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RAD-DINO model
2024年11月
RAD-DINO is a vision transformer model trained to encode chest X-rays using the self-supervised learning method DINOv2. RAD-DINO is described in detail in RAD-DINO: Exploring Scalable Medical Image Encoders Beyond Text Supervision (F. Pérez-García, H. Sharma, S. Bond-Taylor, et al., 2024).
MAIRA-2 model
2024年11月
MAIRA-2 is a multimodal transformer designed for the generation of grounded or non-grounded radiology reports from chest X-rays. It is described in more detail in MAIRA-2: Grounded Radiology Report Generation (S. Bannur, K. Bouzid et al., 2024). MAIRA-2 has been built…
RadFact: An LLM-based Evaluation Metric for AI-generated Radiology Reporting
2024年11月
RadFact is a framework for the evaluation of model-generated radiology reports given a ground-truth report, with or without grounding. Leveraging the logical inference capabilities of large language models, RadFact is not a single number but a suite of metrics, capturing aspects of precision…
RadFact
2024年8月
RadFact is a framework for the evaluation of model-generated radiology reports given a ground-truth report, with or without grounding. Leveraging the logical inference capabilities of large language models, RadFact is not a single number but a suite of metrics, capturing…
Vaccine Search Study
2023年9月
This repository contains code and data for “Accurate Measures of Vaccination and Concerns of Vaccine Holdouts from Web Search Logs” (2023) by Serina Chang, Adam Fourney, and Eric Horvitz.
HI-ML Multimodal Toolbox
2023年5月
HI-ML toolbox for deep learning for medical imaging and Azure integration. The Microsoft Health Intelligence Machine Learning Toolbox aims at providing low-level and high-level building blocks for Machine Learning / AI researchers and practitioners. It helps to simplify and streamline…
Biomedical Signal Processing: “Yardl” tooling
2022年11月
Yardl is a simple schema language and command-line tool that generates domain types and serialization code. This is a tool for generating code based on a schema for raw instrument data.
Exercise Recognition from Wearable Sensors
2019年6月
This data set contains accelerometer and gyroscope recordings from over 200 participants performing various gym exercises. This data set is described in more detail in the associated manuscript: Morris, D., Saponas, T. S., Guillory, A., & Kelner, I. (2014, April).…