Showing posts with label AI Solutions. Show all posts
Showing posts with label AI Solutions. Show all posts

Thursday, 9 March 2023

Innocens BV leverages IBM Technology to Develop an AI Solution to help detect potential sepsis events in high-risk newborns

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From the moment of birth to discharge, healthcare professionals can collect so much data about an infant’s vitals—for instance, heartbeat frequency or every rise and drop in blood oxygen level. Although medicine continues to advance further, there’s still much to be done to help reduce the number of premature births and infant mortality. The worldwide statistics on premature births are staggering— the University of Oxford estimates that neonatal sepsis causes 2.5 million infant deaths annually.

Babies born prematurely are susceptible to health problems. Sepsis or bloodstream infection is life threatening and a common complication when admitted in a Neonatal Intensive Care Unit (NICU).

At Innocens BV, the belief is that earlier identification of sepsis-related events in newborns is possible, especially given the vast amount of data points collected from the moment a baby is born. Years’ worth of aggregated data in the NICU could help lead us to a solution. The challenge was gleaning relevant insights from the vast amount of data collected to help identify those infants at risk. This mission is how Innocens BV began in the Neonatal Intensive Care Unit (NICU) at Antwerp University Hospital in Antwerp, Belgium in cooperation with the University of Antwerp. The NICU at the hospital is associated closely with the University , and its focus is on improving care for premature and low birthweight infants. We joined forces with a Bio-informatics research group from the University of Antwerp and started taking the first steps in developing a solution.

Using IBM’s technology and the expertise of their data scientists along with the knowledge and insights from the hospital’s NICU medical team, we kicked off a project to further develop the ideas into a solution that was aimed at using clinical signals that are routinely collected in clinical care to aid doctors with the timely detection of patterns in such data that are associated with a sepsis episode. The specific approach we took required the use of both AI and edge computing to create a predictive model that could process years of anonymized data to help doctors make informed decisions. We wanted to be able to help them observe and monitor the thousands of data points available to make informed decisions.

How AI powers the Innocens Project


When the collaboration began, data scientists at IBM understood they were dealing with a sensitive topic and sensitive information. The Innocens team needed to build a model that could detect subtle changes in neonates’ vital signs while generating as few false alarms as possible. This required a model with a high level of precision that also is built upon  key principles of trustworthy AI including transparency, explainability, fairness, privacy and robustness.

Using IBM Watson Studio, a service available on IBM Cloud Pak for Data, to train and monitor the AI solution’s machine learning models, Innocens BV could help doctors by providing data driven insights that are associated with a potential onset of sepsis. Early results on historical data show that many severe sepsis cases can be identified multiple hours in advance. The user interface providing the output of the predictive AI model is designed to help provide doctors and other medical personel with insights on individual patients and to augment their clinical intuition.

Innocens worked closely with IBM and medical personel at the Antwerp University Hospital to develop a purposeful platform with a user interface that is consistent and easy to navigate and uses a comprehensible AI model with explainable AI capabilities. With the doctors and nurses in mind, the team aimed to create a model that would allow the intended users to reap its benefits. This work was imperative for building trust between the users and the instruments that would help inform a clinician’s diagnosis. Innocens also involved doctors in the development process of building the user interface and respected the privacy and confidentiality of the anonymous historical patient data used to train the model within a robust data architecture.

The technology and outcomes of this research project could have the potential to not only help the patients at Antwerp University Hospital, but to scale for different NICU centers and help other hospitals as they work to combat neonatal sepsis. Innocens BV is working in collaboration with IBM to explore how Innocens can continue to leverage data to help train transparent and explainable AI models capable of finding patterns in patient data, providing doctors with additional data insights and tools that help inform clinical decision-making.

The impact of the Innocens technology is being investigated in clinical trials and is not yet commercially available.

Source: ibm.com

Tuesday, 3 January 2023

Call Center Modernization with AI

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Picture this: A traveler sets off on a camping trip. She decides to extend her RV rental halfway through her trip, so she calls customer service for assistance, but finds herself waiting minutes, then what feels like hours. When she finally does get a hold of somebody, her call is redirected. More waiting follows. Suddenly her new plan doesn’t seem worth the aggravation. Now, imagine the same scenario from the agent’s perspective, dealing with a dissatisfied customer, scrambling for information that takes time to collect. Instances like these are far too common—the debacle ends up being costly for the company, and frustrating for both customer and agent.

