The American Journal of Managed Care

AI Model Accurately Predicts PH Risk in Patients With CKD

A machine learning model using basic clinical data can predict PH risk, identifying key predictors like low hemoglobin and elevated NT-proBNP. Researchers have developed a machine learning model that ...

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 ...
Scientific Research Publishing

Estimating Average and Heterogeneous Effects of Special Education: A Causal Machine Learning Perspective ()

Causal Machine Learning (CML) unites ML techniques with CI in order to take advantage of both approaches’ strengths. CML ...
The American Journal of Managed Care

Novel Machine Learning Model Improves MASLD Detection in Type 2 Diabetes

A machine learning–driven web tool based on 13 standard patient metrics demonstrates strong predictive performance for MASLD, ...
CBSSports.com

Seahawks vs. Cardinals NFL player props: Self-learning AI backs Sam Darnold Over 217.5 passing yards on TNF

A pair of 2-1 divisional rivals will face off on Thursday Night Football as the Arizona Cardinals host the Seattle Seahawks. Both Kyler Murray and Sam Darnold figure to factor into NFL prop bets, as ...
C&EN

Machine-Learning-Assisted Discovery of Cr

Department of Chemistry, University of Houston, Houston, Texas 77204, United States Texas Center for Superconductivity, University of Houston, Houston, Texas 77204, United States Department of ...
GitHub

machine-learning-algorithms-from-scratch

A collection of core Machine Learning algorithms implemented from scratch using only NumPy. This project focuses on understanding the inner workings of ML models without relying on libraries like ...
C&EN

Machine-Learning Potential Molecular Dynamics Reveals the Critical Role of Flexibility in Solid–Liquid Nanofluidic Friction

Shanghai Key Laboratory of Mechanics in Energy Engineering, Shanghai Institute of Applied Mathematics and Mechanics, School of Mechanics and Engineering Science, Shanghai University, Shanghai 200444, ...
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

Postpartum depression risk prediction using explainable machine learning algorithms

1 Department of Science and Education, Shenyang Maternity and Child Health Hospital, Shenyang, China 2 Department of Maternal, Child and Adolescent Health, School of Public Health, Shenyang Medical ...
GitHub

Pull requests: pratyaksh-sinha/multiple-disease-prediction-using-SVM-Logistic-Regression--Machine-Learning-Project

Pull requests help you collaborate on code with other people. As pull requests are created, they’ll appear here in a searchable and filterable list. To get started, you should create a pull request.