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Service of Patient Health Care
  • by Team Handson
  • may 5th, 2022

Data Science at the Service of Patient Health Care.

Improving people’s lives based on data is one of our main goals at SAS
The Curiosity Data Science Iberian Awards was organized the first time together with SPAIN IA and the Data Science Portuguese Association (DSPA). It was dedicated to the Data4Good initiative.Leid Zejnilovic, Professor at NOVA School of Business and Economics in Lisbon and telecommunications engineer with a double PhD in Technological Evolution and Entrepreneurship, was the winner in this category. With more than two decades of experience in the technology industry, he is also President and co-founder of the Data Science Foundation for Social Good. He has dedicated part of his career to working to improve patient care in the healthcare sector.He has been awarded in the Data4Good category in the first edition of the SAS Iberia Curiosity Awards,

Can you explain to us what your project consists of?
This project aims to identify patients at high risk of developing diabetic nephropathy. According to data from the Portuguese National Diabetes Observatory, one in four people with diabetes will develop this condition chronically. This implies the reduction of blood flow that is filtered by the kidney. It also implies a significant loss in the quality of life of patients. With prior and adequate care, there is an opportunity to delay the progression of diabetic nephropathy. So early detection is crucial for the Portuguese Diabetes Association, partner and driver of this project. The goal of this organization was to determine if data science could assess risk and better identify high-risk individuals.Internally, we defined three phases for this project. The first is modelling. This consists of developing an algorithm that predicts the risk of patients with type 2 diabetes to develop chronic kidney disease over a 3–5-year horizon. The second step is to integrate the results of the model into the medical decision-making process. Finally, we would have a capacity building that the partner institution would be heavily involved in the process. As a result, is better to develop and implement Data Science projects. We are currently in the second phase of this project.

How can data science help improve patient care?
Patient care as a set of actions that includes the prevention, treatment and management. Data science offers a wide variety of opportunities for improvement at all stages of the process. Consider, for example, the case we described of using data science to prevent a disease from getting worse. Its use could be extended to monitoring and active training, suggesting treatments or personalized activities to the doctor or directly to the patient. All this considers the genetic and personal responses to different environmental stimuli. While we are all aware of the scalability problem of health services, it has become particularly evident during the pandemic.
A possible solution for the future would be to invest in technologies that improve patients’ access to care providers and encourage their autonomy. In this scenario, the patient would be actively involved in the responsible collection. Analysis of their data would become part of the decision-making process related to their health. Here, Data science is an instrumental part that allows:
• Socio-economic system for expansion, better reach, learning.
• An unprecedented level of patient empowerment.

Data4Good
Data4Good is an initiative that attaches great importance to the purpose for using the data. What do you think is the potential of artificial intelligence and data for social purposes? Data4Good is a great initiative that responds to the efforts of a community to promote the use of data in order to improve people’s lives. We share the belief that AI can help our society to become better. The reality is, there is still a long way to go if we think about its potential and what has been done so far,
Here, the most important benefit of AI is
• The opportunity to redesign service delivery from the ground up to make it more meaningful.
• It can help policy makers to identify and act on mismatches between the supply and demand of skills.
• Help citizens to plan their learning and help educational institutions to adapt their training offer.
The SAS Iberia Curiosity Award was created to recognize the curiosity of AI and data science professionals.

What influence has curiosity had on your career and your life?
Curiosity is the essential ingredient of progress, as it motivates people to challenge the status quo and enriches our lives. Learning and experimentation are the best ingredient for curiosity, and the academic world is a good playing field. Discovering why something is the way it looks and its way to improvement, motivates me to continue researching. This also enables the thought of about new impact projects. Well, everything might not be rosy. It takes curiosity to be in academia.

What does this identification mean to you personally and professionally?
This is the recognition of the work of an entire team, the members of the Portuguese Diabetes Association and the Data Science Knowledge Centre. The objective of their investigation was to find a solution to a problem of great impact. They submitted their application thanks to one of the team members, Lénia. She also convinced us of the importance of also sharing information about their work.

What would you say to someone who is considering entering the field of data science?
If someone is considering it, it means they already have some aspiration or interest in this field. It is true that knowledge of mathematics, programming and statistics is required to understand the concepts. There are many free and easily accessible sources of knowledge that can help develop skills at your own pace.
The good news is that the field of data science offers options for both profit-oriented individuals and those looking for social impact. It is an occupation that is likely to be in high demand for decades to come. The worst possible scenario is that you may discover that this field is not the most suitable. Even in that case, the acquired knowledge can be very valuable to succeed in other professional areas.