Artificial Intelligence in Healthcare: A New Technology Benefit for Both Patients and Doctors
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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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] .”
From Artificial intelligence, machine learning and deep learning in advanced robotics, a review (2023) · cites this paper as [11]
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Artificial intelligence, machine learning and deep learning in advanced robotics, a review
Soori, M., Arezoo, B., & Dastres, R. (2023) · Cognitive Robotics · doi:10.1016/j.cogr.2023.04.001 · Cited by 1,131 · see citing works
Benefits and Risks of AI in Health Care: Narrative Review
Chustecki, M. (2024) · Interactive Journal of Medical Research · doi:10.2196/53616 · Cited by 208 · see citing works
Saihi, A., Ben-Daya, M., Hariga, M., & As'ad, R. (2024) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2024.100274 · Cited by 75 · see citing works
Equity and AI Governance at Academic Medical Centers
(2024) · The American Journal of Managed Care · doi:10.37765/ajmc.2024.89555 · Cited by 8 · see citing works
- Authors
- Le Nguyen, T., & Do, T. T. H.
- Affiliations
- Ho Chi Minh City University of Economics and Finance (VN)
- ORCID
- Do, Thi Thu Ha
- 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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