IEEE

IMed-CNN: Ensemble Learning Approach With Systematic Model Dropout for Enhanced Medical Image Classification Using Image Channels and Pixel Intervals

Abstract: To obtain light ensemble model through clearly explained effective ensemble member selection and finding data representation in various valuable forms are major challenges in medical image ...
GitHub

A minimal, secure Python interpreter written in Rust for use by AI.

Experimental - This project is still in development, and not ready for the prime time. A minimal, secure Python interpreter written in Rust for use by AI. Monty avoids the cost, latency, complexity ...
news.gov.hk

Cultivating AI innovation on campus

Spearheaded by the Digital Policy Office, the IT Innovation Lab in Secondary Schools programme and the Knowing More About IT ...
dailyyonder.com

Research: Urban Hospitals Use a Dual-Classification Loophole to Exploit Aid Programs for Rural Hospitals

The Barnes-Jewish Hospital in St. Louis, Missouri. (AP Photo/Jeff Roberson) A recent study published in Health Affairs found that the incidents of dual classification have exploded over the past ...
IEEE

ITJP: Image and Text Joint Prompts for Few-Shot Whole Slide Image Classification

Multiple instance learning has achieved remarkable results in whole slide image (WSI) classification. However, constrained by patient privacy and the scarcity of cancer data, the insufficient quantity ...