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Evaluating Machine Learning and Deep Learning models for predicting Wind Turbine power output from environmental factors.
PLoS One
January 2025
Renewable Energy Science and Engineering Department, Faculty of Postgraduate Studies for Advanced Sciences (PSAS), Beni-Suef University, Beni-Suef, Egypt.
This study presents a comprehensive comparative analysis of Machine Learning (ML) and Deep Learning (DL) models for predicting Wind Turbine (WT) power output based on environmental variables such as temperature, humidity, wind speed, and wind direction. Along with Artificial Neural Network (ANN), Long Short-Term Memory (LSTM), Recurrent Neural Network (RNN), and Convolutional Neural Network (CNN), the following ML models were looked at: Linear Regression (LR), Support Vector Regressor (SVR), Random Forest (RF), Extra Trees (ET), Adaptive Boosting (AdaBoost), Categorical Boosting (CatBoost), Extreme Gradient Boosting (XGBoost), and Light Gradient Boosting Machine (LightGBM). Using a dataset of 40,000 observations, the models were assessed based on R-squared, Mean Absolute Error (MAE), and Root Mean Square Error (RMSE).
View Article and Find Full Text PDFEvaluation of racial/ethnic disparities in surgical outcomes after rectal cancer resection: An ACS-NSQIP analysis.
Surg Pract Sci
June 2024
Division of Colorectal Surgery, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.
Background: Disparities exist the management of rectal cancer. We sought to evaluate short-term surgical outcomes among different racial/ethnic groups following rectal cancer resection.
Materials And Methods: National Surgical Quality Improvement Program (NSQIP) database (2016-2019) was queried.
Association between serum levels of 12 different cytokines and short-term efficacy of chemoradiotherapy in esophageal squamous cell carcinoma.
Discov Oncol
January 2025
Clinical Oncology Laboratory, Changzhou Tumor Hospital, Changzhou, 213002, Jiangsu, China.
Background: Esophageal squamous cell carcinoma (ESCC) has a poor prognosis, with chemoradiotherapy (CRT) being a key treatment method. This study focused on circulating cytokines as potential predictors of treatment response and prognosis in patients with ESCC.
Materials And Methods: Serum samples were collected from 36 ESCC patients, and 12 different cytokines were quantified using a multiplex immunofluorescence assay.
Association of the blood urea nitrogen to serum albumin ratio and all-cause mortality in critical ill acute ischemic stroke patients: a retrospective cohort study of MIMIC-IV database 3.0.
Front Nutr
January 2025
Department of Immunology, Mianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of China (UESTC), Mianyang, Sichuan, China.
Purpose: We aim to ascertain the extent to which the blood urea nitrogen (BUN) to serum albumin (ALB) ratio (BAR) could be implemented to anticipate the short- and long-term prognosis of acute ischemic stroke (AIS) patients in intensive care units (ICUs).
Methods: The data was derived from the Marketplace for Intensive Care Medical Information-IV (MIMIC-IV v3.0) database, primarily pertaining to AIS patients as categorized by the International Classification of Diseases (ICD)-9 and ICD-10.
Diabetes disparities in diabetes health care access and outcomes during the Covid-19 Pandemic in the United States.
Expert Rev Pharmacoecon Outcomes Res
January 2025
Department of Clinical Pharmacy, University of California San Francisco, San Francisco, CA, USA.
Objectives: To investigate the impact of COVID-19 on hospitalization and consequent diabetes-related complications in patients with type 2 diabetes mellitus (diabetes).
Methods: We conducted a retrospective cohort study of patients with diabetes. Interrupted time series analysis (ITS) was used to analyze the monthly trends in diabetes-related hospitalization rates, including short- and long-term complications, 1-year before and after onset of COVID-19.
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