Medical Transcription Billing Corp (NASDAQ:MTBC) presented its advanced Intelligent EHR Coding Offering at the Machine Learning for Health Workshop. This presentation was done at the 2017 Annual Conference of NIPS 2017. The event, which was joined by many thought leaders in artificial intelligence from renowned institutions such as International Business Machines Corp (NYSE:IBM), Microsoft Corp (NASDAQ:MSFT), Alphabet Inc (NASDAQ:GOOG), Amazon.com Inc (NASDAQ:AMZN) and many others, was held from December 4 to December 9, 2017 in California.
Sibt ul Hussain, Ph.D., who is a member of Medical Transcription’s data science team and also one of company’s presenters at NIPS 2017, reported that machine learning and big data analytics are transforming the healthcare market and they are delighted that their team is on the forefront of these growing trends. Their research paper detailed a deep learning related artificial intelligence process for automating procedure coding. This presentation was well appreciated. It offers a roadmap that will eventually improve the accuracy and timeliness of the claim submission and code selection for their customer base.
NIPS 2017 marks as the 31st yearly conference of the renowned “Neural Information Processing Systems Foundation”, which exists to share the research findings on neural information processing mechanisms in their technological, mathematical, theoretical and biological aspects. The yearly NIPS conferences gets together data scientists from major academic institutions and firms to participate in events and share knowledge. Medical Transcription Billing’s data science team was led by Dr. Hussain and Rameel Ahmed at NIPS 2017.
In the last trading session, the stock price of Medical Transcription Billing declined 0.35% to close the day at $2.81. The decline came at a share volume of 93,307 compared to average share volume of 1.10 million. After the recent trading session, the market cap of firm was noted at $32.5 million. MTBC has recorded gains of more than 287% so far in this year.