Agno is a lightweight library for building Multimodal Agents. It exposes LLMs as a unified API and gives them superpowers like memory, knowledge, tools and reasoning.

Cancer survival measures

Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.

Python training for business analysts and traders

A machine learning software for extracting information from scholarly documents

OncoText is an information extraction service for breast pathology reports. It supports over 20 categories including DCIS, includes pretrained models, and supports flexible addition of new categori…

Developing Deep Learning Models for Mammography

Sharing Deep Learning Models for Breast Cancer Risk

This repository was used to develop Mirai, the risk model described in: Towards Robust Mammography-Based Models for Breast Cancer Risk.

Collecting papers from PubMed Central and extracting text, metadata and stereotactic coordinates.

Simple and readable code for training and sampling from diffusion models

Make Mac apps accessible for AI agents

Make websites accessible for AI agents

reasoning model trained using GRPO towards rosetta REF2015 for protein stability

The official codes for "PMC-LLaMA: Towards Building Open-source Language Models for Medicine"

9 separate websites IN SECONDS for you to chaotically edit!

MedAgentBench: A Realistic Virtual EHR Environment to Benchmark Medical LLM Agents

A lightweight data processing framework built on DuckDB and 3FS.

Basic implementation of the life2vec model with the dummy data.

A community-maintained repository of cancer clinical knowledge bases and databases focused on cancer variants.

save 200 a month and use deep research right in your terminal. - port of https://github.com/dzhng/deep-research but in python

Single-Sample Predictors for Breast Cancer (sspbc) include functions and models to assign classes to breast cancer samples using gene expression data.

Mapping ICD billing codes and terms to a standard ontology