https://www.allerin.com/blog/3-ways-deep-learning-is-reinventing-the-healthcare-industry

University of Michigan - Ann Arbor

Deep Learning helps researchers and medical experts by analyzing medical data to treat diseases. It enhances healthcare providers'  abilities to analyze medical images, diagnose diseases accurately and provide personalized medicine.

More practically, the three useages of deep learning in current healthcare industry are:

1. Faster Diagnosis: 
GPU-accelerated Deep Learning to automate analysis and increase the accuracy of diagnosticians.

2. Genomics for Personalized Medicine : 
Deep Learning can help in tailoring personalized or “precision” medicine, with treatments that are customized according to a patient’s genomic makeup

3. Computer-Aid diagnosis:
Differentiation of malignancy/benignancy for tumors

Reference: https://www.allerin.com/blog/3-ways-deep-learning-is-reinventing-the-healthcare-industry


How Deep Learning is reinventing the healthcare industry

Personalization provides a more scalable and accurate way to achieve unique experiences for individual users. The list below is showing possible concepts and opportunities when building deep learning algorithm for personalization.

Sequence-aware recommenders :
Use of RNN (Recurrent neural network) to process a sequence of inputs by users for tailored experience. 

Classifiers:
Multi-class prediction models can help to improve user experience by showing the right content to the right user.

Context is king:
You need to know which context has higher value and can provide a better experience. 


How Deep Learning can be used for Personalization?

- A critical step in the fight against COVID-19 is effective screening of infected patients as well as be isolated to mitigate the spread of the virus.

- Deep convolutional neural network is used for the detection of COVID-19 cases from chest X-ray (CXR) images 

- Achieving 93.3% test accuracy, thus highlighting the efficacy of leveraging a human-machine collaborative design strategy

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