MTS2Graph: Interpretable Multivariate Time Series Classification with Temporal Evolving Graphs

Conventional time series classification approaches based on bags of patterns or shapelets face significant challenges in dealing with a vast amount of feature candidates from high-dimensional multivariate data. In contrast, deep neural networks can learn low-dimensional features efficiently, and in particular, Convolutional Neural Networks (CNN) have shown promising results in classifying Multivariate Time Series (MTS) data. A key factor in the success of deep neural networks is this astonishing expressive power. However, this power comes at the cost of complex, black-boxed models, conflicting with the goals of building reliable and human-understandable models. An essential criterion in understanding such predictive deep models involves quantifying the contribution of time-varying input variables to the classification. Hence, in this work, we introduce a new framework for interpreting multivariate time series data by extracting and clustering the input representative patterns that highly activate CNN neurons. This way, we identify each signal's role and dependencies, considering all possible combinations of signals in the MTS input. Then, we construct a graph that captures the temporal relationship between the extracted patterns for each layer. An effective graph merging strategy finds the connection of each node to the previous layer's nodes. Finally, a graph embedding algorithm generates new representations of the created interpretable time-series features. To evaluate the performance of our proposed framework, we run extensive experiments on eight datasets of the UCR/UEA archive, along with HAR and PAM datasets. The experiments indicate the benefit of our time-aware graph-based representation in MTS classification while enriching them with more interpretability

Awareness of colorectal cancer signs and symptoms: a national cross-sectional study from Palestine

Abstract Background In low-resource settings, the awareness level of colorectal cancer (CRC) signs and symptoms plays a crucial role in early detection and treatment. This study examined the public awareness level of CRC signs and symptoms in Palestine and investigated the factors associated with good awareness. Methods This was a national cross-sectional study conducted at hospitals, primary healthcare centers, and public spaces in 11 governorates across Palestine between July 2019 and March 2020. A translated-into-Arabic version of the validated bowel cancer awareness measure (BoCAM) was utilized to assess the awareness level of CRC signs and symptoms. For each correctly identified CRC sign/symptom, one point was given. The total score (ranging from 0 to 12) was calculated and categorized into three categories based on the number of symptoms recognized: poor (0 to 4), fair (5 to 8), and good awareness (9 to 12). Results Of 5254 approached, 4877 participants completed the questionnaire (response rate = 92.3%). A total of 4623 questionnaires were included in the analysis; 1923 were from the Gaza Strip and 2700 from the West Bank and Jerusalem (WBJ). Participants from the Gaza Strip were younger, gained lower monthly income, and had less chronic diseases than participants in the WBJ. The most frequently identified CRC sign/symptom was ‘lump in the abdomen’ while the least was ‘pain in the back passage’. Only 1849 participants (40.0%, 95% CI: 39.0%-41.0%) had a good awareness level of CRC signs/symptoms. Participants living in the WBJ were more likely to have good awareness than participants living in the Gaza Strip (42.2% vs. 37.0%; p = 0.002). Knowing someone with cancer (OR = 1.37, 95% CI: 1.21–1.55; p < 0.001) and visiting hospitals (OR = 1.46, 95% CI: 1.25–1.70; p < 0.001) were both associated with higher likelihood of having good awareness. However, male gender (OR = 0.80, 95% CI: 0.68–0.94; p = 0.006) and following a vegetarian diet (OR = 0.59, 95% CI: 0.48–0.73; p < 0.001) were both associated with lower likelihood of having good awareness. Conclusion Less than half of the study participants had a good awareness level of CRC signs and symptoms. Future education interventions are needed to improve public awareness of CRC in Palestine