Guest Editors
Prof. Dr. Imran Ashraf
Email: imranashraf@ynu.ac.kr
Affiliation: Information and Communication Engineering, Yeungnam University, Gyeongsan 38541, Republic of Korea
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Research Interests: machine learning, deep learning, data analytics, bioinformatics, internet of medical things
Prof. Dr. Jin-Ghoo Choi
Email: jchoi@yu.ac.kr
Affiliation: Department of Information and Communication Engineering, Yeungnam University, Gyeongsan 38541, Republic of Korea
Homepage:
Research Interests: data mining, machine learning, deep learning, disease detection
Summary
Advancements in machine learning (ML) and data analysis are transforming the landscape of disease detection, diagnosis, and prognosis. The integration of artificial intelligence (AI) with medical imaging, genomics, electronic health records (EHRs), and wearable sensor data has enabled early and more accurate detection of various diseases, including cancer, cardiovascular disorders, neurological diseases, and infectious diseases.
1. Machine Learning Algorithms for Disease Detection
· Deep learning for medical imaging analysis (e.g., CNNs, Transformers, GANs).
· Explainable AI (XAI) for disease diagnosis and decision support.
· Reinforcement learning and federated learning applications in healthcare.
2. Data Analysis and Feature Engineering
· Big data analytics and predictive modeling for disease surveillance.
· Signal processing techniques for biomedical data (e.g., ECG, EEG, MRI, CT scans).
· Dimensionality reduction techniques in high-dimensional biomedical datasets.
3. Integration of Multi-Modal Data for Disease Prediction
· Fusion of medical imaging, genomic data, and EHRs for precision medicine.
· Sensor-based health monitoring and real-time anomaly detection.
4. Emerging Technologies and Applications
5. Challenges, Ethics, and Future Directions
· Bias and fairness in ML models for disease detection.
· Ethical considerations and privacy-preserving ML techniques.
· Regulatory challenges in deploying AI-based diagnostic tools.
· Future trends in AI-driven healthcare innovations.
Keywords
explainable AI, data analysis, machine learning, deep learning, data privacy, disease prognosis, disease prediction
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