Confronting the data challenges of ‘smart health’

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NSF’s Wendy Nilsen speaking at a South Big Data Hub Roundtable.

Each day countless devices—from monitors in hospitals to diagnostic tests to Fitbits—capture huge amounts of health data. That data could change how patients and doctors interact, how diseases are diagnosed and treated, and the amount of control individuals have over their health outcomes.

But there’s a catch, says Wendy Nilsen, PhD, program director of the Smart and Connected Health Initiative at the National Science Foundation.

The data is plentiful, Nilsen acknowledged. The challenge, she said, is how to make that data easier to use, how to standardize it so it can be analyzed, how to scale it, keep it safe, and how to account for external factors such as the environment or a person’s genome.

Nilsen discussed these challenges and how to address them in a roundtable discussion hosted by the South Big Data Hub on October 14. Nilsen’s talk, titled “Smart Health and Our Future” provides an overview of the challenges that must be addressed as well as the ultimate goal: A system where patients use data to take more control of their health and where healthcare practitioners can use data from multiple sources to improve diagnoses and health outcomes.

To view the presentation slides, click here.

Hackathon part of effort to make Orlando the ‘Smartest City’

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Participants in the Orlando Smart Cities Hackathon take time out for a group photo.

By Dan Ellen

On August 26 and 27, programmers and software engineers convened in Orlando to push the boundaries of creativity, innovation, reality, and technology to build solutions and concepts that have the potential to make a difference in the Orlando community.

Called the Orlando Smart Cities Hackathon, the event aimed to support the city of Orlando in its efforts to become a smart city and also to demonstrate the city’s capabilities as it works to earn the title of “The Smartest City.” Orlando received two smart cities grant awards and is pursuing a variety of additional funding opportunities for smart cities initiatives that would help to enhance transportation citywide and beyond. In these pursuits, the city continues to move forward with building a data-driven infrastructure that will support safer, cleaner, and more efficient travel and an improved quality of life.  Continue reading

Data science education in traditional contexts: Reflections on a recent webinar

On August 28, Karl Schmitt, PhD, an assistant professor in the department of mathematics and statistics at Valparaiso University, attended the webinar Data Science Education in Traditional Contexts, hosted by the South Big Data Innovation Hub as part of its Keeping Data Science Broad: Bridging the Data Divide series. The webinar featured five speakers, including Schmitt, who is also the director of data sciences at Valparaiso. Each speaker talked about their own programs and experiences in data science education as well as some of the challenges involved in creating and implementing educational programs in a field that is still very new and in the process of being defined. Continue reading

Big data and public health: New scenes and a new state of mind

Bigdatahealthcare-3By Eun Kyong Shin

The 2017 International Conference on Social Computing, Behavioral-Cultural Modeling, & Prediction and Behavior Representation in Modeling and Simulation (SBP-BRiMS 2017) was held in Washington, DC, in July, and prominent fields applying social computing techniques include public health and healthcare. In early modern epidemiology, data collection processes relied heavily on painstaking manual labor. Data on a large scale was hard to obtain and resulted from careful observation and intensive recording. Since the introduction of the internet and advances in digital communication, massive amounts of dynamic data have accumulated exponentially. Along with the digitization of medical practices and other social data collection process, the nature of scientific discovery has been fundamentally changed. Continue reading

Deep Learning to classify big data

By Sahar Tavakoli

Our brains do an expert job of classification; it happens when we recognize people from their faces, categorize an object that we see, or predict the future state of an event. Proportional to  the complexity of an input pattern, the classification can be easy (for example recognizing the difference between a cat and a dog) or difficult, such as predicting the probability of two people becoming friends in a social network. Continue reading

Visuals, storytelling help make sense of data

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Panelists discuss data visualization at a recent workshop sponsored by the South and West Big Data Hubs.

By Mark Schroeder

Throughout human history, stories have helped us make sense of sequences of events in our lives, infer cause and effect relationships, and share them with others. Just as our own memories are fallible and retelling stories can shape how we remember events, data can be fallible too. Its value is shaped by the process used to collect it and can be incomplete, incorrect, or biased in some fashion. How can we use data to gain true insights about the world and share them despite these challenges?

Continue reading

Mobile Health Workshop sparks ideas for future research

by Wenbin Zhang

Wenbin ZhangAs a first-year PhD student in information systems, I have been working on mobile health (mHealth) related research since the start of my PhD program. The growth of mHealth has facilitated better and instantaneous health communication, which was not previously possible. The capabilities of mHealth platforms promise to enhance healthcare quality and assist people in achieving healthy lifestyles at reduced costs. Attending the mHealth workshop organized by the South Big Data Hub and the National Consortium for Data Science (NCDS), located at the Renaissance Computing Institute (RENCI) deepened my understanding of mHealth, simply by having the chance to listen to and participate in intense discussions with an interdisciplinary group of mHealth and technology experts. Continue reading

South Hub and partners to hold data-driven storytelling webcast this Friday

The American Association for Advancement of Science (AAAS) Science & Technology Policy Fellowship Big Data Affinity Group, in collaboration with the South Big Data Hub, West Big Data Hub, and The National Consortium for Data Science, are making this Friday’s data visualization and storytelling event available for virtual attendees. To learn more about the event, visit the website or read our earlier blog post announcing the event.

Data-Driven Storytelling: A Deep Dive into Visualization Techniques 
July 14 | 9:00 AM – Noon ET | WebCast
Join the Webcast: http://bit.ly/datavizwebex
Call-in number:1-415-655-0003
Event Number: 641 886 660 | Event password: dataviz​

Developing Standards for Mobile Health

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Attendees at the mHealth conference discuss key issues, including mHealth standards, at a breakout session.

By Alex Cheng

I was honored to have the opportunity to attend the Mobile Health (mHealth) conference sponsored by the South Big Data Innovation Hub and the National Consortium for Data Science as a third-year graduate student in biomedical informatics at Vanderbilt University. My research focuses on using mHealth technology to improve the efficiency of outpatient clinic operations and the quality of care for patients.  Continue reading

Can wearable devices lead to better health outcomes?

Reflections on the South BD Hub mHealth Workshop

By Chenzhang Bao

mhealth-phone-e1498589419307.jpgIn recent years, mobile health (mHealth) has become one of the most popular health care movements for patients and providers. Consumers have embraced the use of mHealth applications in their daily lives through wearable devices, and use these apps to monitor their exercise routines, heartbeats, and sleep quality. The use of mHealth apps is critical for research into new mechanisms designed to improve the quality of patient engagement; a factor that has previously been hard to measure or even unobservable to providers. One important research question looks at the relationship between patients’ usage of mHealth devices, their engagement in their own health and the future health outcomes. Continue reading