Assessment of disease activity in patients with rheumatoid arthritis using optical spectral transmission measurements, a non-invasive imaging technique

Objectives: In rheumatoid arthritis (RA), treat-to-target strategies require instruments for valid detection of joint inflammation. Therefore, imaging modalities are increasingly used in clinical practice. Optical spectral transmission (OST) measurements are non-invasive and fast and may therefore have benefits over existing imaging modalities. We tested whether OST could measure disease activity validly in patients with RA. Methods: In 59 patients with RA and 10 patients with arthralgia, OST, joint counts, Disease Activity Score (DAS) 28 and ultrasonography (US) were performed. Additionally, MRI was performed in patients with DAS28<2.6. We developed and validated within the same cohort an algorithm for detection of joint inflammation by OST with US as reference. Results: At the joint level, OST and US performed similarly inproximal interphalangeal-joints (area under the receiver-operating curve (AUC) of 0.79, p<0.0001) andmetacarpophalangeal joints (AUC 0.78, p<0.0001). Performance was less similar in wrists (AUC 0.62, p=0.006). On the patient level, OST correlated moderately with clinical examination (DAS28 r=0.42, p=0.001), and US scores (r=0.64, p<0.0001). Furthermore, in patients with subclinical and low disease activity, there was a correlation between OST and MRI synovitis score (RAMRIS (Rheumatoid Arthritis MRI Scoring) synovitis), r=0.52, p=0.005. Conclusions: In this pilot study, OST performed moderately in the detection of joint inflammation in patients with RA. Further studies are needed to determine the diagnostic performance in a new cohort of patients with RA

Behavioural modelling using the MOESP algorithm, dynamic neural networks and the Bartels-Stewart algorithm

In this paper we discuss the use of the state-space modelling MOESP algorithm to generate precise information about the number of neurons and hidden layers in dynamic neural networks developed for the behavioural modelling of electronic circuits. The Bartels–Stewart algorithm is used to transform the information from the MOESP algorithm to the neural network formalism. The technique is related to the class of model order reduction algorithms that receives much attention in recent years, especially in the electronics industry

Incorporating Perceptual Task Effort into the Recognition of Intention in Information Graphics

The rapidly increasing availability of electronic publications containing information graphics poses some interesting challenges in terms of information access. For example, visually impaired individuals should ideally be provided with access to the knowledge that would be gleaned from viewing the information graphic. Similarly, digital libraries must take into account the content of information graphics when constructing indices. This paper outlines our approach to recognizing the intended message of an information graphic, focusing on the concept of perceptual task effort, its role in the inference process, our rules for estimating effort, and the results of an eye tracking experiment conducted in order to evaluate and modify those rules