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.1

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 personnel 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.

To learn more about how Innocens BV is putting data and AI to work, visit the case study and short documentary film here.

1 “New Research on Preventing Infant Deaths Due to Neonatal Sepsis.” University of Oxford. 

Was this article helpful?

More from Artificial intelligence

A new era in BI: Overcoming low adoption to make smart decisions accessible for all

5 min read - Organizations today are both empowered and overwhelmed by data. This paradox lies at the heart of modern business strategy: while there's an unprecedented amount of data available, unlocking actionable insights requires more than access to numbers. The push to enhance productivity, use resources wisely, and boost sustainability through data-driven decision-making is stronger than ever. Yet, the low adoption rates of business intelligence (BI) tools present a significant hurdle. According to Gartner, although the number of employees that use analytics and…

The power of remote engine execution for ETL/ELT data pipelines

5 min read - Business leaders risk compromising their competitive edge if they do not proactively implement generative AI (gen AI). However, businesses scaling AI face entry barriers. Organizations require reliable data for robust AI models and accurate insights, yet the current technology landscape presents unparalleled data quality challenges. According to International Data Corporation (IDC), stored data is set to increase by 250% by 2025, with data rapidly propagating on-premises and across clouds, applications and locations with compromised quality. This situation will exacerbate data silos, increase costs…

Where to begin: 3 IBM leaders offer guidance to newly appointed chief AI officers

4 min read - The number of chief artificial intelligence officers (CAIOs) has almost tripled in the last 5 years, according to LinkedIn. Companies across industries are realizing the need to integrate artificial intelligence (AI) into their core strategies from the top to avoid falling behind. These AI leaders are responsible for developing a blueprint for AI adoption and oversight both in companies and the federal government. Following a recent executive order by the Biden administration and a meteoric rise in AI adoption across…

IBM Newsletters

Get our newsletters and topic updates that deliver the latest thought leadership and insights on emerging trends.
Subscribe now More newsletters