sábado, 17 de agosto de 2019

Beyond big data to new biomedical and health data science: moving to next century precision health

Beyond big data to new biomedical and health data science: moving to next century precision health



Beyond Big Data to new Biomedical and Health Data Science: moving to next century precision health

Guest edited by Prof. Aziz Sheikh, Dr. Paul Wicks, Dr. Josip Car and Dr. Marc S. Williams
Big data image


The ability to gather data has become faster and cheaper over the last decade. This has led to an increasing amount of routinely generated data and advances in digital technology and biostatistical tools to examine and interpret these.
Big Data in Medicine can be used to provide health profiles and predictive models around individual patients. The use of high-throughput data to integrate genetic and clinical inter-relationships; real-world data to infer biological principles as well as associations, trajectories and stratifications of patients; data-driven approaches for patients and digital platforms are the hope for medical problems and evidence-based medicine.
We are inviting manuscripts that use data-driven approaches for patient care with astrong focus on policy making, clinical implementation and public health importance. Studies looking at data complexity, cost-effectiveness, new methods and tools, challenges facing Big Data in Medicine with the potential to transform medicine and the health system are of interest for this exciting collection.
We are delighted to work with four exceptional Guest Editors in this collection, all with different expertise:
  • Prof. Aziz Sheikh, Chair of Primary Care Research and Development at the University of Edinburgh and Director of The Usher Institute of Population Health and Informatics, has an interest in machine learning, data-enabled health policy making, transformation of care processes and precision medicine.
  • Dr. Paul Wicks, Vice President of Innovation at PatientsLikeMe, is interested in studies using real-world data (electronic health records, medical imaging and patient-generated health data), data sharing and data privacy.
  • Dr. Josip Car, Director of the Centre for Population Health Sciences in Singapore, is interested in how artificial intelligence and digital health are advancing medicine and population health, new analytical approaches and methods, and new data sources such as smartphones and the Internet of Things (IoT).  
  • Dr. Marc S. Williams, Director of the Geisinger Genomic Medicine Institute in Danville, PA, is interested in studies using high-throughput data, phenotyping, risk prediction and medical genomics with a focus on clinical implementation of big data.
We welcome direct submissions of original research or front matter content that meets the above described criteria. Please submit directly to BMC Medicine stating in your cover letter that you are targeting this collection. Alternatively, you can email your pre-submission queries (cover letter and abstract) to bmcmedicineeditorial@biomedcentral.com​​​​​​.  This collection will be open and accepting submissions until July 2020.
Guest Editors provided guidance on the scope of this collection and advised on commissioned content. However, they are not involved in editorial decision-making on papers submitted to this collection. All final editorial decisions are with the Editor-in-Chief, Dr. Lin Lee.​


  3. Content Type:Research Article

    Non-alcoholic fatty liver disease (NAFLD) is a common chronic liver illness with a genetically heterogeneous background that can be accompanied by considerable morbidity and attendant health care costs. The pa...
    Authors:Bahram Namjou, Todd Lingren, Yongbo Huang, Sreeja Parameswaran, Beth L. Cobb, Ian B. Stanaway, John J. Connolly, Frank D. Mentch, Barbara Benoit, Xinnan Niu, Wei-Qi Wei, Robert J. Carroll, Jennifer A. Pacheco, Isaac T. W. Harley, Senad Divanovic, David S. Carrell…
    Citation:BMC Medicine 2019 17:135
    Published on: 
  4. Content Type:Research Article

    Risk prediction models are commonly used in practice to inform decisions on patients’ treatment. Uncertainty around risk scores beyond the confidence interval is rarely explored. We conducted an uncertainty an...
    Authors:Alexander Pate, Richard Emsley, Darren M. Ashcroft, Benjamin Brown and Tjeerd van Staa
    Citation:BMC Medicine 2019 17:134
    Published on: 
    The Correction to this article has been published in BMC Medicine 2019 17:158
  5. Content Type:Debate

    There is great interest in and excitement about the concept of personalized or precision medicine and, in particular, advancing this vision via various ‘big data’ efforts. While these methods are necessary, th...
    Authors:Eric B. Hekler, Predrag Klasnja, Guillaume Chevance, Natalie M. Golaszewski, Dana Lewis and Ida Sim
    Citation:BMC Medicine 2019 17:133
    Published on: 
  6. Content Type:Research Article

    Smartphone apps are becoming increasingly popular for supporting diabetes self-management. A key aspect of diabetes self-management is appropriate medication-taking. This study aims to systematically assess an...
    Authors:Zhilian Huang, Elaine Lum, Geronimo Jimenez, Monika Semwal, Peter Sloot and Josip Car
    Citation:BMC Medicine 2019 17:127
    Published on: 
  8. Content Type:Forum

    Blockchain is a shared distributed digital ledger technology that can better facilitate data management, provenance and security, and has the potential to transform healthcare. Importantly, blockchain represen...
    Authors:Tim K. Mackey, Tsung-Ting Kuo, Basker Gummadi, Kevin A. Clauson, George Church, Dennis Grishin, Kamal Obbad, Robert Barkovich and Maria Palombini
    Citation:BMC Medicine 2019 17:68
    Published on: 
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