Application of Artificial Intelligence in Disease Prediction and Healthcare

Dear Colleagues,

Artificial Intelligence has rapidly transformed modern healthcare by enabling early diagnosis, disease prediction and intelligent monitoring systems. In particular, neurological and developmental disorders such as Autism Spectrum Disorder, Parkinson’s Disease and Alzheimer’s Disease are becoming major global health challenges. Autism Spectrum Disorder is increasingly recognized as a significant concern in developing regions, including many Asian and African countries, where large child populations and limited healthcare resources create challenges for early screening and diagnosis. Meanwhile, Parkinson’s Disease and Alzheimer’s Disease are major concerns in aging societies such as Japan, Korea, the European Union and the United States. In addition to these disorders, other movement-related neurological conditions and brain disorders continue to affect millions of people worldwide. Recent advances in machine learning and deep learning have enabled researchers to detect and monitor these diseases using diverse multimodal data sources, including medical images, videos, skeleton and motion data, eye-tracking signals, handwriting patterns, physiological signals, wearable sensors, gait or foot pressure data and text-based behavioral information. Artificial Intelligence-based systems are also increasingly used for emotion recognition, brain and skin disease detection and intelligent health monitoring.

This Special Issue aims to present innovative research on Artificial Intelligence-driven healthcare technologies for disease detection and prediction across multiple domains. Beyond human healthcare, we also welcome studies on animal and crop diseases and aquatic health monitoring, which are critical to environmental sustainability, agriculture and global food security. Furthermore, this Special Issue encourages research on responsible and trustworthy Artificial Intelligence, including explainable Artificial Intelligence methods, ethical Artificial Intelligence practices and secure medical data processing frameworks to ensure reliability and transparency in healthcare applications.

By bringing together interdisciplinary research from healthcare, computer science, agriculture and life sciences, this Special Issue seeks to advance intelligent diagnostic systems that improve healthcare accessibility, early intervention and disease management worldwide.

Topics of interest include, but are not limited to, the following:

• Artificial intelligence techniques for healthcare analytics and disease prediction
• Machine learning and deep learning models for medical diagnosis
• Early detection of Autism Spectrum Disorder using Artificial Intelligence-based systems
• Artificial Intelligence-based detection and monitoring of Parkinson’s disease and movement disorders
• Artificial intelligence methods for Alzheimer’s disease diagnosis and progression prediction
• Medical image analysis using deep learning for disease identification
• Artificial Intelligence-based analysis of multimodal healthcare data (image, signal and text)
• Handwriting, gait and motion-based analysis for neurological disorder detection
• Eye-tracking and behavioral analysis for autism and cognitive disorder assessment
• Wearable sensor data analysis for health monitoring and disease prediction
• Emotion recognition using facial images, physiological signals, text, or video
• Artificial Intelligence-driven clinical decision support systems for healthcare applications
• Predictive modeling for chronic and neurodegenerative diseases
• Artificial Intelligence-enabled assistive technologies for healthcare and rehabilitation
• Detection and monitoring of crop diseases using computer vision and Artificial Intelligence
• Artificial Intelligence-based animal disease detection and livestock health monitoring
• Intelligent systems for aquatic and fish disease monitoring
• Artificial Intelligence approaches for skin disease and brain disease detection
• Explainable Artificial Intelligence and trustworthy Artificial Intelligence for healthcare applications
• Ethical, privacy-preserving and reliable Artificial Intelligence systems for medical data analysis

Dr. Abu Saleh Musa Miah
Guest Editor

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• artificial intelligence
• disease prediction
• healthcare applications
• deep learning
• explainable artificial intelligence