Abstract Machine learning is frequently being leveraged to tackle problems in the health
sector including utilization for clinical decision-support. Its use has historically been focused …

Healthcare traditionally relies on single-modality approaches, which limit the information
available for medical decisions. However, advancements in technology and the availability …

Abstract Background and Objective: The automatic assessment of pain is vital in designing
optimal pain management interventions focused on reducing suffering and preventing the …

Emotion produces complex neural processes and physiological changes under appropriate
event stimulation. Physiological signals have the advantage of better reflecting a person's …

Pain assessment is used to improve patients' treatment outcomes. Human observers may be
influenced by personal factors, such as inexperience and medical organizations are facing a …

The development of non-contact patient monitoring applications for the neonatal intensive
care unit (NICU) is an active research area, particularly in facial video analysis. Recent …

With the power of parallel processing, large datasets, and fast computational resources,
deep neural networks (DNNs) have outperformed highly trained and experienced human …

Background Exposure to repetitive pain during the neonatal period has been shown to have
important short and long-term effects on the neurodevelopment of the premature neonate …

The advent of increasingly sophisticated medical technology, surgical interventions, and
supportive healthcare measures is raising survival probabilities for babies born premature …

This paper presents the first multimodal neonatal pain dataset that contains visual, vocal,
and physiological responses following clinically required procedural and postoperative …