PharmiTech: Addressing Polypharmacy Challenges through AI-Driven Solutions

被引:0
|
作者
Martins, Andreia [1 ]
Vitorino, Joao [1 ]
Maia, Eva [1 ]
Praca, Isabel [1 ]
机构
[1] Polytech Porto ISEP IPP, Sch Engn, Res Grp Intelligent Engn & Comp Adv Innovat & Dev, P-4249015 Porto, Portugal
来源
APPLIED SCIENCES-BASEL | 2024年 / 14卷 / 19期
关键词
clinical decision support system; artificial intelligence; machine learning; herb-drug interactions; drug abuse detection; CLINICAL DECISION-SUPPORT; DRUG INTERACTIONS;
D O I
10.3390/app14198838
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Due to the rising prevalence of polypharmacy, pharmacists face more challenges in ensuring patient safety and optimizing medication management. This paper introduces PharmiTech, a Clinical Decision Support System that leverages Artificial Intelligence (AI) to tackle the growing need for efficient tools to assist pharmacists. The primary focus of the tool is to identify possible herb-drug interactions and instances of prescription drug abuse, combining an expert knowledge base with a supervised classification model and providing user-friendly alerts to pharmacists. To demonstrate the capabilities of the developed tool, this paper presents its functionalities through a case study involving simulated scenarios using de-identified information to maintain the confidentiality of real patients' personal data. Tested in Portuguese pharmacies, PharmiTech enhances pharmaceutical care, safeguards patient data, and aids pharmacists in informed decision-making, making it a valuable resource for healthcare professionals.
引用
收藏
页数:15
相关论文
共 50 条
  • [21] AI-driven techniques for controlling the metal melting production: a review, processes, enabling technologies, solutions, and research challenges
    Chadha, Utkarsh
    Selvaraj, Senthil Kumaran
    Raj, Aditya
    Mahanth, T.
    Praveen Vignesh, S. T.
    Lakshmi, Pasham Janani
    Samhitha, K.
    Reddy, Nagireddy Bharath
    Adefris, Addisalem
    MATERIALS RESEARCH EXPRESS, 2022, 9 (07)
  • [22] AI-driven smile designing
    Kurian, N.
    Sudharson, N. A.
    Varghese, K. G.
    BRITISH DENTAL JOURNAL, 2024, 236 (03) : 146 - 146
  • [23] Empowering the AI-Driven Laboratory
    Meek, Trish
    Gioioso, Marisa
    LCGC NORTH AMERICA, 2023, 41 (11) : 470 - 471
  • [24] Alienation in the AI-Driven Workplace
    Vredenburgh, Kate
    AIES '21: PROCEEDINGS OF THE 2021 AAAI/ACM CONFERENCE ON AI, ETHICS, AND SOCIETY, 2021, : 266 - 266
  • [25] AI-DRIVEN MANAGEMENT OF SUBMASSIVE PE ADVANCES BEYOND INITIAL APPROACH FOR AI-DRIVEN DIAGNOSIS
    Abide, Aimee
    CRITICAL CARE MEDICINE, 2025, 53 (01)
  • [26] Regulate or Revise: Addressing Algorithmic Bias in AI-driven Residential Mortgage Underwriting in Australia
    Yardi, Sonali
    JOURNAL OF BANKING AND FINANCE LAW AND PRACTICE, 2024, 34 (01):
  • [27] Explainable AI-driven IoMT fusion: Unravelling techniques, opportunities, and challenges with Explainable AI in healthcare
    Wani, Niyaz Ahmad
    Kumar, Ravinder
    Mamta
    Bedi, Jatin
    Rida, Imad
    INFORMATION FUSION, 2024, 110
  • [28] Towards AI-Driven Software Development: Challenges and Lessons from the Field (Keynote)
    Yahav, Eran
    PROCEEDINGS OF THE 31ST ACM JOINT MEETING EUROPEAN SOFTWARE ENGINEERING CONFERENCE AND SYMPOSIUM ON THE FOUNDATIONS OF SOFTWARE ENGINEERING, ESEC/FSE 2023, 2023, : 1 - 1
  • [29] AI-driven innovations for enhancing mental health care in Tanzania: opportunities and challenges
    Mwogosi, Augustino
    Mambile, Cesilia
    Shao, Deo
    Kibinda, Nyaura
    MENTAL HEALTH AND SOCIAL INCLUSION, 2024,
  • [30] Enhancing Student Scholarly Writing Through AI-Driven Teaching Strategies
    Fritz, Ashlie
    Toothaker, Rebecca
    NURSE EDUCATOR, 2025,