Results 211 to 220 of about 303,008 (292)

Predicting the severity of COVID-19 using machine learning methods. [PDF]

BMC Med Inform Decis Mak
Ezati M, Masroor B, Kahramfar Z, Najafi-Vosough R, Amiri F.   +4 more
europepmc   +1 more source

Electricity Price Prediction Using Multikernel Gaussian Process Regression Combined With Kernel‐Based Support Vector Regression

Journal of Forecasting, EarlyView.
ABSTRACT This paper presents a new hybrid model for predicting German electricity prices. The algorithm is based on a combination of Gaussian process regression (GPR) and support vector regression (SVR). Although GPR is a competent model for learning stochastic patterns within data and for interpolation, its performance for out‐of‐sample data is not ...
Abhinav Das, Stephan Schlüter, Lorenz Schneider   +2 more
wiley   +1 more source

Data Mining Strategies for Understanding Birth Patterns in Dairy Cattle: Single and Multiple Birth Analysis. [PDF]

Vet Med Sci
Ghaderi-Zefrehei M, Montazeri-Najafabadi M, Rafeie F, Esfahani EN, Soflaei MRAB, Kafi M, Banabazi MH.   +6 more
europepmc   +1 more source

Intraday Functional PCA Forecasting of Cryptocurrency Returns

Journal of Forecasting, EarlyView.
ABSTRACT We study the functional PCA (FPCA) forecasting method in application to functions of intraday returns on Bitcoin. We show that improved interval forecasts of future return functions are obtained when the conditional heteroscedasticity of return functions is taken into account.
Joann Jasiak, Cheng Zhong
wiley   +1 more source

Development and validation of a highly accurate multigene gene expression biomarker to predict chemotherapy response in primary triple-negative breast cancer. [PDF]

Breast Cancer Res Treat
Amniouel S, Jafri MS.
europepmc   +1 more source

Using DSGE and Machine Learning to Forecast Public Debt for France

Journal of Forecasting, EarlyView.
ABSTRACT Forecasting public debt is essential for effective policymaking and economic stability, yet traditional approaches face challenges due to data scarcity. While machine learning (ML) has demonstrated success in financial forecasting, its application to macroeconomic forecasting remains underexplored, hindered by short historical time series and ...
Emmanouil Sofianos, Thierry Betti, Theophilos Papadimitriou, Amélie Barbier‐Gauchard, Periklis Gogas   +4 more
wiley   +1 more source

Forecasting auditor's going concern opinion using with hybrid robust machine learning model. [PDF]

PLoS One
Ejder U, Yaşar A.
europepmc   +1 more source

Toxicological Evaluation of the Undesirable Components in Processed Infant Foods Using Artificial Intelligence

Future Postharvest and Food, EarlyView.
The detection of toxins in baby food using artificial intelligence. ABSTRACT Infant foods and baby formulas are becoming increasingly popular across the globe owing to their ease of consumption and nutritional value specific to infants. Impurities may find their way into the food chain at any point from the acquisition of raw materials to final ...
Poornima Singh, Anurag Singh, Ashutosh Upadhyay, Navneet Kumar   +3 more
wiley   +1 more source

A proof-of-concept machine learning model for short-term suicide risk stratification in depressed youth. [PDF]

Transl Psychiatry
Sun B, Zhang J, Ma Y, He H.
europepmc   +1 more source

The Global Patent Landscape of Mushroom‐Derived Functional Foods: Current Status, Future Perspectives, and Artificial Intelligence–Driven Exploration

Food Safety and Health, EarlyView.
The global patent landscape of mushroom‐derived functional food was widely analyzed, and AI‐integrated approaches realizing cost‐effective and reliable exploration of functional foods derived from mushrooms were explored. ABSTRACT Global health concerns and the increasing demand for nourishment have collectively driven the rising demand for functional ...
Xihong Zhao, Linhuizi Xiang, Dongmei Liu, Shoucheng Qin, Yue Chen, Xueyan Sun   +5 more
wiley   +1 more source