Chest X-Ray Abnormality Classification Using Monk AI

Key Tasks

In this blog post, we will be performing three main tasks:-

  • To create a binary classifier to classify the chest x-ray images as normal/abnormal.To compare three deep neural network architectures.To create a multi-label classifier to generate 14 disease labels and the respective confidence scores.

Three deep neural network architectures used by me are Vgg16, Resnet50, and MobileNet.

Table of Contents

1. Installing Monk

2. Downloading dataset

3. Importing Framework and libraries

4. Visualizing and Exploring the Samples Provided from Dataset

5. Visualizing and Exploring the Samples Provided from Dataset

6. Comparing

7. Infer


Installing Monk

We will start by setting up the Monk AI toolkit and its dependencies on the platform you are working with and I am using Google Colab as my environment.

!git clone https://github.com/Tessellate-Imaging/monk_v1.git
!cd monk_v1/installation/Misc && pip install -r requirements_colab.txt

Downloading the Dataset

After setting up the Monk toolkit the next step is to install Kaggle and download the NIH Chest X-Ray Dataset from Kaggle on our Colab notebook.

! pip install -q kaggle

To download any dataset from Kaggle we need to first download the kaggle.json file by going to MyAccount on Kaggle and download a new API. Then we will upload the JSON file on our Colab notebook.

from google.colab import files

files.upload()

Now we can download the zip file of the dataset from Kaggle and unzip it.

! mkdir ~/.kaggle
! cp kaggle.json ~/.kaggle/
! chmod 600 ~/.kaggle/kaggle.json
! kaggle datasets download -d 'nih-chest-xrays/sample'
! unzip -qq sample.zip

The dataset has a total of 15 classes (14 disease classes and 1 “no findings” class).

Image for post

A Chest X-Ray Image from NIH Chest X-Ray Dataset in Kaggle

Importing Frameworks and libraries

Monk provides us three major frameworks to work with i.e., Keras, Pytorch, and Mxnet. We are using Keras framework for this project and the Pandas library is used for visualizing and exploring the dataset. To set up a working directory of a project we initialize a prototype for the framework being used.

from keras_prototype import prototype
import pandas as pd

Visualizing and Exploring the Samples provided from Dataset

Two DataFrames were made, one had multi-labeled target values which comprised of 14 disease classes and 1 “no finding” class, for binary classification of images another DataFrame was formed by replacing the disease classes and the “no finding” class by **abnormal **and **normal **respectively

$ df=pd.read_csv('sample/sample_labels.csv')

$ for i in range(len(df)):
          df["Finding Labels"][i] = df["Finding Labels"][i].replace("|", ",");
$ df.to_csv("sample/kush1.csv", index=False)
$ for i in range(len(df)):
if df["Finding Labels"][i] == "No Finding":
df["Finding Labels"][i] = "Normal";
else:
               df["Finding Labels"][i] = "Abnormal";
$ df.to_csv("sample/kush2.csv",index=False)

#image-classification #monk #chest-x-ray #deep-learning #computer-vision #deep learning

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Chest X-Ray Abnormality Classification Using Monk AI

Chest X-Ray Abnormality Classification Using Monk AI

Key Tasks

In this blog post, we will be performing three main tasks:-

  • To create a binary classifier to classify the chest x-ray images as normal/abnormal.To compare three deep neural network architectures.To create a multi-label classifier to generate 14 disease labels and the respective confidence scores.

Three deep neural network architectures used by me are Vgg16, Resnet50, and MobileNet.

Table of Contents

1. Installing Monk

2. Downloading dataset

3. Importing Framework and libraries

4. Visualizing and Exploring the Samples Provided from Dataset

5. Visualizing and Exploring the Samples Provided from Dataset

6. Comparing

7. Infer


Installing Monk

We will start by setting up the Monk AI toolkit and its dependencies on the platform you are working with and I am using Google Colab as my environment.

!git clone https://github.com/Tessellate-Imaging/monk_v1.git
!cd monk_v1/installation/Misc && pip install -r requirements_colab.txt

Downloading the Dataset

After setting up the Monk toolkit the next step is to install Kaggle and download the NIH Chest X-Ray Dataset from Kaggle on our Colab notebook.

