Machine learning (ML) is one of the fastest-developing topics today, straddling boundary between statistics and computer science, as well data science. It a type artificial intelligence that allows software applications to become more accurate at predicting outcomes without being explicitly programmed. And addresses difficulty way assemble gadgets enhance themselves via experience, make conclus...

Epigenetic targets are of significant importance in drug discovery research, as demonstrated by the eight approved epigenetic drugs for treatment cancer and increasing availability chemogenomic data related to epigenetics. This represents many structure-activity relationships that have not been exploited thus far develop predictive models support medicinal chemistry efforts. Herein, we report f...

Air temperature is an essential climatic component particularly in water resources management and other agro-hydrological/meteorological activities planning This paper examines the prediction capability of three machine learning models, least square support vector (LSSVM), group method data handling neural network (GMDHNN) classification regression trees (CART) air forecasting using monthly Ast...

BACKGROUND As more and more researchers are turning to big data for new opportunities of biomedical discoveries, machine learning models, as the backbone of big data analysis, are mentioned more often in biomedical journals. However, owing to the inherent complexity of machine learning methods, they are prone to misuse. Because of the flexibility in specifying machine learning models, the resul...

Machine learning uses experimental data to optimize clustering or classification of samples or features, or to develop, augment or verify models that can be used to predict behavior or properties of systems. It is expected that machine learning will help provide actionable knowledge from a variety of big data including metabolomics data, as well as results of metabolism models. A variety of mac...

Millions of people throughout the world suffer with Parkinson's disease (PD), severely reducing their quality life. With symptoms when we detect Parkinson automatically, it could provide insights to disease's early stages development, enhancing patients' projected clinical results through correctly focused therapies. This potential has prompted numerous academics explore ways for measuring and ...