Predictive Analytics World for Healthcare Berlin Agenda

Berlin - October 5-6, 2022

In January 2020, just after the first case of COVID-19 was discovered in the US, a multidisciplinary team of AI and medicine experts both in the US and China developed the first COVID-19 Clinical Severity Predictive Analytics Tool. In July 2021, another tool named COVID-19 Early-alerts Signals was built on a digital epidemiology framework that analyses alternative data sources to discover predictors of the pandemic curve. After the vaccine rollout, another team also co-led by the speaker developed a Vaccine Hesitancy Analytics Tool which is a real-time big data analytics cloud application to track misinformation and extract themes and topics related to vaccine hesitancy. In this keynote, Prof. Bari will outline the experimental research results from the three studies and the tools his team developed at New York University. This talk will also cover how governments and health systems can detect and respond to outbreaks, and how they can prepare for future pandemics using predictive analytics, mature AI capabilities, and infectious disease knowledge.

Over the past two years, ONE LOGIC supported a major Covid vaccine manufacturer and several government agencies in using data to reliably scale the Covid vaccine production and distribute doses to when and where they are needed. We believe this case study can be applied broadly across sensitive supply chains in biotech and pharma, but also on a global scale for issues like the current “chip crisis.

Classification is one of the most frequently solved problems using machine learning. Unfortunately, it cannot handle a case with a number of classes, varying over time, and require all the data to be labelled. There is another approach, designed to solve cases when we can’t perform full data annotation and/or would like to dynamically modify the number of classes. Similarity learning is capable of solving such problems even with extreme classification. We’re going to show how to use such models in production.

AI algorithms deteriorate and fail silently over time impacting the business’ bottom line. The talk is focused on learning how you should be monitoring machine learning in production. It is a conceptual and informative talk addressed to data scientists & machine learning engineers. We’ll learn about the types of failures, how to detect and address them.

Fraud can be considerably reduced via speed, scalability, and stability. Investigating fraudulent activities, using fraud detection machine learning is crucial where decisions need to be made in microseconds, not seconds or even milliseconds. This becomes more challenging when things get demanding and scaling real-time fraud detection becomes a bottleneck. The talk will address these issues and provide solutions using the Hazelcast Open Source platform.

Healthcare is about people- the patients receiving care, the people delivering it and those creating ways to support this. Data via predictive analytics is an enabler to supports a healthcare provider or system to achieve operational excellence to help problems thus faced by the people. Doing this well not only delivers patient outcomes but supports preventative and proactive population health management. In this table discussion, we would like to discuss these questions: What is the connection between operational excellence, predictive data analytics and artificial intelligence? What are the driving forces for achieving organizational performance by using artificial intelligence? What are the barriers to achieving organizational performance using artificial intelligence?

The changes in the ads ecosystem have led marketers to lean on existing aggregate experimentation tools that assume a predetermined treatment effect. Choosing the treatment group to ensure you have high chances of detecting an effect is non-trivial. Built by Meta Open Source, GeoLift solves this problem by building well powered geographical experiments. Join us to go over why geographical experiments are necessary and their implications in the marketing industry, along with a demo of GeoLift.

While pharma companies are increasingly realizing the value of data, they need to realize the importance of data mindset among non-data employees. Without the right mindset neither BI nor AI will be utilized. MSD has implemented a 3-year data literacy program to enable marketing and sales employees to understand customer data & insights and know how to use it. We are in the middle of this journey and will share the approaches we have used and our experience so far.