Neural Network Case Study: Google Health/DeepMind

Today, neural networks (NN) transform business and everyday life, bringing us to the next level in artificial intelligence (AI). By mimicking the way brain cells work, NN-enabled devices (including smartphones and computers we use every day) are now trained to read, detect patterns, and make humanoid predictions and problem-solving in all areas of business.

So what is Neural Network?

Computer programs inspired by neural networks to perform various functions with a large amount of information involved are called neural networks or artificial ANN networks. Various algorithms are used to understand the relationships in a given data set to obtain the best results for dynamic inputs. The network is trained to produce the desired results and various models are used to predict future results and data. The nodes are connected to function like the human brain. Different connections and hidden patterns in raw data are used to compile and separate data.

• Neural networks are a series of algorithms that mimic the operations of a human brain to recognize relationships between vast amounts of data.

• They are used in a variety of applications in financial services, from forecasting and marketing research to fraud detection and risk assessment.

• The use of neural networks for stock market price prediction varies.

Application of Neural Networks

Neural networks are broadly used, with applications for financial operations, enterprise planning, trading, business analytics and product maintenance. Neural networks have also gained widespread adoption in business applications such as forecasting and marketing research solutions, fraud detection and risk assessment.

Google Health/DeepMind

The advancements in AI has spread across all the business domains with pharmaceutical companies lately catching up in the race.

AI Helps Doctors Complete Routine Tasks:

Google is beefing up a research project called Medical Digital Assist as it explores ways to use artificial intelligence to improve visits to the doctor’s office. The primary aim of using Medical Digital Assist to leverage speech and voice recognition technologies that can help physicians with note-taking and paperwork.

This tool, which can listen in on conversations between a doctor and patient, not only transcribes dialogue but also takes relevant notes automatically as a means to help care teams better coordinate, Android Headlines reports.

Google uses AI to help Cure Blindness

Google announced the development of an image library that helps itself, and other organizations, train AI models to detect diseases such as diabetic retinopathy one of the world’s fastest-growing causes of blindness.

In this case, Google trained the models using images it collected from a computer vision system that could read images of retinal fundus, or the interior lining of the eye.

Google help’s predict patients care needs

Google has also begun work on an electronic health record model that uses machine learning to forecast a host of patient outcomes. Among them, the potential length of a patient’s hospital stay, odds of readmission and the likelihood of death.

Conclusion

Mining medical records are the most obvious application of AI in medicine. Collecting, storing, normalizing, tracing its lineage is the first step in revolutionizing existing healthcare systems

The computing world has a lot to gain from neural networks. Their ability to learn by example makes them very flexible and powerful. Furthermore, there is no need to devise an algorithm to perform a specific task; i.e. there is no need to understand the internal mechanisms of that task. They are also very well suited for real-time systems because of their fast response and computational times which are due to their parallel architecture.

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