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Big data medicine

Jason H Moore, Mary Regina Boland, Pablo G Camara, Hannah Chervitz, Graciela Gonzalez, Blanca E Himes, Dokyoon Kim, Danielle L Mowery, Marylyn D Ritchie, Li Shen, Ryan J Urbanowicz, John H Holmes
Personalized medicine is being realized by our ability to measure biological and environmental information about patients. Much of these data are being stored in electronic health records yielding big data that presents challenges for its management and analysis. Here, we review several areas of knowledge that are necessary for next-generation scientists to fully realize the potential of biomedical big data. We begin with an overview of big data and its storage and management. We then review statistics and data science as foundational topics followed by a core curriculum of artificial intelligence, machine learning and natural language processing that are needed to develop predictive models for clinical decision making...
February 14, 2019: Personalized Medicine
Enrico Capobianco
Changes and transformations enabled by Big Data have direct effects on Translational Medicine. At one end, superior precision is expected from a more data-intensive and individualized medicine, thus accelerating scientific discovery and innovation (in diagnosis, therapy, disease management etc.). At the other end, the scientific method needs to adapt to the increased diversity that data present, and this can be beneficial because potentially revealing greater details of how a disease manifests and progresses...
February 12, 2019: Journal of Translational Medicine
Yuzhuo Zhao, Xiaoke Zhao, Fei Pan, Zhihong Zhu, Lijing Jia, Cong Feng, Kaiyuan Li, Jing Li, Zhengbo Zhang, Tanshi Li
Medical big data is a hot research topic in China, and it is also the main research direction in the field of emergency medicine. The current situation of the construction of the first-aid big data platform and the construction of the first-aid clinical decision support system were analyzed, the problems existing in the development of the first-aid big data research field were enumerated, to explore the theoretical methods for promoting the development of domestic first-aid big data, so as to provide references for the research in related fields...
January 2019: Zhonghua Wei Zhong Bing Ji Jiu Yi Xue
Bilal Mirza, Wei Wang, Jie Wang, Howard Choi, Neo Christopher Chung, Peipei Ping
Recent developments in high-throughput technologies have accelerated the accumulation of massive amounts of omics data from multiple sources: genome, epigenome, transcriptome, proteome, metabolome, etc. Traditionally, data from each source (e.g., genome) is analyzed in isolation using statistical and machine learning (ML) methods. Integrative analysis of multi-omics and clinical data is key to new biomedical discoveries and advancements in precision medicine. However, data integration poses new computational challenges as well as exacerbates the ones associated with single-omics studies...
January 28, 2019: Genes
V Mohan, Venkatesan Radha
The concept of precision medicine is becoming increasingly popular. The use of big data, genomics and other 'omics' like metabolomics, proteomics and trancriptomics could make the dream of personalized medicine become a reality in the near future. As far as polygenic forms of diabetes like type 2 diabetes (T2DM) and type 1 diabetes (T1DM) are concerned, interesting leads are emerging, but precision diabetes is still in its infancy. However, with regard to monogenic forms of diabetes like Maturity-Onset-diabetes of the young (MODY) and Neonatal Diabetes Mellitus (NDM), rapid strides have been made and precision diabetes has already become part of the clinical tools used at advanced diabetes centres...
January 27, 2019: Medical Principles and Practice: International Journal of the Kuwait University, Health Science Centre
J L García Garmendia
The series of updates on methodology for research in critically ill patients has addressed the difficulties caused by the characteristics of patients of this kind, bioethics, the interpretation of results, and methodological error. New statistical methods for causality research, meta-analysis and big data analysis have also been described. The last update refers to the horizon for new research in the field of critical care. We close the series with the hope of having provided a global vision of the statistical methods oriented toward the future, with the aim of promoting statistical culture...
