Onicio Leal Neto

Singularity Expert

Working with breakthrough innovation in healthcare for 12 years, I keep on the mission to accelerate the digital transformation in data-driven health and epidemiology. We built Epitrack, a science-based business, to bridge the gap between scientific knowledge and health needs. In this way we help society to experience these innovations in a more practical and relevant way for their lives. Besides that, I'm a researcher based at University of Zürich, building a bridge between academic research and innovation to solve real problems related to health.

Speaking Topics

Data stories: reducing the time to insight!

We live in a data-driven world that needs to leverage organizations, results and impact with data. We also experience an excess of techniques and tools to reach this goal. More specifically, data visualization tools need to be more understood to avoid creating more difficulties in decision-making due to exaggeration and overload of information presented. In contrast, the trend of data stories has been the new way of building narratives with contextualized data, shortening the path to better decisions.In addition, in applying Machine Learning for data analysis and decision-making, one cannotignore the Fairness and Bias aspects that these machines may have to avoid automating inequalities. In this session, which can have a lecture or workshop format, we address the need to reframe how hypotheses and data products are built to reduce understanding asymmetries within organizations. Methodologies such as Data Product Canvas, Data Stories and Experiment Design are current tools that need to be part of the routine of analytical teams. So that fragile foundations do not compromise the leverage of data. Aspects ofExplainable AIs (XAIs) are also addressed to tackle ethical challenges in implementing essential data analysis routines. The expected results of this session are the construction of a homogeneous level of understanding about these aspects of application methods, criticism, ethics and optimization of data routines.

How novel data streams are transforming Population Health

What if a time machine allowed us to travel back 30 years to share this outlook with the health industry at that time, we bet that no one would have believed it. Understanding how these technologies became feasible and widely accepted helps make sense of the past and anticipate what might be coming in the future. However, what is the use of advances in these technologies if they need to be better distributed globally, especially for those who need them most? In this section, we will explore the following topics: (1) main unexpected applications of data streams to population health; (2)understanding the importance of re-purposing technologies for the democratization of access to health; (3) point out the ethical and fairness challenges that artificial intelligence must consider in order not to automate inequalities; and (4) bring fresh perspectives on the global health challenges that lie ahead and what technologies will meet them.

Unlocking power of crowdsourcing to impact the Future of Health

The power of collaboration and data sharing has demonstrated a paradigm shift towards building more integrated societies in recent decades. The technologies that serve as crowdsourcing platforms in several industries are already well accepted by a large part of the population, being part of many people's daily routines. In health, crowdsourcing has also shown essential contributions to improving people's lives, either through the collective construction of health scenarios or through decentralized information on regions with a higher risk of illness and consequent improvement in disease prevention. But what next? In addition to self-reported data, what technologies can benefit from crowdsourcing to expand the impact on the global population? How to seek people's collaboration and citizenship mindset around a social good? What are the challenges to engaging social machines in the data-sharing economy? These are some aspects that will be discussed in this session, shedding light on the role of crowdsourcing in the future of healthcare.