The Lancet

Development and validation of a generalisable machine learning algorithm for identifying interstitial lung disease cohorts: a retrospective cohort study

aDepartment of Medicine, University of California San Francisco, San Francisco, CA, USA bDepartment of Medicine, University of California Los Angeles, Los Angeles, CA, USA cDepartment of Medicine, ...
IEEE

Learn From Examples: In-Context Learning for Camouflaged Object Detection

Abstract: Recently, new paradigms of camouflaged object detection (COD), such as referring COD (Ref-COD) and collaborative COD (Co-COD), have been proposed to enhance task performance. However, there ...
Journal of Medical Internet Research

Prediction of Moderate-to-Severe Sepsis-Associated Acute Kidney Injury Using a Dual-Timepoint Machine Learning Model: Development, Multiregional Validation, and Clinical ...

Based on clinical data from the first 24 hours of ICU admission, we used a two-stage feature selection process combining light gradient boosting machine (LightGBM) and Shapley additive explanation ...
GitHub

pkumari78311-collab/AI_Drone_Vision_System

This project was developed collaboratively by Priya Kumari and Nripendra Kumar as part of an Artificial Intelligence, Computer Vision, and Autonomous Systems learning initiative.
IEEE

Anomaly Detection in Cybersecurity using Machine Learning Classifiers

Abstract: This research examines anomaly detection in cybersecurity by utilizing various machine learning classifiers, including Naive Bayes, Artificial Neural Network (ANN), Support Vector Machine ...