AI (Artificial Intelligence) and Hypertension Research

被引:10
|
作者
Mueller, Franco B. [1 ]
机构
[1] New York Presbyterian Hosp, Dept Med, Div Nephrol & Hypertens, Weill Cornell Med Coll, 318 West 100th St,Box 8D, New York, NY 10025 USA
关键词
Artificial intelligence; Deep machine learning algorithms; Whole genome and RNA sequencing; Hypertension treatment; Gene and protein networks; Target molecules; Cancer and hypertension research publications; ANGIOTENSIN-CONVERTING ENZYME; MUTATIONS; DISEASE;
D O I
10.1007/s11906-020-01068-8
中图分类号
R6 [外科学];
学科分类号
1002 ; 100210 ;
摘要
Purpose of ReviewThis review a highlights that to use artificial intelligence (AI) tools effectively for hypertension research, a new foundation to further understand the biology of hypertension needs to occur by leveraging genome and RNA sequencing technology and derived tools on a broad scale in hypertension.Recent FindingsFor the last few years, progress in research and management of essential hypertension has been stagnating while at the same time, the sequencing of the human genome has been generating many new research tools and opportunities to investigate the biology of hypertension. Cancer research has applied modern tools derived from DNA and RNA sequencing on a large scale, enabling the improved understanding of cancer biology and leading to many clinical applications. Compared with cancer, studies in hypertension, using whole genome, exome, or RNA sequencing tools, total less than 2% of the number cancer studies. While true, sequencing the genome of cancer tissue has provided cancer research an advantage, DNA and RNA sequencing derived tools can also be used in hypertension to generate new understanding how complex protein network, in non-cancer tissue, adapts and learns to be effective when for example, somatic mutations or environmental inputs change the gene expression profiles at different network nodes. The amount of data and differences in clinical condition classification at the individual sample level might be of such magnitude to overwhelm and stretch comprehension. Here is the opportunity to use AI tools for the analysis of data streams derived from DNA and RNA sequencing tools combined with clinical data to generate new hypotheses leading to the discovery of mechanisms and potential target molecules from which drugs or treatments can be developed and tested.SummaryBasic and clinical research taking advantage of new gene sequencing-based tools, to uncover mechanisms how complex protein networks regulate blood pressure in health and disease, will be critical to lift hypertension research and management from its stagnation. The use of AI analytic tools will help leverage such insights. However, applying AI tools to vast amounts of data that certainly exist in hypertension, without taking advantage of new gene sequencing-based research tools, will generate questionable results and will miss many new potential molecular targets and possibly treatments. Without such approaches, the vision of precision medicine for hypertension will be hard to accomplish and most likely not occur in the near future.
引用
收藏
页数:7
相关论文
共 50 条
  • [1] AI (Artificial Intelligence) and Hypertension Research
    Franco B. Mueller
    [J]. Current Hypertension Reports, 2020, 22
  • [2] Artificial Intelligence in Education and Learning (AI in Research)
    Besimi, Nuhi
    Besimi, Adrian
    Cico, Betim
    [J]. 2022 11TH MEDITERRANEAN CONFERENCE ON EMBEDDED COMPUTING (MECO), 2022, : 613 - 618
  • [3] Scientometric Analysis of Artificial Intelligence (AI) for Geohazard Research
    Jiang, Sheng
    Ma, Junwei
    Liu, Zhiyang
    Guo, Haixiang
    [J]. SENSORS, 2022, 22 (20)
  • [4] Artificial Intelligence (AI) Research Assistants in der Praxis
    Kullmann, Sylvia
    Hiebl, Johannes
    [J]. INFORMATION-WISSENSCHAFT UND PRAXIS, 2024, 75 (01): : 32 - 33
  • [5] 'AI, Artificial Intelligence'
    Mendelsohn, F
    [J]. TLS-THE TIMES LITERARY SUPPLEMENT, 2001, (5139): : 20 - 20
  • [6] ARTIFICIAL INTELLIGENCE (AI)
    Robb, Hannah
    [J]. AUSTRALIAN LAW JOURNAL, 2024, 98 (03):
  • [7] Artificial Intelligence (AI)
    Kreienberg, Rolf
    Janni, Wolfgang
    Vetter, Klaus
    [J]. GYNAKOLOGE, 2021, 54 (07): : 468 - 470
  • [8] ARTIFICIAL INTELLIGENCE (AI)
    Layne, Armand
    [J]. INTELLIGENT SYSTEMS IN ACCOUNTING FINANCE & MANAGEMENT, 2005, 13 (03): : 179 - 181
  • [9] Application of Artificial Intelligence (AI) to cancer research and clinical practice
    Baba, Hideo
    Sese, Jun
    [J]. CANCER SCIENCE, 2018, 109 : 178 - 178
  • [10] The Impact of Artificial Intelligence (AI) Programs on Writing Scientific Research
    Hammad, Mohamed
    [J]. ANNALS OF BIOMEDICAL ENGINEERING, 2023, 51 (03) : 459 - 460