Open Heart

Development and validation of a deep learning model for severe mitral stenosis detection from chest X-rays

Background Although chest X-rays (CXRs) are widely used, diagnosing mitral stenosis (MS) based solely on CXR findings remains ...

What is the Difference Between Deep Learning and Machine Learning

We have explained the difference between Deep Learning and Machine Learning in simple language with practical use cases.
IEEE

A Novel Thermal Image-Based Metal Classification System Using Machine Learning Algorithms

Abstract: Classifying metals is an essential task in all industries to make sure the materials used in the processes are safe and meet the required standards all while enhancing operational and cost ...
Frontiers

Comparative analysis of machine learning techniques on the BraTS dataset for brain tumor classification

1 Information Statistics Center, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China 2 School of Computer Science and Technology, Hubei Business ...
IEEE

Machine Learning Framework for Industrial Machine Sound Classification in Predictive Maintenance

Abstract: Predictive maintenance, utilising anomalous sound classification, demonstrates a strong potential to identify mechanical faults in industrial machinery. This research proposes a machine ...
Frontiers

Migraine triggers, phases, and classification using machine learning models

1 San Juan Bautista School of Medicine, Caguas, Puerto Rico, United States 2 Independent Researcher, Monmouth County, NJ, United States Background: In many countries, patients with headache disorders ...
TechRepublic

20+ Machine Learning Methods in Groundbreaking Periodic Table From MIT, Google, Microsoft

20+ Machine Learning Methods in Groundbreaking Periodic Table From MIT, Google, Microsoft Your email has been sent A new “periodic table for machine learning” is reshaping how researchers explore AI, ...
C&EN

Addressing Imbalanced Classification Problems in Drug Discovery and Development Using Random Forest, Support Vector Machine, AutoGluon-Tabular, and H2O AutoML

The classification models built on class imbalanced data sets tend to prioritize the accuracy of the majority class, and thus, the minority class generally has a higher misclassification rate.
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 ...
Scientific Research Publishing

Research on Fault Detection and Classification of Industrial Equipment Based on Machine Learning ()

In the context of the rapid development of intelligent manufacturing, the stable operation of mechanical equipment is crucial for maintaining industrial production continuity and achieving economic ...