A General-Purpose Self-Supervised Model for Computational Pathology

no code implementations • 29 Aug 2023 • Richard J. Chen, Tong Ding, Ming Y. Lu, Drew F. K. Williamson, Guillaume Jaume, Bowen Chen, Andrew Zhang, Daniel Shao, Andrew H. Song, Muhammad Shaban, Mane Williams, Anurag Vaidya, Sharifa Sahai, Lukas Oldenburg, Luca L. Weishaupt, Judy J. Wang, Walt Williams, Long Phi Le, Georg Gerber, Faisal Mahmood

Tissue phenotyping is a fundamental computational pathology (CPath) task in learning objective characterizations of histopathologic biomarkers in anatomic pathology.

Code Classification Representation Learning +1

Weakly Supervised AI for Efficient Analysis of 3D Pathology Samples

1 code implementation • 27 Jul 2023 • Andrew H. Song, Mane Williams, Drew F. K. Williamson, Guillaume Jaume, Andrew Zhang, Bowen Chen, Robert Serafin, Jonathan T. C. Liu, Alex Baras, Anil V. Parwani, Faisal Mahmood

Human tissue and its constituent cells form a microenvironment that is fundamentally three-dimensional (3D).

Multiple Instance Learning Predicting Patient Outcomes +1

Towards a Visual-Language Foundation Model for Computational Pathology

no code implementations • 24 Jul 2023 • Ming Y. Lu, Bowen Chen, Drew F. K. Williamson, Richard J. Chen, Ivy Liang, Tong Ding, Guillaume Jaume, Igor Odintsov, Andrew Zhang, Long Phi Le, Georg Gerber, Anil V Parwani, Faisal Mahmood

The accelerated adoption of digital pathology and advances in deep learning have enabled the development of powerful models for various pathology tasks across a diverse array of diseases and patient cohorts.

Contrastive Learning Image Classification +3

Visual Language Pretrained Multiple Instance Zero-Shot Transfer for Histopathology Images

1 code implementation • CVPR 2023 • Ming Y. Lu, Bowen Chen, Andrew Zhang, Drew F. K. Williamson, Richard J. Chen, Tong Ding, Long Phi Le, Yung-Sung Chuang, Faisal Mahmood

In this paper we present MI-Zero, a simple and intuitive framework for unleashing the zero-shot transfer capabilities of contrastively aligned image and text models on gigapixel histopathology whole slide images, enabling multiple downstream diagnostic tasks to be carried out by pretrained encoders without requiring any additional labels.

Multiple Instance Learning whole slide images

A Review of Vision-Language Models and their Performance on the Hateful Memes Challenge

1 code implementation • 9 May 2023 • Bryan Zhao, Andrew Zhang, Blake Watson, Gillian Kearney, Isaac Dale

In this work, we aim to explore different models and determine what is most effective for the Hateful Memes Challenge, a challenge by Meta designed to further machine learning research in content moderation.

A Robot for Nondestructive Assay of Holdup Deposits in Gaseous Diffusion Piping

no code implementations • 29 Jan 2019 • Heather Jones, Siri Maley, Mohammadreza Mousaei, David Kohanbash, Warren Whittaker, James Teza, Andrew Zhang, Nikhil Jog, William Whittaker

The RadPiper robot, part of the Pipe Crawling Activity Measurement System (PCAMS) developed by Carnegie Mellon University and commissioned for use at the DOE Portsmouth Gaseous Diffusion Enrichment Facility, automatically measures U-235 in pipes from the inside.

WALL-E: An Efficient Reinforcement Learning Research Framework

1 code implementation • 18 Jan 2019 • Tianbing Xu, Andrew Zhang, Liang Zhao

There are two halves to RL systems: experience collection time and policy learning time.

reinforcement-learning Reinforcement Learning (RL)