developed countries without access to experts. To address this issue, a comprehensive artificial intelligence (AI) tool was created to he...

Forecasting the United State Dollar(USD)/Bangladeshi Taka (BDT) exchange rate with deep learning models: Inclusion of macroeconomic factors influencing the currency exchange rates.

PloS one
Forecasting a currency exchange rate is one of the most challenging tasks nowadays. Due to government monetary policy and some uncertain factors, such as political stability, it becomes difficult to correctly forecast the currency exchange rate. Prev...

Socioexposomics of COVID-19 across New Jersey: a comparison of geostatistical and machine learning approaches.

Journal of exposure science & environmental epidemiology
BACKGROUND: Disparities in adverse COVID-19 health outcomes have been associated with multiple social and environmental stressors. However, research is needed to evaluate the consistency and efficiency of methods for studying these associations at lo...

Long-term care insurance purchase decisions of registered nurses: Deep learning versus logistic regression models.

Health policy (Amsterdam, Netherlands)
OBJECTIVE: The purpose of this study was to use a deep learning model and a traditional statistical regression model to predict the long-term care insurance decisions of registered nurses.

Comparison of Artificial Neural Network and Polynomial Approximation Models for Reflectance Spectra Reconstruction.

Sensors (Basel, Switzerland)
Knowledge of surface reflection of an object is essential in many technological fields, including graphics and cultural heritage. Compared to direct multi- or hyper-spectral capturing approaches, commercial RGB cameras allow for a high resolution and...

Machine learning enabled subgroup analysis with real-world data to inform clinical trial eligibility criteria design.

Scientific reports
Overly restrictive eligibility criteria for clinical trials may limit the generalizability of the trial results to their target real-world patient populations. We developed a novel machine learning approach using large collections of real-world data ...

A Survey on Shape-Constraint Deep Learning for Medical Image Segmentation.

IEEE reviews in biomedical engineering
Since the advent of U-Net, fully convolutional deep neural networks and its many variants have completely changed the modern landscape of deep-learning based medical image segmentation. However, the over-dependence of these methods on pixel-level cla...

Statistical approaches to identifying significant differences in predictive performance between machine learning and classical statistical models for survival data.

PloS one
Research that seeks to compare two predictive models requires a thorough statistical approach to draw valid inferences about comparisons between the performance of the two models. Researchers present estimates of model performance with little evidenc...

Forecasting blood demand for different blood groups in Shiraz using auto regressive integrated moving average (ARIMA) and artificial neural network (ANN) and a hybrid approaches.

Scientific reports
Providing fresh blood to keep people in need of blood alive, has always been a main issues of health systems. Right policy-making in this area requires accurate forecasting of blood demand. The current study aimed at predicting demand for different b...