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Artificial Intelligence | Solve real world complex problems

2 minutes, 14 seconds read

Artificial Intelligence may be a concept unknown to a majority of consumers, but we unknowingly using AI in our everyday life. How? What about the smartphones with Google now and Siri, they help find information for you when you need it.

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With real-time problem solving skills the only thing you have to worry about are your goals as you can leave the assistance to a computer that can think on it’s own but for your benefit. Many intelligent brains working in Artificial Intelligence to make our life comfortable. If you could have someone looking over your day to day needs it’s rather easy to focus on more important things in life. Implementing AI into our lives has been studied for years and now things are getting more real and Mantra Labs is well invested into it.

From consulting on niche technologies, to completely owning your AI initiative – Mantra Labs help you solve complex real world problems, leveraging their expertise in various aspects of AI.

Data Science: It is the study of where information comes from, what it represents and how it can be turned into a valuable resource in the creation of business and IT strategies.

Natural Language: Natural Language Processing (NLP) refers to AI method of communicating with an intelligent system using a natural language such as English. Processing of Natural Language is required when you want an intelligent system like a robot to perform as per your instructions, when you want to hear a decision from a dialogue based clinical expert system, etc.

Machine Learning: It is a type of artificial intelligence (AI) that provides computers with the ability to learn without being explicitly programmed. Machine learning focuses on the development of computer programs that can teach themselves to grow and change when exposed to new data.

• Integrations: Most artificial intelligence systems involve some sort of integrated technologies, for example, the integration of speech synthesis technologies with that of speech recognition.

Deep Learning: Deep learning refers to artificial neural networks that are composed of many layers.  It  is a branch of machine learning based on a set of algorithms that attempt to model high level abstractions in data by using a deep graph with multiple processing layers, composed of multiple linear and non-linear transformations

• Computer Vision: It is the science that aims to give a similar, if not better, the capability to a machine or computer. Computer vision is concerned with the automatic extraction, analysis and understanding of useful information from a single image or a sequence of images.

Making an approach to pursue the most advanced technology takes a lot of innovation and it is exactly what Mantra Labs has been doing.

If you are keen to solve real world problem using AI, Drop us a line hello@mantralabsglobal.com

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Enhancing digital patient experience with healthcare chatbots

5 minutes read

Chatbots are fast emerging at the forefront of user engagement across industries. In 2021, healthcare is undoubtedly being touted as one of the most important industries due to the noticeable surge in demand amid the pandemic and its subsequent waves. The Global Healthcare Chatbots Market is expected to exceed over US$ 314.63 Million by 2024 at a CAGR of 20.58%.

Chatbots are being seen as those with high potential to revolutionize healthcare. They act as the perfect support system to agents on the floor by providing the first-step resolution to the customer, in terms of understanding intent and need, boost efficiency, and also improve the accuracy of symptom detection and ailment identification, preventive care, feedback procedures, claim filing and processing and more.

At the outset of the COVID-19 pandemic, digital tools in healthcare, most commonly chatbots, rose to the forefront of healthcare solutions. Providence St. Joseph Health, Mass General Brigham, Care Health Insurance (formerly Religare), and several other notable names built and rolled out artificial intelligence-based chatbots to help with diagnostics at the first stage before a human-human virtual contact, especially while differentiating between possible COVID-19 cases and other ailments. The CDC also hosts an AI-driven chatbot on its website to help screen for coronavirus infections. Similarly, the World Health Organization (WHO) partnered with a messaging app named Ratuken Viber, to develop an interactive chatbot for accurate information about COVID-19 in multiple languages. This allowed WHO to reach up to 1 billion people located anywhere in the world, at any time of the day, in their respective native languages.

For Care Health Insurance, Mantra Labs deployed their Conversational AI Chatbot with AR-based virtual support, called Hitee, trained to converse in multiple languages. This led to 10X interactions over the previous basic chatbot; 5X more conversions through Vanilla Web Experience; Drop-in Customer Queries over Voice Support by 20% among other benefits.

Artificial Intelligence’s role in the healthcare industry has been growing strength by strength over the years. According to the global tech market advisory firm ABI Research, AI spending in the healthcare and pharmaceutical industries is expected to increase from $463 million in 2019 to more than $2 billion over the next 5 years, healthtechmagazine.net has reported. 

Speaking of key features available on a healthcare chatbot, Anonymity; Monitoring; Personalization; collecting Physical vitals (including oxygenation, heart rhythm, body temperature) via mobile sensors; monitoring patient behavior via facial recognition; Real-time interaction; and Scalability, feature top of the list. 

However, while covering the wide gamut of a healthcare bot’s capabilities, it is trained on the following factors to come in handy on a business or human-need basis. Read on: 

Remote, Virtual Consults 

Chatbots were seen surging exponentially in the year 2016, however, the year 2020 and onwards brought back the possibility of adding on to healthcare bot capabilities as people continued to stay home amid the COVID-19 pandemic and subsequent lockdowns. Chatbots work as the frontline customer support for Quick Symptom Assessment where the intent is understood and a patient’s queries are answered, including connection with an agent for follow-up service, Booking an Appointment with doctors, and more. 

Mental Health Therapy

Even though anxiety, depression, and other mental health-related disorders and their subsequent awareness have been the talk around the world, even before the pandemic hit, the pandemic year, once again could be attributed to increased use of bots to seek support or a conversation to work through their anxiety and more amid trying times. The popular apps, Woebot and Wysa, both gained popularity and recognition during the previous months as a go-to Wellness Advisor. 

An AI Wellness Advisor can also take the form of a chatbot that sends regular reminders on meal and water consumption timings, nutrition charts including requisite consultation with nutritionists, lifestyle advice, and more. 

Patient Health Monitoring via wearables 

Wearable technologies like wearable heart monitors, Bluetooth-enabled scales, glucose monitors, skin patches, shoes, belts, or maternity care trackers promise to redefine assessment of health behaviors in a non-invasive manner and helps acquire, transmit, process, and store patient data, thereby making it a breeze for clinicians to retrieve it as and when they need it.

Remote patient monitoring devices also enable patients to share updates on their vitals and their environment from the convenience and comfort of home, a feature that’s gained higher popularity amid the pandemic.

A healthcare chatbot for healthcare has the capability to check existing insurance coverage, help file claims and track the status of claims. 

What’s in store for the future of chatbots in Healthcare? 

The three main areas where healthcare chatbots can be particularly useful include timely health diagnostics, patient engagement outside medical facilities, and mental health care. 

According to Gartner, conversational AI will supersede cloud and mobile as the most important imperative for the next ten years. 

“For AI to succeed in healthcare over the long-term, consumer comfort and confidence should be front and center. Leveraging AI behind the scenes or in supporting roles could collectively ease us into understanding its value without risking alienation,” reads a May 2021 Forbes article titled, The Doctor Is In: Three Predictions For The Future Of AI In Healthcare. 

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