Popular GitHub Repositories for Invasive Ductal Carcinoma

Fast, minimally-invasive neural network inference library

The Invasive Ductal Carcinoma (IDC) Detection System is an open source computer vision program created to classify IDC positive and negative samples. This project is a complete system including a locally hosted webserver / UI / API allowing you to manage your pipeline.

Self-Supervised Vision Transformers for Breast Histopathology Image Embeddings in Invasive Ductal Carcinoma Detection

open-source kit that brings professional-grade ultrasound imaging to your fingertips for under $200. Designed for non-invasive monitoring of mushroom (mycelium) growth, FungiVue empowers educators to inspire students with hands-on STEM projects, researchers to uncover intricate growth patterns with real-time data, and hobbyists to experiment in bio

?? Pandas Checks: Non-invasive health checks for Pandas method chains

SYNAPTICON is a research prototype at the intersection of neuro-hacking, non-invasive BCIs, and foundational models, probing new territories of human expression, aesthetics, and AI alignment. At its core lies a live "BrainWaves-to-NaturalLanguage-to-Aesthetics" system integrating EEG decoding with LLMs and Transformers.

A tool to streamline the identification process of invasive and non-native species in the Florida area.

This article introduces artificial neural networks as a computational tool to utilize legacy archaeological data for precisely and accurately estimating dates of residential site occupation. The implementation of this deep learning algorithm can provide high-resolution demographic reconstructions of a study area from non-collection, non-invasive, and non-destructive data collection methods that only record frequencies of artifact types on the contemporary ground surface. The utility of this deep learning algorithm is presented through an example from the central Mesa Verde region in the northern US Southwest. Results show a properly trained artificial neural network predicts annual residential occupation with an average 93.5% accuracy from AD 450–1300. An annual demographic reconstruction of the central Mesa Verde region is also presented

A scalable and non-invasive speech-based machine learning model for early Alzheimer's detection using mel-spectrograms and lightweight semi-supervised CNN with no transcription or neuroimaging needed.

Revolutionizing Kidney Cancer Detection: Harnessing AI to Predict Renal Cell Carcinoma.

River: an AI Environmental Expert. A RAG-based chatbot application designed to assist a Regional Council with data, documentation, and reporting regarding invasive species management. The application features integration with Slack and leverages tools from LangChain, OpenAI, Pinecone, and Azure Blob Storage.

This repository provides a basic implementation for detecting IDC (Invasive Ductal Carcinoma) in histopathology images using the YOLO11 (You Only Look Once) object detection algorithm.

Retinal Optical Coherence Tomography (OCT) is a non-invasive imaging technique used to capture high-resolution cross-sections of the retina. With over 30 million OCT scans performed annually, efficient analysis is critical for timely diagnosis.

A scalable and non-invasive speech-based machine learning model for early Alzheimer's detection using mel-spectrograms and lightweight semi-supervised CNN with no transcription or neuroimaging needed.