TrustyAI Explainability Toolkit

Supporting models and data to doi 10.1021/acs.jcim.1c01163

This repository contains a code of Unfold and Conquer Attribution Guidance, which is presented in a conference of Association for the Advancement of Artificial Intelligence 2023.

Ths repo has the list of Interesting Literature in the domain of XAI

OrganismCore transforms reasoning into executable artifacts built on the Universal Reasoning Substrate (URS). Its purpose is to accelerate discovery by making reasoning itself a programmable, transmissible, and model-agnostic object.

Skin cancer classification using Transfer Learning and explainable AI

Hacking a Neural Network to understand what concepts the network learns in order to solve a logic task.

Re-Implementation of COVID-NET in PyTorch

Methods to interpret machine learning models/black box which can help us understand how it’s making decisions.

An AI-powered clinical assistant using Retrieval-Augmented Generation (RAG) on the MIMIC-IV DiReCT dataset. It retrieves relevant patient cases and generates diagnostic reasoning using LLMs. Built with Streamlit, Transformers, FAISS, and SentenceTransformers.

See the world through the eyes of AI

Detects Pneumonia using Chest X rays through Deep Learning models