Conversational AI solutions for customer service have come a long way, helping organizations meet customer expectations while reducing containment rates, complexity, and costs. It starts with bringing AI into the mix and ends with more cost-efficient operations and more satisfied customers.

So how can conversational AI help fulfill customer expectations in today’s ever-demanding landscape?


When you deploy conversational AI in your call center, you get:

1. Increased customer and agent satisfaction. Think of the example above—long wait times and unanswered questions can only lead to frustrated customers and agents and slower businesses. With leading natural language understanding (NLU) and automation leading to faster resolution, everybody wins.
2. Improved call resolution rates. AI and machine learning enable more self-service answers and actions and help route customers who need live agent support to the right place – continuously analyzing customer interactions to improve response. Agents benefit from this assistance too; empowering them to perform at their best when call traffic is high. Ultimately, improved resolution rates mean better customer experiences and improved brand reputation.
3. Reduced operational costs. With the capabilities of AI-powered virtual agents, you can contain up to 70% of calls without any human interaction and save an estimated USD 5.50 per contained call. This is money saved for your business, and time saved for your customers.

Not all AI platforms are built the same


On the lowest rung of the AI ladder, you have rules-based bots with limited response function. For example, you want to know if your telecom provider offers an unlimited data plan, so you call customer service and are given a set of basic questions following strict if-then scenarios—“…say yes if you want to review service plans; say yes if you want unlimited data.”

Climb up one rung, and there’s level two AI with machine learning and intent detection. You accidentally type “speal to an agenr”— but the virtual assistant understands your intention and responds properly: “I will connect you with an agent who can assist you.”

Then there’s IBM Watson® Assistant—the always-learning, highly resourceful virtual agent. Watson Assistant sits at the top—level three. Level three offers powerful AI that has unparalleled data and research capabilities.

The Watson Assistant deployed at Vodafone, the second-largest telecommunications company in Germany, exhibits level-three capacities—in addition to answering questions across a variety of platforms, such as WhatsApp, Facebook and RCS, Watson Assistant answers requests pulled from databases and can converse in multiple languages. It mines data, customizes interactions and is continuously learning. “*Insert Name*, transferring you to one of our agents who can answer your question about coverage abroad.” 

With Watson AI, you can expect more for your call center: 24/7 support, speedy response times and higher resolution rates. Seamlessly integrate your virtual agent with your existing back-end systems and processes, with every customer channel and touchpoint, without migrating your tech stack—IBM can meet you wherever you are in your customer service journey. Watson AI offers:

◉ Best-in-class NLU
◉ Intent detection
◉ Large language models
◉ Unsupervised learning
◉ Advanced analytics
◉ AI-powered agent assist
◉ Easy integration with existing systems
◉ Consulting services

All these features work in concert to redefine customer care at the speed of your business.

Why add complexity when you can simplify with AI? 


According to a Gartner® report, in 2031, conversational AI chatbots and virtual assistants will handle 30% of interactions that would have otherwise been handled by a human agent, up from 2% in 2022. To remain among the leaders, modern contact centers will need to keep up with AI innovations. Of course, like Watson, leading businesses are constantly learning, analyzing, and striving to become better.

Watson Assistant plugs into your company’s infrastructure, is reliable, easy to use, and always there to provide answers and self-service actions. Take Arvee, for example, an IBM Watson AI-powered virtual assistant for Camping World, the number one retailer of RVs. When customer demand surged early in the global pandemic, Camping World deployed Arvee in their call center and agent efficiency increased 33%.  Customer engagement also increased by 40%.

Similarly, IBM is working together with CcaaS providers like Nice to make it even simpler to build, deploy and scale AI-powered virtual voice agents.

Watson Assistant helps streamline processes and create agent efficiency—and when calls go to human agents, they can deliver higher quality personal service. Remember that aggravated customer from earlier? With the power and capabilities of Watson Assistant, she can enjoy her time camping—goodbye hold music, hello sounds of nature.

Source: ibm.com