Popular GitHub Repositories for Diagnostic

Visual analysis and diagnostic tools to facilitate machine learning model selection.

this code library is mainly about applying graph neural networks to intelligent diagnostic and prognostic.

yc-360 Script is a lightweight diagnostic script that captures comprehensive troubleshooting artifacts (like Application logs, GC logs, thread dumps, heap dumps, OS-level metrics) from environments like Linux, Windows, Docker, Kubernetes, and OpenShift.

[ICMLSC 2018] On Breast Cancer Detection: An Application of Machine Learning Algorithms on the Wisconsin Diagnostic Dataset

RET-CLIP: A Retinal Image Foundation Model Pre-trained with Clinical Diagnostic Reports

Developed to assist in managing day-to-day operations of a mobile automotive diagnostic, and car key replacement business. This project integrates several technologies to improve hands-free interaction while driving. Automotive-AI can be customized for 2-way interaction with any available API services.

Extracting knowledge graphs from language models as a diagnostic benchmark of model performance (NeurIPS XAI 2021).

Code for IterInpaint model, presented in Diagnostic Benchmark and Iterative Inpainting for Layout-Guided Image Generation (CVPR 2024 workshop)

Diagnostic CLI tool for Python Azure Functions environment and configuration checks.

Insight & Inference for DVARS: 3-part variance decomposition, gives units & p-values to DVARS measures as well as spatiotemporal rs-fMRI diagnostic.

VS Code extension that exposes diagnostic problems via Model Context Protocol (MCP) for AI agents and tools

Computed tomography (CT) is one of the most widely used radiography exams worldwide for different diagnostic applications. However, CT scans involve ioniz- ing radiational exposure, which raises health concerns. Counter-intuitively, low- ering the adequate CT dose level introduces noise and reduces the image quality, which may impact clinical diagnosis. This study analyzed the feasibility of using a conditional generative adversarial network (cGAN) called pix2pix to learn the mapping from low dose to high dose CT images under different conditions. This study included 270 three-dimensional (3D) CT scan images (85,050 slices) from 90 unique patients imaged virtually using virtual imaging trials platform for model development and testing. Performance was reported as peak signal-to-noise ra- tio (PSNR) and structural similarity index measure

? AI-powered breast cancer classification using Logistic Regression with 95% accuracy. Features interactive Gradio web interface for real-time predictions on 30 diagnostic parameters from Wisconsin dataset. Includes comprehensive Jupyter notebooks for model training, evaluation metrics, and deployment-ready architecture for healthcare application.

SADA: Semantic Adversarial Diagnostic Attacks for Autonomous Applications (AAAI 2020)

For more information, refer to https://www.frontiersin.org/articles/10.3389/fnins.2019.00509/full

Source codes and datasets for paper "Zero-1-to-3: Domain-level Zero-shot Cognitive Diagnosis via One Batch of Early-bird Students towards Three Diagnostic Objectives" (AAAI2024)

A Diagnostic Benchmark for Evaluating Logical Robustness of Deductive Reasoners

This repository contains machine learning models for breast cancer tumor staging, leveraging SVM, Random Forest, AdaBoost, XGBoost, and ensemble methods to provide accurate and reliable staging predictions. It features comprehensive model evaluations and demonstrates the potential of ensemble methods in improving diagnostic accuracies.

Diagnostic Expert Advisor: A research platform for heterogeneous medical timeseries data

Defense of adversarial attacks on FDD models. fdd-defense is a python library with adversarial attacks on Fault Detection and Diagnostic (FDD) models and defense methods against attacks.