January 21, 2019: Medicina Intensiva
Nuria Oliver, Oscar Mayora, Michael Marschollek
INTRODUCTION: This accompanying editorial provides a brief introduction to this focus theme, focused on "Machine Learning and Data Analytics in Pervasive Health". OBJECTIVE: The innovative use of machine learning technologies combining small and big data analytics will support a better provisioning of healthcare to citizens. This focus theme aims to present contributions at the crossroads of pervasive health technologies and data analytics as key enablers for achieving personalised medicine for diagnosis and treatment purposes...
September 2018: Methods of Information in Medicine
Jia Xu, Pengwei Yang, Shang Xue, Bhuvan Sharma, Marta Sanchez-Martin, Fang Wang, Kirk A Beaty, Elinor Dehan, Baiju Parikh
In the field of cancer genomics, the broad availability of genetic information offered by next-generation sequencing technologies and rapid growth in biomedical publication has led to the advent of the big-data era. Integration of artificial intelligence (AI) approaches such as machine learning, deep learning, and natural language processing (NLP) to tackle the challenges of scalability and high dimensionality of data and to transform big data into clinically actionable knowledge is expanding and becoming the foundation of precision medicine...
January 22, 2019: Human Genetics
Nicola Luigi Bragazzi, Ottavia Guglielmi, And Sergio Garbarino
Sleep disorders have reached epidemic proportions worldwide, affecting the youth as well as the elderly, crossing the entire lifespan in both developed and developing countries. "Real-life" behavioral (sensor-based), molecular, digital, and epidemiological big data represent a source of an impressive wealth of information that can be exploited in order to advance the field of sleep research. It can be anticipated that big data will have a profound impact, potentially enabling the dissection of differences and oscillations in sleep dynamics and architecture at the individual level ("sleepOMICS"), thus paving the way for a targeted, "one-size-does-not-fit-all" management of sleep disorders ("precision sleep medicine")...
January 21, 2019: International Journal of Environmental Research and Public Health
Pablo Olivera, Silvio Danese, Nicolas Jay, Gioacchino Natoli, Laurent Peyrin-Biroulet
Big data methodologies, made possible with the increasing generation and availability of digital data and enhanced analytical capabilities, have produced new insights to improve outcomes in many disciplines. Application of big data in the health-care sector is in its early stages, although the potential for leveraging underutilized data to gain a better understanding of disease and improve quality of care is enormous. Owing to the intrinsic characteristics of inflammatory bowel disease (IBD) and the management dilemmas that it imposes, the implementation of big data research strategies not only can complement current research efforts but also could represent the only way to disentangle the complexity of the disease...
January 18, 2019: Nature Reviews. Gastroenterology & Hepatology
Samuel M Rubinstein, Jeremy L Warner
Rapid-learning health systems have been proposed as a potential solution to the problem of quality in medicine, by leveraging data generated from electronic health systems in near-real time to improve quality and reduce cost. Given the complex, dynamic nature of cancer care, a rapid-learning health system offers large potential benefits to oncology practice. In this article, we review the rationale for developing a rapid-learning health system for oncology and describe the sequence of events that led to the development of ASCO's CancerLinQ (Cancer Learning Intelligence Network for Quality) initiative, as well as the current state of CancerLinQ, including its importance to efforts such as the Beau Biden Cancer Moonshot...
December 2018: JCO Clinical Cancer Informatics
Si Yuan Chew, Mariko S Koh, Chian Min Loo, Julian Thumboo, Sumitra Shantakumar, David B Matchar
Clinical practice guidelines (CPGs) have become ubiquitous in every field of medicine today but there has been limited success in implementation and improvement in health outcomes. Guidelines are largely based on the results of traditional randomised controlled trials (RCTs) which adopt a highly selective process to maximise the intervention's chance of demonstrating efficacy thus having high internal validity but lacking external validity. Therefore, guidelines based on these RCTs often suffer from a gap between trial efficacy and real world effectiveness and is one of the common reasons contributing to poor guideline adherence by physicians...
