5 ways Deep Learning AI can be used for better medical decisions

Applications of Deep Learning AI are accumulating a lot of hope and interest as an important non-medical intervention for transforming patient care and supporting clinicians.

Here are top five ways on how Deep Learning AI can be used in creating better medical decisions:

Drug Industry

Deep learning in drug industry facilitates the discovery of medicines and promote their research and accelerate development in the industry. Further, by analysing the patient’s past medical record it provides the best treatment for them. Moreover, Deep Learning is gaining insights from patient tests and disease symptoms as it is an ideal strategy for pharmaceutical stakeholders and researchers looking to highlight new patterns and information in these relatively unexplored data.

Clinical decision support

The healthcare field has inflated hopes from deep learning in predictive analytics and clinical decision support.

It facilitates the clinical decision support in the following ways :

1. Alert providers to changes in high-risk conditions.
2. Alert clinicians to patient downturns in the critical care centres.
3. Acts as a single model to predict outcomes of various research works.
4. Offers human clinicians and providers a detailed rationale for its recommendations.

Processing natural language

Neural networks and Deep Learning are underpinning many of the natural human language processing tools that have become known in the medical industry for translating speech-to-text and dictating various documents.

Although, Deep Learning in Medicare is still in its early stages of its potential, yet the future of healthcare and medicine has never been more exciting as not only do Deep Learning present an opportunity to develop many solutions that cater for very specific demand within the industry, but deep learning in healthcare can become powerful for transforming patient care and supporting decision making clinicians.

The author is Tanisha Gupta.