Background: By 2050, the global population of individuals aged 60 years and older is projected to reach two billion, with 80% residing in low- and middle-income countries (LMICs). Africa’s older ...

WS/ ├── cancer_diagnosis.py # Main backend analysis and model training ├── app.py # Streamlit frontend application ├── launch.bat # Windows launcher script ├── launch.sh # Linux/Mac launcher script ...

Neurointervention is a highly specialized area of medicine and, as such, neurointerventional research studies are often more challenging to conduct, require large, multicenter efforts and longer study ...

Abstract: Ordinal regression (OR, also called ordinal classification) is classification of ordinal data, in which the underlying target variable is categorical and considered to have a natural ordinal ...

The recent release of the rcssci R package represents a significant advancement in the way researchers visualize and analyze complex relationships between continuous variables and their outcomes. The ...

ABSTRACT: Food insecurity is a global issue, and households in a society can experience food insecurity at different levels that could range from being mildly food insecure to severely food insecure.

ABSTRACT: Ordinal outcome neural networks represent an innovative and robust methodology for analyzing high-dimensional health data characterized by ordinal outcomes. This study offers a comparative ...

In this project, we leverage the power of artificial intelligence in healthcare to predict lung cancer risks. By employing various machine learning techniques, we aim to assist medical professionals ...