Science, Technology, Engineering and Mathematics.
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COMPUTATIONAL MEDICINE - COPING WITH THE CHALLENGES OF BIG DATA AND CLINICAL TRANSFORMATION

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Volume 1, Issue 1, Pp 1-5, 2024

DOI: https://doi.org/10.61784/bcm3001

Author(s)

YunRu Lin

Affiliation(s)

School of Medicine, Shanghai Jiao Tong University, Shanghai 200030, Shanghai, China.

Corresponding Author

YunRu Lin

ABSTRACT

As an emerging interdisciplinary discipline, computational medicine aims to use computer science and information technology to cope with the challenges of medical big data and promote its clinical transformation. Computational medicine combines knowledge from multiple fields such as medicine, biology, computer science and data science to analyze and interpret large-scale medical data. Through advanced data analysis and machine learning techniques, computational medicine aims to discover biomarkers of diseases, predict disease risks, optimize treatment plans, etc. The amount of medical data is huge, including electronic health records, medical images, genomic data, etc. Computational medicine processes this data through efficient algorithms. Issues such as data heterogeneity, data quality, data security and privacy are key challenges that computational medicine needs to solve. Computational medicine supports clinical decision-making by mining big data, including personalized treatment, early diagnosis of diseases and risk prediction. Algorithm models based on big data can help doctors better understand disease mechanisms and develop precise treatment plans. Computational medicine tools such as medical image analysis and genomic data analysis can be directly applied to clinical practice to improve the quality and efficiency of medical services. Feedback from clinical trials and practical applications can further optimize computational medicine models and promote their clinical transformation. While responding to the challenges of medical big data, computational medicine is gradually transforming from research results to clinical applications, and is expected to provide more accurate and efficient support for medical services.

KEYWORDS

Computational medicine; Big data; Clinical medicine

CITE THIS PAPER

YunRu Lin. Computational medicine - coping with the challenges of big data and clinical transformation. Bioinformatics and Computational Medicine. 2024, 1(1): 1-5. DOI: https://doi.org/10.61784/bcm3001.

REFERENCES

[1] Jeff Cooper.  Waste: Striving for a more sustainable future. Local Environment, 2019.

[2] Fairley Mike. "Green" initiatives point to a more sustainable label future. Converting Magazine, 2006.

[3] Liu Guqun. Discussion on the Auxiliary Role of Multimedia in Chemical Experiment Teaching. CD Technology, 2009, 62.

[4] Li Anfeng, Lu Wei, Zhao Feng. Micro experiments and the reform of new chemistry curriculum standards. Chemistry Teaching, 2005(10): 4-6.

[5] David Pencheon. Delivering a more sustainable NHS: key strategies and policies. Journal of Renal Nursing, 2024: 589-590.

[6] Zhou Na. The Transformation of Teaching Methods for Chemistry Teachers in the Reform of New Curriculum Standards. Journal of Anhui Education College, 2004(3): 111-112.

[7] Chen Shijie, Li Jinlong, Bai Liming, et al. Research and Practice of Inorganic Chemistry Experimental Teaching System Based on Innovation and Entrepreneurship Talent Cultivation. Journal of Chemical Engineering, 2017, 31(7): 53-54.

[8] Han Jingchang. How to cultivate students' experimental exploration ability in chemistry teaching. Journal of Liaoning Education Administration College, 2007 (1): 156-158.

[9] Chen Shijie, Li Jinlong, Bai Liming, et al. Research and Practice of Inorganic Chemistry Experimental Teaching System Based on Innovation and Entrepreneurship Talent Cultivation. Journal of Chemical Engineering, 2017, 31(7): 53-54.

[10] Yasantha Abeysundara, Sandhya Babel. A quest for sustainable materials for building elements in Sri Lanka: Foundations. U.G. Environmental Progress & Sustainable Energy, 2016.

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