The Path and Process to Advanced Healthcare

Exploring the possibilities of Natural Language Processing (NLP) being the next big data technology that advances modern healthcare to a new era.

The age of human-computer interaction is upon us. Considering the speed of technology these days, it would come as no surprise to witness the interaction going beyond screens. It won’t be long before computers will truly be able to derive meaning from human language and input. It’s the era of natural language processing and it needs to be put to good use.

The positive implications of NLP towards countless sectors are but evident. NLP could transform each sector it seeps into, be it industry, customer interaction or hospitality among countless others. However, potentially the biggest of lot could well be healthcare.

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Healthcare is one of the most, if not the most critical sector of human society. The market has expanded rapidly courtesy of evolving customer needs and a greater use of connected devices. With the advancement of technology, healthcare has already benefitted extensively. Yet, few technologies aid healthcare organizations extract in-depth information from a mass clutter of data. To cap it off, the mass of data is ever expanding. This poses a challenge for healthcare organizations to smoothly manage said data and make use of it to provide clinical healthcare solutions. In a nutshell, the problem is in fact an opportunity in disguise for NLP.

Natural language processing can play a game changing role in healthcare. NLP tools in the hands of healthcare providers will enable the creation of big data goldmine. Precision medicine, predictive analysis, mass health management, electronic health record documentation and clinical decision making; all stand to benefit with this treasure trove of data. Through machine learning and computer vision algorithms, the doors of opportunity have been flung wide open. These tools enable improved patient care by enabling large scale analysis of imaging and textual data. Being able to draw critical insights from a mass of both filtered and raw data will multiply the diagnosis, treatment and monitoring capacity of healthcare providers in a sustainable manner.

Pioneers in tech are already pulling ahead in the market as they integrate NLP into healthcare. IBM Watson Health, MEDIAN Technologies, Microsoft, Dell Services and many more are already adopting NLP to innovate and expand the segment of big data healthcare. Organizations such as Health Catalyst use data mining, modeling and algorithmic development to predict hospital readmission’s, heart failures and patient stay duration. UNC Healthcare is using IBM’s big data analytics to reduce costly and avoidable readmission’s, decrease mortality rates and improve patient care. Furthermore, newer entrants are constantly looking to capitalize on the opportunity NLP provides in order to keep pace with the growing demands of the segment.

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The marketplace for predictive analysis hit the $2.5 billion mark in 2014. From here, it is anticipated to grow at a steady rate of a little over 8% at least till the year 2020. Monetary predictions aside, there’s no doubt NLP will well and truly offer countless solutions in the face of growing concerns of healthcare being able to keep pace with technology. A boost in precision and predictive ability is exactly what the segment needs. In the right hands and with the right vision, organizations integrating NLP will be able to deliver exactly that and much more in the times to come.

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