medical-projects Goto Github PK

icd-prediction-mimic

Predicting ICD Codes from Clinical Notes

icd_prediction

Predicting Medical Billing Codes (ICD9) from Clinical Notes (in MIMIC-III datasets) using Deep Learning

iceri-conference-2020-pmneumonia-xray-classification

This JuPyter notebook is a learning material for students. It is a case of medical image classification using deep learning (PyTorch framework).

iciar2018

Our solution for ICIAR 2018 Grand Challenge

iclr20-lcn

"Oblique Decision Trees from Derivatives of ReLU Networks" (ICLR 2020, previously called "Locally Constant Networks")

icmr

ICMR Sponsored Seminar On Deep Learning Techniques and Tools for Medical Applications

icmr-seminar

ICMR Sponsored Seminar On Deep Learning Techniques and Tools for Medical Applications

idontlikecode

igt

ihmc-robotics

Work done in IHMC Robotics since Aug 2019

iic

Invariant Information Clustering for Unsupervised Image Classification and Segmentation

iic-1

TensorFlow Implementation of https://arxiv.org/abs/1807.06653

ijcars19

Accurate and interpretable evaluation of surgical skills from kinematic data using fully convolutional neural networks

image-annotation-research

My Research on Implementing an algorithm of Image Annotation

image-processing-assignment

This assignment consists of the various image processing techniques applied on medical images which can be later processed easily to make predictions through machine learning and deep learning models

image-translation

Deep learning-based image translation for medical image analysis

imgclsmob

Sandbox for training deep learning networks

imgseg

medical image segmentation via deep learning

imimic-rcvs

This repository contains the code for implementing Bidirectional Relevance scores for Digital Histopathology, which was used for the results in the iMIMIC workshop paper: Regression Concept Vectors for Bidirectional Explanations in Histopathology

imodels

Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).

improving-3d-shape-prediction-from-a-single-rgb-image-with-deep-learning-by-adding-prior-cues

The goal of this 3D prediction from single RGB image is to predict the 3D geometry and structure of objects from a single RGB image using deep learning techniques. This long standing ill-posed problem is crucial to numerous applications such as robot navigation, object recognition and scene understanding, medical diagnosis, and 3D modeling and animatio n. The advancement of deep learning techniques and the increasing availability of large 3D training data sets, have lead to a new generatio n of 3D shape inference methods that are able to predict the 3D geometry and structure of objects from a single view. In this work, we have experimented on different output representations, i.e. voxel, mesh, and point cloud, and two coordinate systems, commonly known as object-centered and viewer-centered. We have developed an end-to-end learning framework with Variational Autoencoder network, where the recognition network maps both the input image and silhouette, autogenerated using U-Net, to a latent representation and the generative network is expected to perform non-trivial reasoning about the 3D structure of the object, which we tried on chair category of ShapeNet dataset and achieved a comparable result to the state of the art

independentevaluation

indexnet_matting

Indices Matter: Learning to Index for Deep Image Matting

indians_diabetes_prediction

Use 9 demographic/medical measurements to predict diabetes via deep learning MLP with cross-validation and grid search.

indigo

innereye-deeplearning

Medical Imaging Deep Learning library to train and deploy models on Azure Machine Learning and Azure Stack

instadam

Application to create ground truth pixel-wise labels for deep learning based semantic segmentation of complex shapes like mechanical/structural defects in civil infrastructure like buildings and bridges or medical images in a user friendly manner.

interp-net

Interpolation-Prediction Networks for Irregularly Sampled Time Series

interpretable-deep-learning-for-medical-imaging

interpretable-ml-covid-19

Interpretable Machine Learning for COVID-19