! pip install -q kaggle

To download any dataset from Kaggle we need to first download the kaggle.json file by going to MyAccount on Kaggle and download a new API. Then we will upload the JSON file on our Colab notebook.

from google.colab import files

files.upload()

Now we can download the zip file of the dataset from Kaggle and unzip it.

! mkdir ~/.kaggle
! cp kaggle.json ~/.kaggle/
! chmod 600 ~/.kaggle/kaggle.json
! kaggle datasets download -d 'nih-chest-xrays/sample'
! unzip -qq sample.zip

The dataset has a total of 15 classes (14 disease classes and 1 “no findings” class).

Image for post

A Chest X-Ray Image from NIH Chest X-Ray Dataset in Kaggle

Importing Frameworks and libraries

Monk provides us three major frameworks to work with i.e., Keras, Pytorch, and Mxnet. We are using Keras framework for this project and the Pandas library is used for visualizing and exploring the dataset. To set up a working directory of a project we initialize a prototype for the framework being used.

from keras_prototype import prototype
import pandas as pd

Visualizing and Exploring the Samples provided from Dataset

Two DataFrames were made, one had multi-labeled target values which comprised of 14 disease classes and 1 “no finding” class, for binary classification of images another DataFrame was formed by replacing the disease classes and the “no finding” class by **abnormal **and **normal **respectively

$ df=pd.read_csv('sample/sample_labels.csv')

$ for i in range(len(df)):
          df["Finding Labels"][i] = df["Finding Labels"][i].replace("|", ",");
$ df.to_csv("sample/kush1.csv", index=False)
$ for i in range(len(df)):
if df["Finding Labels"][i] == "No Finding":
df["Finding Labels"][i] = "Normal";
else:
               df["Finding Labels"][i] = "Abnormal";
$ df.to_csv("sample/kush2.csv",index=False)

#image-classification #monk #chest-x-ray #deep-learning #computer-vision #deep learning

Otho  Hagenes

Otho Hagenes

1619511840

Making Sales More Efficient: Lead Qualification Using AI

If you were to ask any organization today, you would learn that they are all becoming reliant on Artificial Intelligence Solutions and using AI to digitally transform in order to bring their organizations into the new age. AI is no longer a new concept, instead, with the technological advancements that are being made in the realm of AI, it has become a much-needed business facet.

AI has become easier to use and implement than ever before, and every business is applying AI solutions to their processes. Organizations have begun to base their digital transformation strategies around AI and the way in which they conduct their business. One of these business processes that AI has helped transform is lead qualifications.

#ai-solutions-development #artificial-intelligence #future-of-artificial-intellige #ai #ai-applications #ai-trends #future-of-ai #ai-revolution

Dominic  Feeney

Dominic Feeney

1624435853

X-ray Image Classification and Model Evaluation

Pneumonia detection from chest X-ray images using Tensorflow

Kaggle has a wonderful source of chest X-ray image datasets for pneumonia and normal cases. There are significant differences between the image of a normal X-ray and an affected X-ray. Machine learning can play a pivotal role in determining the disease and significantly boost the diagnosis time as well as reduce human effort. In this article, I will walk through this dataset and classify the images with an evaluation accuracy of 90%

Image by Author

I have been motivated by the work done here on the datasets between cats and dogs and reused the code block for dataset pipeline. First we need to import the necessary packages.

#image-classification #x-rays #tensorflow #dnn #python #x-ray image classification and model evaluation

Russian Alphabet Classification Using Monk AI

Table of contents:

  1. Introduction
  2. About the Dataset
  3. Setting up Monk and Prerequisites
  4. Downloading Dataset
  5. Creating Projects and Experiments
  6. Approach
  7. Selecting the best model
  8. Conclusion

Introduction:

It is an easy task for us to classify handwritten information but to computers, it is a disconcerting and daunting job. Handwritten character classification in general is a challenging task because there are innumerable ways in which any character can be written.

Neural networks have although redefined this task and also play a huge role in developing such classifiers, provided they are fed with a huge amount of data for it to be trained.

In this particular blog, we will explore the Russian alphabets and classify them in their handwritten form.

About The Dataset:

In the data set, we have got 14190 colored images distributed among 3 image folders, consisting of all 33 categories of Russian alphabets.

The first folder has striped backgrounds (with few horizontal and/or vertical lines), the second folder has white backgrounds and the third one has graph type backgrounds (with many ordered horizontal and vertical lines).

