Artificial Intelligence for
Healthcare Applications

Most of the medical data collected from healthcare systems are recorded in digital format. The increased availability of these data has enabled a number of artificial intelligence applications. Specifically, machine learning can generate insights to improve the discovery of new therapeutics tools, to support diagnostic decisions, to help in the rehabilitation process, to name a few. Researchers coupled with expert clinicians can play an important role in turning complex medical data (e.g., genomic data, online acquisitions of physicians, medical imagery, etc.) into actionable knowledge that ultimately improves patient care. In the last years, these topics have drawn clinical and machine learning research which ultimately led to practical and successful applications in healthcare. The purpose of this workshop is to present recent advances in artificial intelligence techniques for healthcare applications.

• Biomedical image analysis
• Data analytics for healthcare
• Automatic disease prediction
• Automatic diagnosis support system
• Genomic and proteomic data analysis
• Artificial intelligence for personalized medicine
• Machine Learning as tool to support medical diagnoses and decisions
• Machine learning on handwriting and eye tracking traces for diagnosis and rehabilitation
• Decoding of neural signal for diagnosis assistance
• Physiological signals processing
• Gait analysis
• Therapy selection
• Brain computer interface for healthcare
• Biomechatronics for medicine
• Neuromotor rehabilitation

Accepted papers will be included in the ICPR 2020 Workshop Proceedings, which will be published by Springer in the Lecture Notes in Computer Science Series (LNCS).