Modelling Segmented Cardiotocography Time-Series Signals Using One-Dimensional Convolutional Neural Networks for the Early Detection of Abnormal Birth Outcomes

Gynaecologists and obstetricians visually interpret cardiotocography (CTG) traces using the International Federation of Gynaecology and Obstetrics (FIGO) guidelines to assess the wellbeing of the foetus during antenatal care. This approach has raised concerns among professionals with regards to inter- and intra-variability where clinical diagnosis only has a 30\% positive predictive value when classifying pathological outcomes. Machine learning models, trained with FIGO and other user derived features extracted from CTG traces, have been shown to increase positive predictive capacity and minimise variability. This is only possible however when class distributions are equal which is rarely the case in clinical trials where case-control observations are heavily skewed in favour of normal outcomes. Classes can be balanced using either synthetic data derived from resampled case training data or by decreasing the number of control instances. However, this either introduces bias or removes valuable information. Concerns have also been raised regarding machine learning studies and their reliance on manually handcrafted features. While this has led to some interesting results, deriving an optimal set of features is considered to be an art as well as a science and is often an empirical and time consuming process. In this paper, we address both of these issues and propose a novel CTG analysis methodology that a) splits CTG time-series signals into n-size windows with equal class distributions, and b) automatically extracts features from time-series windows using a one dimensional convolutional neural network (1DCNN) and multilayer perceptron (MLP) ensemble. Collectively, the proposed approach normally distributes classes and removes the need to handcrafted features from CTG traces

FRAGMATIC: A randomised phase III clinical trial investigating the effect of fragmin® added to standard therapy in patients with lung cancer

Background Venous thromboembolism (VTE) occurs when blood clots in the leg, pelvic or other deep vein (deep vein thrombosis) with or without transport of the thrombus into the pulmonary arterial circulation (pulmonary embolus). VTE is common in patients with cancer and is increased by surgery, chemotherapy, radiotherapy and disease progression. Low molecular weight heparin (LMWH) is routinely used to treat VTE and some evidence suggests that LMWH may also have an anticancer effect, by reduction in the incidence of metastases. The FRAGMATIC trial will assess the effect of adding dalteparin (FRAGMIN), a type of LMWH, to standard treatment for patients with lung cancer. Methods/Design The study design is a randomised multicentre phase III trial comparing standard treatment and standard treatment plus daily LMWH for 24 weeks in patients with lung cancer. Patients eligible for this study must have histopathological or cytological diagnosis of primary bronchial carcinoma (small cell or non-small cell) within 6 weeks of randomisation, be 18 or older, and must be willing and able to self-administer 5000 IU dalteparin by daily subcutaneous injection or have it administered to themselves or by a carer for 24 weeks. A total of 2200 patients will be recruited from all over the UK over a 3 year period and followed up for a minimum of 1 year after randomisation. Patients will be randomised to one of the two treatment groups in a 1:1 ratio, standard treatment or standard treatment plus dalteparin. The primary outcome measure of the trial is overall survival. The secondary outcome measures include venous thrombotic event (VTE) free survival, serious adverse events (SAEs), metastasis-free survival, toxicity, quality of life (QoL), levels of breathlessness, anxiety and depression, cost effectiveness and cost utility. Trial registration Current Controlled Trials ISRCTN8081276

Examining the Correspondence Between Relationship Identity and Actual Sexual Risk Behavior Among HIV-Positive Men Who Have Sex with Men

Sexual behavior of men who have sex with men (MSM), within and outside of one’s primary relationship, may contribute to increased risk of HIV transmission among those living with HIV. The current study sought to understand how HIV-infected MSM report their relationship status and the degree to which this corresponds with their sexual behavior. Further, we examined rates and psychosocial associations with sexual HIV transmission risk behavior (TRB) across relationship categories. In a sample of 503 HIV-infected MSM in HIV care, 200 (39.8%) reported having a primary partner. Of these, 115 reported that their relationship was open and 85 reported that it was monogamous. Of the 85 who reported a monogamous relationship, 23 (27%) reported more than one sexual partner in the prior three months, 53 (62%) reported only one partner, and nine did not report on the number of partners in the past 3 months. Hence, there were three categories of relationships: (1) “monogamous with one sexual partner,” (2) “monogamous with more than one sexual partner,” and (3) “open relationship.” The “monogamous with more than one sexual partner” group reported higher TRB and crystal methamphetamine use compared to the “monogamous with one sexual partner” group and different patterns of relationships with TRB emerged across the three groups. Couples-based HIV prevention interventions for MSM may be enhanced by considering that there may be different definitions of monogamy among MSM, and that the context of relationship status may require tailoring interventions to meet the needs of specific subgroups of MSM couples

Text Mining in Multimedia

C. Aggarwal and C. Zha