Application of Artificial Intelligence in the Diagnosis, Treatment and Management of Diseases

Dear Colleagues,

Artificial Intelligence (AI) has evolved to offer great possibilities for improving the health of millions of people worldwide. Today, AI can be used to improve the speed and accuracy of diagnosis and early disease detection; facilitate clinical care; strengthen health research and drug development; and support various public health interventions, such as morbidity surveillance, outbreak response, and health systems management. AI also enables self-management of health, i.e., patients having greater control over their healthcare and a better understanding of their evolving needs. In addition, AI could facilitate access to health services in resource-poor countries and rural communities, where patients often have difficulty accessing health workers or medical staff.

One of the priorities of the World Health Organization is to highlight the need for accessible, affordable, and quality healthcare for everyone everywhere. Hence, the e-health services of the future that incorporate AI become vitally important, because, in addition to supporting specialists in healthcare, they will comprehensively include services for prevention, diagnosis, and follow-up of medical treatments. This will help to save lives, anticipate diseases, and optimize costs. Finally, although the global pandemic accelerated many digital initiatives to improve daily life, it also left many health systems with digital deficiencies in chaos, mainly in developing countries; thus, it is important to ensure that the global health sector has the necessary maturity for AI-based digital advances that will produce an exponential increase in the application of digital solutions in healthcare.

This Special Issue aims to collect and consolidate innovative and high-quality research contributions related to Artificial Intelligence in healthcare across different disciplines and its challenges, such as the personalized diagnosis, treatment, and management of diseases. AI in medical imaging and video has improved the efficiency of clinical trials; enhanced the early detection of disease; supported the diagnosis, treatment, and management and f-management of various diseases; improved clinical decision support, telehealth, and healthcare informatics systems; and optimized the generation of clinical expedients, among others.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

• Chatbots applied to mental health support, symptom assessment, patient triage, health education, medication management, and supporting telehealth services.
• Computer vision applied to medical imaging for the precise localization, segmentation, and sizing of tumors, eyes, and skin and bone diseases, among others.
• Data mining applied to predictive analytics, early detection, diagnosis, and forecasting of diseases.
• Deep learning models to audit prescriptions vs. patient health records to identify and correct possible diagnostic errors or errors in prescription.
• Deep learning techniques applied to the detection and diagnosis of diseases through the analysis of medical image data to acquire information for treatment planning and monitoring disease progression.
• Expert medical systems to improve patient care by providing recommendations for medical decision making.
• Fuzzy logic applicable for developing knowledge-based systems in medicine for tasks such as the interpretation of sets of medical findings and the diagnosis of diseases.
• Machine learning applications for predictive analysis of disease outbreaks in a population and pattern detection for early disease diagnosis.
• Natural Language Processing applied to personalized patient care and to obtaining medical information from free text for relevant medical treatments.
• Robotics applied to surgical treatments, including minimally invasive surgeries, orthopedic surgeries, and rehabilitation.

We look forward to receiving insightful contributions.

Prof. Dr. José Luis Sánchez-Cervantes
Prof. Dr. Giner Alor-Hernández
Dr. Jezreel Mejía-Miranda
Guest Editors

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• artificial intelligence
• deep learning
• e-health
• intelligent systems
• m-health
• machine learning
• smart health
• vision transformer architectures
• data mining
• fuzzy logic
• natural language processing
• robotics
• expert systems