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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 a strong 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​​​​​​.  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.​

  1. Medical costs and the burden associated with cardiovascular disease are on the rise. Therefore, to improve the overall economy and quality assessment of the healthcare system, we developed a predictive model o...

    Authors: Tomoyuki Takura, Keiko Hirano Goto and Asao Honda
    Citation: BMC Medicine 2021 19:15
  2. Dementia is caused by a variety of neurodegenerative diseases and is associated with a decline in memory and other cognitive abilities, while inflicting an enormous socioeconomic burden. The complexity of deme...

    Authors: KongFatt Wong-Lin, Paula L. McClean, Niamh McCombe, Daman Kaur, Jose M. Sanchez-Bornot, Paddy Gillespie, Stephen Todd, David P. Finn, Alok Joshi, Joseph Kane and Bernadette McGuinness
    Citation: BMC Medicine 2020 18:398
  3. Evidence has pointed towards differences in the burden of arteriosclerosis according to its location and sex. Yet there is a scarcity of population-based data on aggregated sex-specific cardiovascular risk pro...

    Authors: Janine E. van der Toorn, Oscar L. Rueda-Ochoa, Niels van der Schaft, Meike W. Vernooij, M. Arfan Ikram, Daniel Bos and Maryam Kavousi
    Citation: BMC Medicine 2020 18:263
  4. Infective endocarditis is an uncommon but serious infection, where evidence for giving antibiotic prophylaxis before invasive dental procedures is inconclusive. In England, antibiotic prophylaxis was offered r...

    Authors: T. Phuong Quan, Berit Muller-Pebody, Nicola Fawcett, Bernadette C. Young, Mehdi Minaji, Jonathan Sandoe, Susan Hopkins, Derrick Crook, Timothy Peto, Alan P. Johnson and A. Sarah Walker
    Citation: BMC Medicine 2020 18:84
  5. Multimorbidity, the co-occurrence of two or more diseases in one patient, is a frequent phenomenon. Understanding how different diseases condition each other over the lifetime of a patient could significantly ...

    Authors: Nina Haug, Carola Deischinger, Michael Gyimesi, Alexandra Kautzky-Willer, Stefan Thurner and Peter Klimek
    Citation: BMC Medicine 2020 18:44
  6. There are an estimated 800,000 suicides per year globally, and approximately 16,000,000 suicide attempts. Mobile apps may help address the unmet needs of people at risk. We assessed adherence of suicide preven...

    Authors: Laura Martinengo, Louise Van Galen, Elaine Lum, Martin Kowalski, Mythily Subramaniam and Josip Car
    Citation: BMC Medicine 2019 17:231
  7. Clinical guidelines and public health authorities lack recommendations on scalable approaches to defining and monitoring the occurrence and severity of bleeding in populations prescribed antithrombotic therapy.

    Authors: Laura Pasea, Sheng-Chia Chung, Mar Pujades-Rodriguez, Anoop D. Shah, Samantha Alvarez-Madrazo, Victoria Allan, James T. Teo, Daniel Bean, Reecha Sofat, Richard Dobson, Amitava Banerjee, Riyaz S. Patel, Adam Timmis, Spiros Denaxas and Harry Hemingway
    Citation: BMC Medicine 2019 17:206
  8. Artificial intelligence (AI) research in healthcare is accelerating rapidly, with potential applications being demonstrated across various domains of medicine. However, there are currently limited examples of ...

    Authors: Christopher J. Kelly, Alan Karthikesalingam, Mustafa Suleyman, Greg Corrado and Dominic King
    Citation: BMC Medicine 2019 17:195
  9. Diagnostic codes from electronic health records are widely used to assess patterns of disease. Infective endocarditis is an uncommon but serious infection, with objective diagnostic criteria. Electronic health...

    Authors: Nicola Fawcett, Bernadette Young, Leon Peto, T. Phuong Quan, Richard Gillott, Jianhua Wu, Chris Middlemass, Sheila Weston, Derrick W. Crook, Tim E. A. Peto, Berit Muller-Pebody, Alan P. Johnson, A. Sarah Walker and Jonathan A. T. Sandoe
    Citation: BMC Medicine 2019 17:169
  10. The alpha-adrenergic agonist phenylephrine is often used to treat hypotension during anesthesia. In clinical situations, low blood pressure may require prompt intervention by intravenous bolus or infusion. Dif...

    Authors: Yanfei Zhang, S. Mark Poler, Jiang Li, Vida Abedi, Sarah A. Pendergrass, Marc S. Williams and Ming Ta Michael Lee
    Citation: BMC Medicine 2019 17:168
  11. 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
  12. 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

    The Correction to this article has been published in BMC Medicine 2019 17:158

  13. 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
  14. 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
  15. 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