Journal of Medical Internet Research

Supervised Machine Learning Models for Predicting Sepsis-Associated Liver Injury in Patients With Sepsis: Development and Validation Study Based on a Multicenter Cohort Study

Nine machine learning models—decision tree, random forest (RF), extreme gradient boosting (XGBoost), light gradient boosting machine (LightGBM), support vector machine, elastic net, logistic ...
IEEE

Forecasting Obesity and Customized Nutrition Planning using KNN and Linear Regression Models for Higher Accuracy

Abstract: This study deals with the various contributors of obesity through the use of advanced ML algorithms are KNN and linear regression. These KNN and linear regression algorithms help to ...
IEEE

SFT: Few-Shot Learning via Self-Supervised Feature Fusion With Transformer

Abstract: The few-shot learning paradigm aims to generalize to unseen tasks with limited samples. However, a focus solely on class-level discrimination may fall short of achieving robust ...
GitHub

rasikasrimal/covid-19-data-analysis-using-python

This project provides a hands-on exploration of COVID19 data analysis techniques using Python. It covers data preparation, analysis, and visualization, aiming to understand correlations with happiness ...
GitHub

MP2CDLO: Self-supervised Learning of Reconstructing Deformable Linear Objects under Single-Frame Occluded View

Create conda environments and active it. conda create -n MP2CDLO python=3.9 conda activate MP2CDLO Install torch1.13.0+cu117. pip install torch==1.13.0+cu117 ...