Devdiscourse

AI models face real-world reality check in 6G network slicing

One of the key findings is that raw accuracy in laboratory conditions does not guarantee stability in deployment. The study ...
RMD Open

Systemic lupus erythematosus damage risk index (SLE-DRI): a simple machine learning-based tool for identifying patients at risk for early organ damage

Objective Organ damage is a key determinant of poor prognosis and increased mortality in systemic lupus erythematosus (SLE).
BMJ Global Health

The Ethiopian Surgical Outcome Study (Ethio-SOS): a 7-day multicentre national prospective observational cohort study

Introduction Safe surgical care is a cost-effective intervention for addressing a wide range of conditions, yet postoperative ...
IEEE

A Web-based Proctoring System using PHP-MySQL and Logistic Regression for Student Classification

Abstract: The Proctor plays the role and responsibility of 'Friend, Philosopher and Guide' in nurturing the student for their overall academics. It is a common practice to pair a student with a ...
IEEE

A Comparative Study of Logistic Regression, Support Vector Machines, and LSTM Networks for Sentiment Classification in Academic Reviews

Abstract: In recent years, sentiment analysis has become an important tool for understanding what people think and feel about different topics, especially in education. This study looks at how well ...
Frontiers

Evaluating machine learning models for stroke prediction based on clinical variables

Introduction: Stroke remains one of the leading causes of global mortality and long-term disability, driving the urgent need for accurate and early risk prediction tools. Traditional models such as ...
SciELO

Obesity classification: a comparative study of machine learning models excluding weight and height data

OBJECTIVE: Obesity is a global health problem. The aim is to analyze the effectiveness of machine learning models in predicting obesity classes and to determine which model performs best in obesity ...