TMCnet

Data Normalization vs. Standardization: What's the Difference and When to Use Each

Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and data preprocessing. If you''ve ever built a predictive model, worked on a ...
Harvard Business Review

When Every Company Can Use the Same AI Models, Context Becomes a Competitive Advantage

When everyone has access to the same AI models, the same AI-enabled tools, and the same vendor ecosystem, organizational context becomes the differentiator. Context is demonstrated execution: the ...
AHA/ASA Journals

Multistage Electrocardiographic Profiling for Mental Stress-Induced Myocardial Ischemia in Women: A Prospective, Age-Matched Cohort Study in China

BACKGROUND: Mental stress-induced myocardial ischemia is often clinically silent and associated with increased cardiovascular risk, particularly in women. Conventional ECG-based detection is limited, ...
GitHub

TfELM : Extreme Learning Machines Framework with Python and TensorFlow

This framework provides a comprehensive set of tools and utilities for implementing and experimenting with Extreme Learning Machines using Python and TensorFlow. ELMs are a type of machine learning ...
The Lancet

When to and when not to use machine learning in risk prediction models

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...
North Penn Now

Machine Learning Using Python: A Complete Learning Path With Practical Projects

Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...
Oncology Nurse Advisor

Machine Learning Predicts Postembolization Fever After TACE

Researchers sought to determine an effective approach to predict postembolization fever in patients undergoing TACE.
IEEE

The Impact of Feature Scaling in Machine Learning: Effects on Regression and Classification Tasks

Abstract: This study addresses the lack of comprehensive evaluations of feature scaling by systematically assessing 12 techniques, including less common methods such as VAST and Pareto, in 14 machine ...
Scientific Research Publishing

Heart Disease Prediction: A Logistic Regression Approach ()

1 School of Computing and Data Science, Wentworth Institute of Technology, Boston, USA. 2 Department of Computer Science and Quantitative Methods, Austin Peay State University, Clarksville, USA. 3 ...
InfoWorld

AI and machine learning outside of Python

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.
tech2geek

Scikit-learn: The Essential Machine Learning Library for Python

If you’re learning machine learning with Python, chances are you’ll come across Scikit-learn. Often described as “Machine Learning in Python,” Scikit-learn is one of the most widely used open-source ...
BMJ

Accuracy of machine learning methods in predicting prognosis of patients with psychotic spectrum disorders: a systematic review

3 Alice Lee Centre for Nursing Studies, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 4 Yong Loo Lin School of Medicine, National University of Singapore, Singapore 5 ...