Biomedical data analytics for better patient outcomes

被引:0
|
作者
Ghofrani, Alireza [1 ]
Taherdoost, Hamed [1 ,2 ,3 ,4 ]
机构
[1] Hamta Business Corp, Vancouver, BC, Canada
[2] Univ Canada West, Vancouver, BC, Canada
[3] Westcliff Univ, Irvine, CA 92614 USA
[4] Global Univ Syst, GUS Inst, London, England
关键词
clinical practice; patient care enhancement; data sources; health-care innovation; medical decision-making; QUALITY-OF-LIFE; BIG DATA; HEALTH; CARE; DISEASE; CLASSIFICATION; FRAMEWORK; PATTERNS; MODELS;
D O I
10.1016/j.drudis.2024.104280
中图分类号
R9 [药学];
学科分类号
1007 ;
摘要
Medical professionals today have access to immense amounts of data, which enables them to make decisions that enhance patient care and treatment efficacy. This innovative strategy can improve global health care by bridging the divide between clinical practice and medical research. This paper reviews biomedical developments aimed at improving patient outcomes by addressing three main questions regarding techniques, data sources and challenges. The review includes peer-reviewed articles from 2018 to 2023, found via systematic searches in PubMed, Scopus and Google Scholar. The results show diverse disease-specific applications. Challenges such as data quality and ethics are discussed, underscoring data analytics' potential for patient-focused health care. The review concludes that successful implementation requires addressing gaps, collaboration and innovation in biomedical science and data analytics.
引用
收藏
页数:19
相关论文
共 50 条
  • [1] Temporal biomedical data analytics
    Moskovitch, Robert
    Shahar, Yuval
    Wang, Fei
    Hripcsak, George
    JOURNAL OF BIOMEDICAL INFORMATICS, 2019, 90
  • [2] From big data to better patient outcomes
    Hulsen, Tim
    Friedecky, David
    Renz, Harald
    Melis, Els
    Vermeersch, Pieter
    Fernandez-Calle, Pilar
    CLINICAL CHEMISTRY AND LABORATORY MEDICINE, 2023, 61 (04) : 580 - 586
  • [3] The Ethics of Biomedical ‘Big Data’ Analytics
    Brent Mittelstadt
    Philosophy & Technology, 2019, 32 (1) : 17 - 21
  • [4] Improving Patient Outcomes in Gynecology: The Role of Large Data Registries and Big Data Analytics
    Erekson, Elisabeth A.
    Iglesia, Cheryl B.
    JOURNAL OF MINIMALLY INVASIVE GYNECOLOGY, 2015, 22 (07) : 1124 - 1129
  • [5] A Review of Big Data Analytics in the Biomedical Field
    Jatmiko, Wisnu
    Arsa, Dewa Made Sri
    Wisesa, Hanif
    Jati, Grafika
    Ma'sum, M. Anwar
    2016 INTERNATIONAL WORKSHOP ON BIG DATA AND INFORMATION SECURITY (IWBIS), 2016, : 31 - 39
  • [6] Translating Data Analytics Into Improved Spine Surgery Outcomes: A Roadmap for Biomedical Informatics Research in 2021
    Greenberg, Jacob K.
    Otun, Ayodamola
    Ghogawala, Zoher
    Yen, Po-Yin
    Molina, Camilo A.
    Limbrick, David D., Jr.
    Foraker, Randi E.
    Kelly, Michael P.
    Ray, Wilson Z.
    GLOBAL SPINE JOURNAL, 2022, 12 (05) : 952 - 963
  • [7] The age of data analytics: converting biomedical data into actionable insights
    Veselkov, Kirill
    Schuller, Bjoern
    METHODS, 2018, 151 : 1 - 2
  • [8] Private Data Analytics on Biomedical Sensing Data via Distributed Computation
    Gong, Yanmin
    Fang, Yuguang
    Guo, Yuanxiong
    IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS, 2016, 13 (03) : 431 - 444
  • [9] Better-Not Just Bigger-Data Analytics
    Nallamothu, Brahmajee K.
    CIRCULATION-CARDIOVASCULAR QUALITY AND OUTCOMES, 2017, 10 (07):
  • [10] Data Analytics for Better Informed Technology & Engineering Management
    Porter A.L.
    IEEE Engineering Management Review, 2019, 47 (03): : 29 - 32