abdulkarimab Goto Github PK

advance-mil

Multiple Instance Learning

advmil

The implementation of Adversarial Multiple Instance Learning for the Survival Analysis on Whole-Slide Images

agxnet

air-quality-prediction

air_pollution_prediction

Predicting air pollution using ML model

balnmp

Predicting Axillary Lymph Node Metastasis in Early Breast Cancer Using Deep Learning on Primary Tumor Biopsy Slides, BCNB Dataset

barlow-twins-hsic

datatransfer

DATA TRANSFER

deepslide

Code for the Nature Scientific Reports paper "Pathologist-level classification of histologic patterns on resected lung adenocarcinoma slides with deep neural networks." A sliding window framework for classification of high resolution whole-slide images, often microscopy or histopathology images.

dtfd-mil

frmil

local_learning_wsi

Repository for "Gigapixel Whole-Slide Images Classification using Locally Supervised Learning"

math_foundation_ds

Mathematical FOundation

mil-land-cover-classification

Code for the paper "Scene-to-Patch Earth Observation: Multiple Instance Learning for Land Cover Classification".

mlnd-online-news-popularity-prediction

This is the Capstone Project of Udacity Machine Learning Nanodegree.

multiattentionmil

supplementary code for paper:

nagcn

ncrf

Cancer metastasis detection with neural conditional random field (NCRF)

pathml

Tools for computational pathology

pcl.pytorch

PyTorch codes for our papers "Multiple Instance Detection Network with Online Instance Classifier Refinement" and "PCL: Proposal Cluster Learning for Weakly Supervised Object Detection".

popularity-prediction

This repository contains the code for a Data Science project I did in school. Full report can be found here: https://medium.com/@syedsadiqalinaqvi/predicting-popularity-of-online-news-articles-a-data-scientists-report-fac298466e7

prerpcessing-pannuke-nuclei-instance-segmentation-dataset

python-projects

Amazing Python Projects.

rlogist

RLogist = RL (reinforcement learning) + Pathologist

scaledependantcnn

This repository contains all the necessary to reproduce the work in "Scale dependant layer for self-supervised nuclei encoding" (2022) by Peter Naylor, Yao-Hung Hubert Tsai, Marick Laé and Makoto Yamada.

slideflow

Deep learning pipeline for digital pathology, with both Tensorflow and PyTorch support.

springexamples

Initial Commit

swin-transformer

This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".

swin_mil

tabular-data-projects

Collection of ML scripts for tabular datasets