Deep Learning in health industry

In the Covid-19 pandemic, the situation changed dramatically. During the crisis, we saw rapid digital transformation and the adoption of disruptive technologies across all industries.

Healthcare organizations of all sizes, types, and specialists are increasingly interested in how artificial intelligence can support better patient care while reducing costs and improving efficiency.Deep learning is a good place to start. This branch of artificial intelligence has made rapid changes in health care, providing the ability to analyze data faster than ever before.

What is Deep Learning?

Deep learning is a machine learning technique that teaches computers to do what comes naturally to humans: example,Deep learning is a key technology behind driver less vehicles, enabling them to detect a stop sign, or to distinguish a pedestrian from a lamppost. It is the key to voice control on customer devices such as phones, tablets, TVs, and hands-free speakers. Deep learning gains a lot of attention lately and for good reason. It gets results that never happened before.

Use of Deep Learning in Healthcare

1. Diagnose diseases leveraging medical imaging solutions, for example recognition of potential cancerous lesions on radiology images.
2. Personalize medical treatments
3. Determine patients most at risk in the healthcare system
4. Drug Discovery
5. Simplifying Clinical Trails
6. Deep Learning and NLP(Natural language processing)

Conclusion:

Deep neural networks change the way doctors diagnose diseases, making diagnostics faster, cheaper, and more accurate than ever. deep learning is useful for converting biomedical data and improving human health care.