Papers
→ Will Thompson, David Vidmar, Jessica De Freitas, Gabriel Altay, Kabir Manghnani, Andrew Nelsen, Kellie Morland, John Pfeifer, Brandon Fornwalt, RuiJun Chen, Martin Stumpe, Riccardo Miotto “Large Language Models with Retrieval-Augmented Generation for Zero-Shot Disease Phenotyping.” DGM4H NeurIPS 2023.
→ David Vidmar, Will Thompson, Ruijun Chen, Dustin Hartzel, Daniel Rocha, Joseph Leader, Brandon Fornwalt, and Christopher M Haggerty. 2022. “Abstract 11934: Natural Language Processing Models Can Be Trained to Accurately Recognize the Presence of Disease Within Clinical Notes.” Circulation 146 (Suppl_1): A11934–A11934.
Repos
→ mistral_7b_lora_example (2024) - example of how to fine-tune Mistral-7B via QLoRA.
→ microstructure-plotter (2023) - visualize market microstructure data.
→ tldr-transformers (2021)- earlier set of notes comparing transformer research threads.
→ deeplearning-nlp-models (2020)- built a few deep learning models from scratch in Pytorch (w/ tests). Run on GPUs.
Patents
→ Translating AI Algorithms From 12-Lead Clinical ECGS to Portable and Consumer ECGS With Fewer Leads
→ Phenotyping of clinical notes using natural language processing models