Showing posts with label Artificial Intelligence. Show all posts
Showing posts with label Artificial Intelligence. Show all posts

Tuesday, April 28, 2020

What is AI and Why You Should Be Excited About It

In 1950, Alan Turing asked, “Can machines think?”. Fast-forward to 2010 and artificial intelligence can diagnose diseases, fly drones, translate between languages, recognise emotions, trade stocks and even beat humans at Chess and Go.

Artificial Intelligence (AI), in essence, is machines mimicking human intelligence. Now, that can be of two types:
1. One that's already here, narrow AI, where a computer performs some very specific task. Take for example, Apple's Siri or Netflix's recommender system.
2. The other, general AI, that remains science fiction for now. If you're thinking of Jarvis in “Iron Man" or R2-D2 in “Star Wars”, you're quite right.

An application of AI is Machine Learning, where the computer automatically improves at performing a task, with more experience. Deep Learning is a subset of machine learning that is more intensive; uses more data and more complex algorithms.

Now, as a community of medicos, why should we bother about tech at all? Well, the future of healthcare looks increasingly facilitated by technology. The aim is to shift from "treating illness" to "sustaining wellness"; to have have a more proactive, rather than a reactive, model of care delivery. AI will help redesign our services and better utilise our resources. The goal isn't to replace what humans do, but instead augment it.

Here are a few ways AI can potentially help medicine:
1. Image recognition and diagnostic radiography, eg:, and Stanford's CheXpert system 
2. Preliminary diagnoses, eg: Babylon Health, and DeepMind's Streams application 
3. Virtual nursing assistants, eg: Care Angel's virtual nurse assistant
4. Clinical trials participant identifier, eg:
5. Computer-assisted robotic surgery, eg: Heartlander miniature robot
6. 3D mapping and printing, eg: 3D printed heart stents
7. Administrative workflow assistance, eg: IBM Watson 
8. Fraud detection and Cybersecurity, eg: 

[The list is by no means exhaustive. I implore you to know more about the examples mentioned by simply copy-pasting them into Google search.]

To conclude, the future of healthcare looks exciting and will be far more collaborative than it is today, working in alliance with AI, data science, statistics, engineering, and genomics. The ultimate objective is always to improve quality of treatment and patient outcomes.

Author's note: If, as a med student or a doctor, you're interested in kickstarting your own career towards AI and healthcare, please let me know in the comments. I will appropriately refer you to the relevant resources. To give you a brief background, I’ve worked with data scientists on seven medicine related portfolio projects, utilising machine and deep learning algorithms. I worked as a clinician and a programmer (have professional working proficiency in Python). Here’s my top 3:
1. Breast Cancer Detection Using Python & Machine Learning, with a model accuracy of 95% using artificial neural networks and support vector machine, on Wisconsin diagnostic data set
2. Identifying Skin Lesions Using Python & Deep Learning, with a model accuracy of 79% using convolution neural networks, on Cornell HAMNIST-10000 data set
3. Determining the Efficacy of Corrective Spinal Surgery in Childhood Kyphosis Using Python & Machine Learning, with a model accuracy of 88% using decision trees and random forest classifier on a Kaggle datset 

Thank you for reading.

- Ashish Singh

Wednesday, April 1, 2020

COVID-19: Lessons from coronavirus outbreak in China and formulating a strategy

Hello awesomites!

The following information is regarding the situation of COVID19 in China and how did China manage to reduce the incidence of new cases.

Image by  Nakeya. Medicowesome 2020