#handwritten-classifier #russian-letters #monk #classification #russian-dataset #ai

Why Use WordPress? What Can You Do With WordPress?

Can you use WordPress for anything other than blogging? To your surprise, yes. WordPress is more than just a blogging tool, and it has helped thousands of websites and web applications to thrive. The use of WordPress powers around 40% of online projects, and today in our blog, we would visit some amazing uses of WordPress other than blogging.
What Is The Use Of WordPress?

WordPress is the most popular website platform in the world. It is the first choice of businesses that want to set a feature-rich and dynamic Content Management System. So, if you ask what WordPress is used for, the answer is – everything. It is a super-flexible, feature-rich and secure platform that offers everything to build unique websites and applications. Let’s start knowing them:

1. Multiple Websites Under A Single Installation
WordPress Multisite allows you to develop multiple sites from a single WordPress installation. You can download WordPress and start building websites you want to launch under a single server. Literally speaking, you can handle hundreds of sites from one single dashboard, which now needs applause.
It is a highly efficient platform that allows you to easily run several websites under the same login credentials. One of the best things about WordPress is the themes it has to offer. You can simply download them and plugin for various sites and save space on sites without losing their speed.

2. WordPress Social Network
WordPress can be used for high-end projects such as Social Media Network. If you don’t have the money and patience to hire a coder and invest months in building a feature-rich social media site, go for WordPress. It is one of the most amazing uses of WordPress. Its stunning CMS is unbeatable. And you can build sites as good as Facebook or Reddit etc. It can just make the process a lot easier.
To set up a social media network, you would have to download a WordPress Plugin called BuddyPress. It would allow you to connect a community page with ease and would provide all the necessary features of a community or social media. It has direct messaging, activity stream, user groups, extended profiles, and so much more. You just have to download and configure it.
If BuddyPress doesn’t meet all your needs, don’t give up on your dreams. You can try out WP Symposium or PeepSo. There are also several themes you can use to build a social network.

3. Create A Forum For Your Brand’s Community
Communities are very important for your business. They help you stay in constant connection with your users and consumers. And allow you to turn them into a loyal customer base. Meanwhile, there are many good technologies that can be used for building a community page – the good old WordPress is still the best.
It is the best community development technology. If you want to build your online community, you need to consider all the amazing features you get with WordPress. Plugins such as BB Press is an open-source, template-driven PHP/ MySQL forum software. It is very simple and doesn’t hamper the experience of the website.
Other tools such as wpFoRo and Asgaros Forum are equally good for creating a community blog. They are lightweight tools that are easy to manage and integrate with your WordPress site easily. However, there is only one tiny problem; you need to have some technical knowledge to build a WordPress Community blog page.

4. Shortcodes
Since we gave you a problem in the previous section, we would also give you a perfect solution for it. You might not know to code, but you have shortcodes. Shortcodes help you execute functions without having to code. It is an easy way to build an amazing website, add new features, customize plugins easily. They are short lines of code, and rather than memorizing multiple lines; you can have zero technical knowledge and start building a feature-rich website or application.
There are also plugins like Shortcoder, Shortcodes Ultimate, and the Basics available on WordPress that can be used, and you would not even have to remember the shortcodes.

5. Build Online Stores
If you still think about why to use WordPress, use it to build an online store. You can start selling your goods online and start selling. It is an affordable technology that helps you build a feature-rich eCommerce store with WordPress.
WooCommerce is an extension of WordPress and is one of the most used eCommerce solutions. WooCommerce holds a 28% share of the global market and is one of the best ways to set up an online store. It allows you to build user-friendly and professional online stores and has thousands of free and paid extensions. Moreover as an open-source platform, and you don’t have to pay for the license.
Apart from WooCommerce, there are Easy Digital Downloads, iThemes Exchange, Shopify eCommerce plugin, and so much more available.

6. Security Features
WordPress takes security very seriously. It offers tons of external solutions that help you in safeguarding your WordPress site. While there is no way to ensure 100% security, it provides regular updates with security patches and provides several plugins to help with backups, two-factor authorization, and more.
By choosing hosting providers like WP Engine, you can improve the security of the website. It helps in threat detection, manage patching and updates, and internal security audits for the customers, and so much more.

Read More

#use of wordpress #use wordpress for business website #use wordpress for website #what is use of wordpress #why use wordpress #why use wordpress to build a website