LONG-TERM PREDICTION OF DEMENTIA USING MACHINE LEARNING ALGORITHMS
نویسندگان
چکیده
Abstract The core interest of this project is the development predictive estimates and identification modifiable risk factors for neurocognitive disorders based on multifactorial data from multiple health databases.We are conducting epidemiological research predicting diseases older adults included in National E-Infrastructure Aging Research (NEAR) using deep learning other AI methods. Exploring impact lifestyle environment dementia subjects together with biomarkers images machine techniques would give insights into long-term development. In addition, possibility screening a large number persons consequent early prediction optimized could be great importance treatment.
منابع مشابه
Dynamic Branch Prediction using Machine Learning Algorithms
Machine Learning algorithms have long been used to develop classifiers which learn patterns among the data for grouping them into classes. Using such algorithms for exploiting finer structure in the data seems to be a good way to address the problem of Dynamic branch prediction (DBP). However, not all conventional algorithms in machine learning can be directly applied to DBP, since they usually...
متن کاملmachine learning for predictive management: short and long term prediction of phytoplankton biomass using genetic algorithm based recurrent neural networks
in the regulated nakdong river, algal proliferations are annually observed in some seasons, with cyanobacteria (microcystis aeruginosa) appearing in summer and diatom blooms (stephanodiscus hantzschii) in winter. this study aims to develop two ecological models forecasting future chlorophyll a at two time-steps (one-week and one-year forecasts), using recurrent neural networks tuned by genetic...
متن کاملPrediction of brain maturity in infants using machine-learning algorithms
Recent resting-state functional MRI investigations have demonstrated that much of the large-scale functional network architecture supporting motor, sensory and cognitive functions in older pediatric and adult populations is present in term- and prematurely-born infants. Application of new analytical approaches can help translate the improved understanding of early functional connectivity provid...
متن کاملMachine learning algorithms in air quality modeling
Modern studies in the field of environment science and engineering show that deterministic models struggle to capture the relationship between the concentration of atmospheric pollutants and their emission sources. The recent advances in statistical modeling based on machine learning approaches have emerged as solution to tackle these issues. It is a fact that, input variable type largely affec...
متن کاملStock Price Prediction using Machine Learning and Swarm Intelligence
Background and Objectives: Stock price prediction has become one of the interesting and also challenging topics for researchers in the past few years. Due to the non-linear nature of the time-series data of the stock prices, mathematical modeling approaches usually fail to yield acceptable results. Therefore, machine learning methods can be a promising solution to this problem. Methods: In this...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Innovation in Aging
سال: 2022
ISSN: ['2399-5300']
DOI: https://doi.org/10.1093/geroni/igac059.967