Prediction of Long-Term Stroke Recurrence Using Machine Learning Models
نویسندگان
چکیده
منابع مشابه
Cancer Recurrence Prediction Using Machine Learning
Cancer is one of the deadliest diseases in the world and is responsible for around 13% of all deaths worldwide. Cancer incidence rate is growing at an alarming rate in the world. Despite the fact that cancer is preventable and curable in early stages, the vast majority of patients are diagnosed with cancer very late. Furthermore, cancer commonly comes back after years of treatment. Therefore, i...
متن کاملThermal conductivity of Water-based nanofluids: Prediction and comparison of models using machine learning
Statistical methods, and especially machine learning, have been increasingly used in nanofluid modeling. This paper presents some of the interesting and applicable methods for thermal conductivity prediction and compares them with each other according to results and errors that are defined. The thermal conductivity of nanofluids increases with the volume fraction and temperature. Machine learni...
متن کاملThermal conductivity of Water-based nanofluids: Prediction and comparison of models using machine learning
Statistical methods, and especially machine learning, have been increasingly used in nanofluid modeling. This paper presents some of the interesting and applicable methods for thermal conductivity prediction and compares them with each other according to results and errors that are defined. The thermal conductivity of nanofluids increases with the volume fraction and temperature. Machine learni...
متن کاملBreast Cancer Diagnosis and Recurrence Prediction Using Machine Learning Techniques
Breast Cancer has become the common cause of death among women. Due to long hours invested in manual diagnosis and lesser diagnostic system available emphasize the development of automated diagnosis for early diagnosis of the disease. Our aim is to classify whether the breast cancer is benign or malignant and predict the recurrence and non-recurrence of malignant cases after a certain period. T...
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 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: Journal of Clinical Medicine
سال: 2021
ISSN: 2077-0383
DOI: 10.3390/jcm10061286