Virtual Assistance in Healthcare(All you need to know)
@ RISHIKA RAJ | Wednesday, Mar 24, 2021 | 5 minutes read | Update at Wednesday, Mar 24, 2021

Data Science is rapidly growing and occupying all the industries in the world today. There are various applications of data science that are transforming the healthcare sector. One the important aspect of it is Virtual Assistance. In this topic, we will understand the various underlying concepts of data science used in it.

What is Virtual Assistance?

Virtual Assistance is a comprehensive virtual platform developed by the data scientists that provides assistance to the patients. Through these platforms, a patient can enter his or her symptoms in the input and get insights of the various possible diseases/conditions based on the confidence rate.

How VA actually works?

Virtual assistants are combination of deep learning, machine learning, artificial intelligence that combine strong decision support systems and leverages big data, natural language processing and voice recognition. It also uses the disease predictive modelling for search.


Let’s see about them in details - • Artificial Neural Network (ANN): It is used to inform the healthcare management decisions. ANN has been used as a part of decision support models to provide healthcare Providers and the healthcare system with cost effective solutions to time and resource management.


• Deep Learning: It requires less preprocessing of data. The network itself take care of many of the filtering and normalization tasks that must be completed by human programmers when using machine learning techniques (Convolutional Neural Network).


• Natural Language Processing (NLP): The ability of machine to understand and learn from the language that humans speak and write. Because neural networks are designed for classification, they can identify individual linguistic or grammatical elements by “grouping” similar words together and mapping them in relation to one another. But apart from NLP, a lesser-known AI technology called the Natural Language Generation (NLG), which generates the text and speech using predefined data, is also put to use. Apart from this is used as speech recognition, for improvement of clinical documentation and data mining research.


How VA is the need of consumers?

Nowadays people are so busy in their day-to-day lives that they have started taking their health carelessly. They don’t have enough time to go visit a doctor, therefore VA is the need of the hour. There are various VA technologies that enhances the person engagement with the healthcare organizations. Some of them are explained below-

  • Automated calling system & interactive voice response systems: Voice over internet protocol (VoIP) implementation use VA to accomplish online health goals. It eliminates the cancellations and reduce outstanding bills.

  • Mhealth Apps: Healthcare providers encourages the patients to track fitness progress, do their payments and schedule day-to-day activities. There are fitness devices to track the heath parameters which are then uploaded to the portals which can be easily accessed through VA.

  • Patients Portals & Health Kiosks: Adoptions of patient health portals is still growing at a modest rate. Through online portals with VA , patients can confirm appointments, fill out medical history etc. Kiosks have great potential for collecting patients information through integrated VoIP system.

  • Discrete Data: VAs interact with patients and digitally capture their information which are verified in real time using cloud technologies and IoT connected devices. After this, the information is processed and populated into the EHR system.

  • Anytime Access from Anywhere: For the aging population, it is far better to have verbal communication along with virtual interaction, which is accomplished by VA.

Conclusion Post pandemic the Healthcare spending is projected to continue to increase by 1.8% annually, making it one of the most important sectors of economy. According to a study, the data generated by every human body is 2 terabytes per day. This data includes activities of brain, the stress level, heart rate, the sugar level, and many more. To handle such a large amount of data, now, we have more advanced technologies and one of them is Data Science. It helps monitor patients’ health using recorded data. Now Patients are starting to see themselves as consumers: they have instant access to information via their smartphones and wearables, and they don’t understand why healthcare can’t be like that too. There is growing pressure on providers to modernize and embrace new technologies. Basically, there are four factors leading to rapid improvement in the healthcare industry:

  • Technological advancement
  • Digitalization
  • Need for reducing treatment costs and duration
  • Need for handling large population Data Science has already started addressing all these to bring the desired effect.

Future Improvements in VA

  • By finding patterns among multimodal data can increase the accuracy of diagnosis, prediction, and overall performance of the learning system. However, multimodal learning is challenging due to the heterogeneity of the data.
  • Currently automatic speech recognition (ASR) solutions in medical domain only focus on transcribing doctor dictations (i.e., single speaker speech consisting of predictable medical terminology), but a recent research shows that it is possible to build an ASR model which can handle multiple speaker conversations covering complex medical diagnostic as well.
  • EHR vendors are also taking a hard look at how machine learning can streamline the user experience by eliminating wasteful interactions and presenting relevant data more intuitively within the workflow.

With an extremely high number of promising use cases, strong investment from major players in the industry, and a growing amount of data to support cutting-edge analytics, data science will no doubt play a major role in the quest to deliver the highest possible quality care to consumers for decades to come.

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