Category: Application Development
Big data analytics, NLP, and telemedicine are among the top healthcare trends in 2018 ensuring lower costs for providers and higher patient care quality.
While building mobile banking apps companies very often face the following challenges:
- How to build a secure app?
- How to make the app attractive and good selling?
- How to make the app helpful and convenient on the go?
- How to stand out of the competition but at the same time not to exceed the budget?
The answers to these and other questions on the latest security issues and the widely used technologies to protect your mobile banking app against the most common vulnerabilities you will find in this blog.
Technical implementation of HIPAA compliance explained including the benefits and challenges you will meet.
The numbers tell the story best:
- nowadays 31% of healthcare providers are said to have manual claims denial management processes. Manual claims management processes deprive you of elasticity and innovations, increase the possibility of human error and the costs spent on manpower.
- modern automation tools and services can decrease the number of failed claims by up to 30%.
Would you like to implement the Automating Healthcare Claim Processing but don’t know where to start? Here are some practical tips on Claim Processing Automation.
Looking for the best APIs to integrate with your fintech solution? In this blog we will help you understand:
- What is an API integration?
- Essential integrations for Fintech products used for
APIs offered by fintech platforms will help you reduce fraud and other financial risks, enhance security, eliminate the paper hassle, enable instant integration with popular accounting platforms and much more.
Want to increase your sales? Here’s a detailed case study on how ecommerce companies can leverage profits with machine learning algorithms.
This is how clinical natural language processing can improve the quality of care, boost doctors’ efficiency, and improve the patient outcomes. Tech tips on NLP implementation included.
Commentary from data scientist on how to improve diagnosis with clustering analysis models (DBSCAN), classification models, and forecasting models (using regression).
