Cited by 57Artificial Intelligence in Healthcare and EducationInternet of Things and AIArtificial Intelligence in Healthcare

Artificial Intelligence in Healthcare: A New Technology Benefit for Both Patients and Doctors

Le Nguyen, Tran, Do, Thi Thu Ha·2019·2019 Portland International Conference on Management of Engineering and Technology (PICMET)

Abstract

Artificial Intelligence (AI) is arguably the most exciting robotics industry and it is recently emerging in healthcare. Most of the researches have been focusing on prediction algorithms of patients' diseases such as cancer, cardiology, breast pathology, etc. Some findings increased computer intelligence as the main application of AI which called deep or non-deep machine learning. The gap from previous models is using one function or one type of AI to analyze, forecast diseases rather than helping patients and doctors in surgery. There are rarely white papers using AI for patients approach to training them to know more about their diseases or surgery. Therefore, with developing of more than one function of AI, the paper builds a diagrammatic conceptual model of artificial intelligence on medical app running Blockchain technology as a friendly assistant for both patients and doctors to communicate them during pre-surgery, surgery and post-surgery. First, AI as an assistant checks free appointment from doctors and patients' available time. Second, AI reminds doctors' schedule of upcoming surgery list and training patients before taking surgery. Third, deep learning AI analyses patients' healthcare record and suggesting the solutions for patients after surgery under the doctor's review. This paper hopefully will contribute to AI application in healthcare in which not only doctors using it but also patients, drug companies, insurance companies and hospitals can approach.

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Crossref · 10.23919/picmet.2019.8893884

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  • Deep learning techniques are particularly useful in analyzing medical images due to their ability to recognize patterns and features that are not easily identifiable by humans.

    “DL techniques are particularly useful in analyzing medical images due to their ability to recognize patterns and features that are not easily identifiable by humans [11] .”

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Authors
Le Nguyen, T., & Do, T. T. H.
Affiliations
Ho Chi Minh City University of Economics and Finance (VN)
Venue
2019 Portland International Conference on Management of Engineering and Technology (PICMET)
Publisher
IEEE
Published
2019-08
Pages
1-15
OpenAlex
W2983648144
Cited by
57
References
0
Citations by year
2026: 6 · 2025: 6 · 2024: 21 · 2023: 3 · 2022: 5 · 2021: 16
FWCI
4.28
Type
conference paper
Language
en
Open access
closed
Locations
Portland International Conference on Management of Engineering and Technology (PICMET) (publishedVersion)
Topics
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
  • Physical Sciences › Computer Science › Information Systems › Internet of Things and AI
  • Health Sciences › Health Professions › Health Information Management › Artificial Intelligence in Healthcare
Keywords
artificial intelligence in healthcare, blockchain, mobile health apps, patient-doctor communication, deep learning, machine learning, appointment scheduling, patient education, electronic health records, conceptual model

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