Fuzzy-Inspired Sensing for Time-Domain Brain Stroke Diagnosis: Disease Retrospective Monitoring Strategy.

This paper propose a novel disease retrospective monitoring strategy (DRMS) for optimal brain stroke diagnosis. We describe the disease monitoring process using a fuzzy-based model and demonstrate the use of information at different time points to improve disease diagnosis accuracy under the framework of fuzzy-inspired sensing (FIS). Numerical examples are used to demonstrate how the proposed DRMS can be used to determine the optimal treatment strategy with the least amount of fuzziness.

Automated Prediction of Infant Cognitive Development Risk by Video: A Pilot Study.

Objective: Cognition is an essential human function, and its development in infancy is crucial. Traditionally, pediatricians used clinical observation or medical imaging to assess infants' current cognitive development (CD) status. The object of pediatricians' greater concern is however their future outcomes, because high-risk infants can be identified early in life for intervention.

Stability Analysis of fMRI BOLD Signals for Disease Diagnosis.

Previous studies have demonstrated that the stability changes in physiological signals can reflect individuals' pathological conditions. Apart from this, according to system science theory, a large-scale system can generally be divided into many subsystems whose stability level govern its overall performance. Therefore, this study attempts to investigate the possibility of analyzing the stability of decomposed subsystems of resting-state fMRI (rs-fMRI) BOLD signals in order to assess the overall characteristic of the human brain and individuals' health conditions.

Implementing the Risk Identification (RI) and Modified Early Obstetric Warning Signs (MEOWS) tool in district hospitals in Rwanda: a cross-sectional study.

Background: Despite reaching Millennium Development Goal (MDG) 3, the maternal mortality rate (MMR) is still high in Rwanda. Most deaths occur after transfer of patients with obstetric complications from district hospitals (DHs) to referral hospitals; timely detection and management may improve these outcomes. The RI and MEOWS tool has been designed to predict morbidity and decrease delay of transfer.