Which Machine Learning Models Are Most Used In Crypto Signal Generation?

Machine learning is transforming how crypto traders create and understand signals. From supervised models such as Random Forests and Gradient Boosting Machines to sophisticated deep learning hybrids ...
Frontiers

Machine learning-based prediction of hypoglycemia severity in hospitalized diabetic patients

Department of General Practice, The Affiliated Hospital of Qingdao University, Qingdao, China Objective: To identify risk factors for hypoglycemia in hospitalized patients with type 2 diabetes ...
Scientific Research Publishing

Joshi, R.D. and Dhakal, C.K. (2021) Predicting Type 2 Diabetes Using Logistic Regression and Machine Learning Approaches. International Journal of Environmental Research and ...

ABSTRACT: This paper aims to investigate the effectiveness of logistic regression and discriminant analysis in predicting diabetes in patients using a diabetes dataset. Additionally, the paper ...
Frontiers

Exploring the association between vitamin D levels and dyslipidemia risk: insights from machine learning and generalized additive models

Introduction: Vitamin D is a necessary nutrient that is important for calcium homeostasis and bone health. Dyslipidemia is thought to be a risk factor for the development of atherosclerotic illnesses.
Live Science

Scientists use quantum machine learning to create semiconductors for the first time – and it could transform how chips are made

Quantum machine learning is a hybrid approach that combines classical data with quantum computing methods. In classical computing, data is stored in bits encoded as a 0 or 1. Quantum computers use ...
IEEE

Machine Learning–Based Hypertension Risk Stratification Using Logistic Regression and XGBoost

Abstract: Hypertension is a critical global health concern, necessitating accurate prediction models and effective prescription decisions to mitigate its risks. This study proposes a hybrid machine ...
Hosted on MSN

Logistic Regression Machine Learning Example ¦ Simply Explained

Logistic Regression is a widely used model in Machine Learning. It is used in binary classification, where output variable can only take binary values. Some real world examples where Logistic ...
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 ...