Yujing Zou (yujing1997)

yujing1997

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Company:McGill University

Twitter:@yujingzou

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Yujing Zou's repositories

hs2p

Histopathology Slides Preprocessing Pipeline

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2D-VQ-AE-2

2D Vector-Quantized Auto-Encoder for compression of Whole-Slide Images in Histopathology

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auton-survival

Auton Survival - an open source package for Regression, Counterfactual Estimation, Evaluation and Phenotyping with Censored Time-to-Events

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awesome-self-supervised-learning-for-tabular-data

A collection of research materials on SSL for non-sequential tabular data (SSL4NSTD)

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chromark

Code for the manuscript: "Single-cell imaging-AI based chromatin biomarkers for diagnosis and therapy evaluation in tumor patients using liquid biopsies". Code was developed by Daniel Paysan

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dysts_ML_chaos_predictor

More than a hundred strange attractors

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faiss

A library for efficient similarity search and clustering of dense vectors.

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foundation-cancer-image-biomarker

Code and evaluation repository for the paper

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HECTOR

Multimodal deep learning to predict distant recurrence-free probability from digitized H&E tumour slide and tumour stage.

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langgraph

Build resilient language agents as graphs.

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luna

Scripts for data processing

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M3L

Official repository for "Missing Modality Robustness in Semi-Supervised Multi-Modal Semantic Segmentation"

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MedSAM

The official repository for MedSAM: Segment Anything in Medical Images.

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MedSAMSlicer

3D Slicer Plugin for Segment anything in medical images

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MICCAI_MultimodalTransformerPathOmics

[MICCAI 2023] The official code of "Pathology-and-genomics Multimodal Transformer for Survival Outcome Prediction" (Accepted to MICCAI2023, , top14%)

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Multimodal-CustOmics

Multimodal CustOmics: A Unified and Interpretable Multi-Task Deep Learning Framework for Multimodal Integrative Data Analysis in Oncology

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ollama-python

Ollama Python library

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penzai

A JAX research toolkit for building, editing, and visualizing neural networks.

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plip

Pathology Language and Image Pre-Training (PLIP) is the first vision and language foundation model for Pathology AI. PLIP is a large-scale pre-trained model that can be used to extract visual and language features from pathology images and text description. The model is a fine-tuned version of the original CLIP model.

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prov-gigapath

Prov-GigaPath: A whole-slide foundation model for digital pathology from real-world data

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pycox

Survival analysis with PyTorch

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pysurvival

Open source package for Survival Analysis modeling

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RepresentationLearning_SS2023

Representation Learning MSc course Summer Semester 2023

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SurvLIMEpy

Local interpretability for survival models

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survshap

SurvSHAP(t): Time-dependent explanations of machine learning survival models

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