The 2nd International Workshop on Pattern Recognition in Healthcare Analytics
In conjunction with the 15th Asian Conference on Machine Learning
Aim and Scope
A vast amount of digital health data has become accessible to clinical and machine learning researchers. Thus, healthcare has become a prominent field that benefits from data-driven techniques. In parallel, machine learning for healthcare has emerged to develop models to assist physicians and clinical researchers in solving complex healthcare tasks and clinical decision-making. Machine learning and deep learning-based approaches have been successfully applied to various healthcare tasks, such as risk prediction and diagnosis prediction. However, digital patient data retain multiple challenges. For instance, high-dimensional, non-linear, temporal, distributed, and sensitive patient data pose additional requirements while designing machine learning models. The 2nd PRHA workshop aims to showcase the emerging challenges in bioinformatics and digital health with their latest solutions in machine learning and provide an outlet for interdisciplinary collaborations. The workshop's scope entails but is not limited to
Bioinformatics
Patient phenotyping and subtyping
Patient monitoring, machine learning in pervasive healthcare
Multi-modal learning for disease prediction and treatment effects
Temporal modeling for disease progression
Interpretable models for clinical decision support
Privacy-preserving techniques for distributed and sensitive patient data
Important Dates
Submission: October 8, 2023 October 15, 2023
Notification: October 29, 2023, October 30, 2023
Workshop: November 11, 2023