Abstract: In this paper, a hybrid PCA-based approach is proposed for predicting the respiratory imbalance in an urban health monitoring system. To do this, three models namely Random Forest, XGBoost, ...

AI is the broad goal of creating intelligent systems, no matter what technique is used. In comparison, Machine Learning is a specific technique to train intelligent systems by teaching models to learn ...

In some ways, Java was the key language for machine learning and AI before Python stole its crown. Important pieces of the data science ecosystem, like Apache Spark, started out in the Java universe.

Machine learning, a key enabler of artificial intelligence, is increasingly used for applications like self-driving cars, medical devices, and advanced robots that work near humans — all contexts ...

School of Artificial Intelligence and Data Science, Unversity of Science and Technology of China, Hefei 230026, P. R. China Suzhou Institute for Advanced Research, University of Science and Technology ...

The Perspective by Tiwary et al. (8) offers a comprehensive overview of generative AI methods in computational chemistry. Approaches that generate new outputs (e.g., inferring phase transitions) by ...

What if the programming language you rely on most is on the brink of a transformation? For millions of developers worldwide, Python is not just a tool, it’s a cornerstone of their craft, powering ...

Introduction: Stroke remains one of the leading causes of global mortality and long-term disability, driving the urgent need for accurate and early risk prediction tools. Traditional models such as ...

Systems that can learn interactively from their end-users are quickly becoming widespread. Until recently, this progress has been fueled mostly by advances in machine learning; however, more and more ...

Objective: This study aims to develop and validate a machine learning model that integrates dietary antioxidants to predict cardiovascular disease (CVD) risk in diabetic patients. By analyzing the ...