Open Heart

Machine learning-based cardiovascular risk calculator for non-cardiac surgery

Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...
Frontiers

Development and validation of machine learning-based diagnostic models using blood transcriptomics for early childhood diabetes prediction

Background: Early identification of Type 1 Diabetes Mellitus (T1DM) in pediatric populations is crucial for implementing timely interventions and improving long-term outcomes. Peripheral blood ...
GitHub

boosting-classifier-gradient-boosting

Ensemble Techniques: Analyze the data of Visa applicants, build a predictive model to facilitate the process of visa approvals, and based on important factors that significantly influence the Visa ...
Scientific Research Publishing

Utubor, S. (2023) Improving Detection of Attacks in Cyber-Physical Systems: Applying Gradient Boosting Based Machine Learning Techniques. Ph.D. Thesis, The George Washington ...

ABSTRACT: The advent of the internet, as we all know, has brought about a significant change in human interaction and business operations around the world; yet, this evolution has also been marked by ...
Frontiers

Optimizing predictive features using machine learning for early miscarriage risk following single vitrified-warmed blastocyst transfer

1 Guangxi Reproductive Medical Center, The First Affiliated Hospital of Guangxi Medical University, Nanning, China 2 Reproductive Center, Nanning Maternity and Child Health Hospital, Nanning, Guangxi, ...
Scientific Research Publishing

Kalusivalingam, A.K., Sharma, A., Patel, N. and Singh, V. (2012) Enhancing Hospital Readmission Rate Predictions Using Random Forest and Gradient Boosting Algorithms ...

ABSTRACT: Accurate prediction of treatment response in bipolar disorder patients with comorbid obsessive-compulsive disorder (OCD) is essential to improving clinical outcomes and minimizing ...
IEEE

Gradient Boosting Feature Selection with Machine Learning Classifier for Prediction of Intrusion Image

Abstract: The novel approach to intrusion image prediction explained in this paper uses both Gradient Boosting Feature Selection and Machine Learning Classifiers. Detection of intruders in images is a ...