December 2018: Annals of the Academy of Medicine, Singapore
Eric J Topol
The use of artificial intelligence, and the deep-learning subtype in particular, has been enabled by the use of labeled big data, along with markedly enhanced computing power and cloud storage, across all sectors. In medicine, this is beginning to have an impact at three levels: for clinicians, predominantly via rapid, accurate image interpretation; for health systems, by improving workflow and the potential for reducing medical errors; and for patients, by enabling them to process their own data to promote health...
January 2019: Nature Medicine
Michael V Lombardo, Meng-Chuan Lai, Simon Baron-Cohen
Autism is a diagnostic label based on behavior. While the diagnostic criteria attempt to maximize clinical consensus, it also masks a wide degree of heterogeneity between and within individuals at multiple levels of analysis. Understanding this multi-level heterogeneity is of high clinical and translational importance. Here we present organizing principles to frame research examining multi-level heterogeneity in autism. Theoretical concepts such as 'spectrum' or 'autisms' reflect non-mutually exclusive explanations regarding continuous/dimensional or categorical/qualitative variation between and within individuals...
January 7, 2019: Molecular Psychiatry
Y Z Zhang
The development of medicine technology is supported by the progress of materials, electronics, machinery, physics and other related fields.The article mainly reviews the research achievements of traumatic orthopedics from four aspects: big data, new theory, new technology and new implants. The prospects of intelligent minimally invasive, new materials, three-dimensional printing technology, surgical assistant robot of fracture reduction, digital orthopedics and other aspects are presented.Aiming at improving the treatments of traumatic orthopedics in China, this paper tracks the frontier of the orthopedics and absorbed advanced concepts and technologies of treatments on traumatic orthopedics in the world...
January 1, 2019: Zhonghua Wai Ke za Zhi [Chinese Journal of Surgery]
G B Mitropoulos
The use of diagnostic manuals in psychiatry is generally necessitated by the lack of tests that would corroborate psychiatric diagnosis. Criticism towards the today prevailing DSM-ICD diagnosis traditionally regards among others such problems as hyponarrativity, biologism, "death of phenomenology", and a questionably valid over-fragmentation of diagnosis. Lately, and especially after the appearance of the 5th edition of DSM (2013), criticism focuses at such issues as lack of validity, having failed to adopt a dimensional model, not adequately relying on genetics and neurobiology, and impeding, rather than facilitating, research into the etiology of mental disorders, the DSM becoming an "epistemic prison"...
July 2018: Psychiatrikē, Psychiatriki
Andreas S Panayides, Marios Pattichis, Stephanos Leandrou, Costas Pitris, Anastasia Constantinidou, Constantinos S Pattichis
Precision medicine promises better healthcare delivery by improving clinical practice. Using evidence-based sub-stratification of patients, the objective is to achieve better prognosis, diagnosis, and treatment that will transform existing clinical pathways towards optimizing care for the specific needs of each patient. The wealth of today's healthcare data, often characterized as big data, provides invaluable resources towards new knowledge discovery that has the potential to advance precision medicine. The latter requires interdisciplinary efforts that will capitalize the information, know-how, and medical data of newly formed groups fusing different backgrounds and expertise...
December 25, 2018: IEEE Journal of Biomedical and Health Informatics
Mattia Prosperi, Jae S Min, Jiang Bian, François Modave
BACKGROUND: Nowadays, trendy research in biomedical sciences juxtaposes the term 'precision' to medicine and public health with companion words like big data, data science, and deep learning. Technological advancements permit the collection and merging of large heterogeneous datasets from different sources, from genome sequences to social media posts or from electronic health records to wearables. Additionally, complex algorithms supported by high-performance computing allow one to transform these large datasets into knowledge...
December 29, 2018: BMC Medical Informatics and Decision Making
William S Weintraub, Akl C Fahed, John S Rumsfeld
No abstract text is available yet for this article.
November 9, 2018: Circulation Research
Fatima Rodriguez, David Scheinker, Robert A Harrington
No abstract text is available yet for this article.
December 7, 2018: Circulation Research
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