Artificial Intelligence in Healthcare: Theory, Methods and Applications
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Bioelectronics".
Deadline for manuscript submissions: closed (30 August 2023) | Viewed by 12547
Special Issue Editors
Interests: data mining; machine learning; big data analytics; artificial intelligence
Special Issues, Collections and Topics in MDPI journals
Interests: network security; internet of things; medical image analysis; machine learning
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
A range of industries, particularly the healthcare sector, have been significantly impacted by Artificial Intelligence (AI). This cutting-edge technology is no longer just a dream. Instead, this rapidly developing technology has impacted our daily lives in ways we could never have predicted. AI in healthcare has the potential to help providers in many areas of patient care and operational procedures, enabling them to build on current solutions and solve problems more quickly. While it is anticipated that using AI in healthcare will be able to achieve equally successful or even better results than humans in some situations, such as diagnosing diseases, it will be a while before AI in healthcare completely replaces humans for a variety of medical applications. Compared to conventional methods of analytics and clinical decision making, AI offers a number of benefits. For instance, all diagnosis data will be gathered and used to better understand diseases in order to treat them more successfully. Reduced human error, accurate diagnosis and prediction, the treatment of rare diseases, the keeping of medical records, and many other advantages come with using AI for medical applications.
AI is also being used in conjunction with the growth of consumer wearables and other medical devices to monitor disease at an early stage, allowing doctors and other caregivers to more effectively monitor and identify potentially fatal episodes at earlier, more curable stages. NLP applications that can comprehend and categorize clinical documents are another popular application of artificial intelligence in the healthcare industry. Unstructured clinical notes can be analyzed by NLP systems, providing a wealth of knowledge that can be used to enhance procedures, comprehend quality, and provide better treatment for patients.
This Special Issue focuses on the use of AI in diagnosis, rehabilitation, and screening with the goal of demonstrating the cutting-edge applications of these technologies in the healthcare industry. The submissions can include but are not limited to the following topics with a focus on how they apply to healthcare applications:
- Challenges and opportunities of AI in the medical domain;
- Uses of AI in healthcare;
- Precision medicine and AI
- Therapies using AI during the pandemic;
- Wearable technology and AI for healthcare applications;
- Role of big data in medicine;
- AI-based decision support for healthcare applications;
- Computational intelligence and AI in healthcare;
- AI and medical image processing;
- Future of AI in medicine/healthcare;
- Ethical implications of AI in healthcare applications;
- Role of AI in vaccine and drug development;
- AI-enabled secure blockchain for healthcare applications;
- Healthcare data management;
- AI and virtual health assistance;
- Managing electronics health records and AI;
- NLP and AI in the healthcare domain.
The goal of this Special Issue is to foster innovative ideas in AI and bring them to the attention of researchers and scientists working with more advanced AI techniques.
Dr. Sathishkumar V E
Dr. Malliga Subramanian
Guest Editors
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Keywords
- big data analytics
- medical imaging
- medical data mining
- machine learning
- natural language processing
- predictive analytics
- deep learning
- artificial intelligence
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