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  • šŸ‘‹ Hi, Iā€™m @nikhilkurian
  • šŸ‘€ Iā€™m interested in Deep Learning for medical image analysis
  • šŸŒ± Iā€™m currently a researcher at the Australian Institue for Machine Learning (AIML)
  • šŸ’žļø Iā€™m looking to collaborate on applying machine learning techiniques to apply in digitial pathologysettings
  • šŸ“« You can reach me on [email protected]

nikhilkurian's Projects

attentiondeepmil icon attentiondeepmil

Implementation of Attention-based Deep Multiple Instance Learning in PyTorch

chexploration icon chexploration

Official repository for 'Algorithmic encoding of protected characteristics in chest X-ray disease detection models'

clam icon clam

Data Efficient & Weakly Supervised Computational Pathology on Whole Slide Images

cs496-project icon cs496-project

Repository containing code, papers, and report for CS496 (BTP-2).

d2l-pytorch icon d2l-pytorch

This project reproduces the book Dive Into Deep Learning (www.d2l.ai), adapting the code from MXNet into PyTorch.

deepslide icon 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.

llm-course icon llm-course

Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.

minimal-mistakes icon minimal-mistakes

:triangular_ruler: Jekyll theme for building a personal site, blog, project documentation, or portfolio.

monusac icon monusac

This repository contains my implementations of the algorithms which MoNuSAC participants could use for data preparation to train their models at ISBI 2020.

vision icon vision

Datasets, Transforms and Models specific to Computer Vision

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