Introduction Application of artificial intelligence (AI) tools in the healthcare setting gains importance especially in the domain of disease diagnosis. Numerous studies have tried to explore AI in ...

Implement Logistic Regression in Python from Scratch ! In this video, we will implement Logistic Regression in Python from Scratch. We will not use any build in models, but we will understand the code ...

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 ...

The rapid uptake of supervised machine learning (ML) in clinical prediction modelling, particularly for binary outcomes based on tabular data, has sparked debate about its comparative advantage over ...

Developed an end-to-end customer churn prediction ML pipeline using Python, pandas, and scikit-learn. Implemented and trained a logistic regression model, then deployed it as a REST API service using ...

Abstract: This paper's primary goal is to use machine learning techniques, specifically Logistic Regression and Decision Trees, to identify bogus news on social media. An innovative logistic model is ...

1 Clinical Laboratory, Dongyang People’s Hospital, Dongyang, Zhejiang, China 2 Clinical Laboratory, The Second People’s Hospital of Yuhuan City, Yuhuan, Zhejiang, China Introduction: In this study, we ...

Department of Mathematics, Statistics and Actuarial Science, Faculty of Health, Natural Resources and Applied Sciences, Namibia University of Science and Technology, Windhoek, Namibia. Food insecurity ...

Objective: There is limited study on predictive models for live births in patients with polycystic ovarian syndrome (PCOS). The study aimed to develop and validate a nomogram for predicting live ...