Learning to detect chest radiographs containing lung nodules using visual attention networks

Machine learning approaches hold great potential for the automated detection of lung nodules in chest radiographs, but training the algorithms requires vary large amounts of manually annotated images, which are difficult to obtain. Weak labels indicating whether a radiograph is likely to contain pulmonary nodules are typically easier to obtain at scale by parsing historical free-text radiological reports associated to the radiographs. Using a repositotory of over 700,000 chest radiographs, in this study we demonstrate that promising nodule detection performance can be achieved using weak labels through convolutional neural networks for radiograph classification. We propose two network architectures for the classification of images likely to contain pulmonary nodules using both weak labels and manually-delineated bounding boxes, when these are available. Annotated nodules are used at training time to deliver a visual attention mechanism informing the model about its localisation performance. The first architecture extracts saliency maps from high-level convolutional layers and compares the estimated position of a nodule against the ground truth, when this is available. A corresponding localisation error is then back-propagated along with the softmax classification error. The second approach consists of a recurrent attention model that learns to observe a short sequence of smaller image portions through reinforcement learning. When a nodule annotation is available at training time, the reward function is modified accordingly so that exploring portions of the radiographs away from a nodule incurs a larger penalty. Our empirical results demonstrate the potential advantages of these architectures in comparison to competing methodologies

Comparing life histories across taxonomic groups in multiple dimensions: how mammal-like are insects?

Explaining variation in life histories remains a major challenge because they are multi-dimensional and there are many competing explanatory theories and paradigms. An influential concept in life history theory is the ’fast-slow continuum’, exemplified by mammals. Determining the utility of such concepts across taxonomic groups requires comparison of the groups’ life histories in multidimensional space. Insects display enormous species richness and phenotypic diversity, but testing hypotheses like the ’fast-slow continuum’ has been inhibited by incomplete trait data. We use phylogenetic imputation to generate complete datasets of seven life history traits in orthopterans (grasshoppers and crickets) and examine the robustness of these imputations for our findings. Three phylogenetic principal components explain 83-96% of variation in these data. We find consistent evidence of an axis mostly following expectations of a ’fast-slow continuum’, except that ’slow’ species produce larger, not smaller, clutches of eggs. We show that the principal axes of variation in orthopterans and reptiles are mutually explanatory, as are those of mammals and birds. Essentially, trait covariation in Orthoptera, with ’slow’ species producing larger clutches, is more reptile-like than mammal-or-bird-like. We conclude that the ’fast-slow continuum’ is less pronounced in Orthoptera than in birds and mammals, reducing the universal relevance of this pattern, and the theories that predict it

The joint influence of marital status, interpregnancy interval, and neighborhood on small for gestational age birth: a retrospective cohort study

<p>Abstract</p> <p>Background</p> <p>Interpregnancy interval (IPI), marital status, and neighborhood are independently associated with birth outcomes. The joint contribution of these exposures has not been evaluated. We tested for effect modification between IPI and marriage, controlling for neighborhood.</p> <p>Methods</p> <p>We analyzed a cohort of 98,330 live births in Montréal, Canada from 1997–2001 to assess IPI and marital status in relation to small for gestational age (SGA) birth. Births were categorized as subsequent-born with <it>short </it>(<12 months), <it>intermediate </it>(12–35 months), or <it>long </it>(36+ months) IPI, or as firstborn. The data had a 2-level hierarchical structure, with births nested in 49 neighborhoods. We used multilevel logistic regression to obtain adjusted effect estimates.</p> <p>Results</p> <p>Marital status modified the association between IPI and SGA birth. Being unmarried relative to married was associated with SGA birth for all IPI categories, particularly for subsequent births with <it>short </it>(odds ratio [OR] 1.60, 95% confidence interval [CI] 1.31–1.95) and <it>intermediate </it>(OR 1.48, 95% CI 1.26–1.74) IPIs. Subsequent births had a lower likelihood of SGA birth than firstborns. <it>Intermediate </it>IPIs were more protective for married (OR 0.50, 95% CI 0.47–0.54) than unmarried mothers (OR 0.65, 95% CI 0.56–0.76).</p> <p>Conclusion</p> <p>Being unmarried increases the likelihood of SGA birth as the IPI shortens, and the protective effect of <it>intermediate </it>IPIs is reduced in unmarried mothers. Marital status should be considered in recommending particular IPIs as an intervention to improve birth outcomes.</p

VII. Observations on the study of mineralogy

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Endovascular Abdominal Aortic Aneurysm Repair: Overview of Current Guidance, Strategies, and New Technologies, Perspectives from the United Kingdom

Endovascular aortic aneurysm repair has changed the management of patients affected by this condition, offering a minimally invasive solution with satisfactory outcomes. Constant evolution of this technology has expanded the use of endovascular devices to more complex cases. The purpose of this review article is to describe the current strategies, guidance, and technologies in this field, with a particular focus on practices in the United Kingdom

Modelling Radiological Language with Bidirectional Long Short-Term Memory Networks

Motivated by the need to automate medical information extraction from free-text radiological reports, we present a bi-directional long short-term memory (BiLSTM) neural network architecture for modelling radiological language. The model has been used to address two NLP tasks: medical named-entity recognition (NER) and negation detection. We investigate whether learning several types of word embeddings improves BiLSTM's performance on those tasks. Using a large dataset of chest x-ray reports, we compare the proposed model to a baseline dictionary-based NER system and a negation detection system that leverages the hand-crafted rules of the NegEx algorithm and the grammatical relations obtained from the Stanford Dependency Parser. Compared to these more traditional rule-based systems, we argue that BiLSTM offers a strong alternative for both our tasks.Comment: LOUHI 2016 conference proceeding

A real‐world experience with the bioactive human split thickness skin allograft for venous leg ulcers

Data collected from standardized clinical practices can be valuable in evaluating the real‐world therapeutic benefit of skin substitutes in the treatment of venous leg ulcers (VLU). Utilizing such a dataset, this study aimed to validate the effectiveness of a bioactive human split‐thickness skin allograft for the treatment of VLU in the real‐world setting and to understand how certain variables impacted healing rates. From a pool of 1474 VLU treated with allograft, 862 ulcers in 742 patients were selected from a large wound EMR database and analyzed. All patients received standard wound care prior to allograft application. Impact of ulcer duration, number of applications, ulcer size, and time to application were analyzed. The VLU, on average, were of 189 days duration with a mean ulcer size of 19.3 cm2. During treatment, 70.7% of wounds healed, with an average time to closure of 15 weeks (SD = 14.1 weeks). The percentage of VLU less than one‐year duration that healed was significantly higher (72.3%) than the percentage of VLU with duration of greater than 1 years (51.5%) ( χ2 = 18.17; P < .001). Ulcers less than 10 cm2 in size were more likely to heal (73.9%) than those larger than 10 cm2 (67.9%) ( χ2 = 8.65, P = .03). VLU receiving allograft within 90 days of initial presentation are 1.4 times more likely to heal vs those receiving their first BSA application after 90 days of standard of care (95% CI: [1.05, 1.86], P = .02). Allograft used in wound clinics healed a majority of refractory VLU, even in large ulcers of long duration, which are more difficult to heal. Smaller wound, size, and shorter wound duration were associated with greater likelihood of healing. VLUs treated earlier with allograft had better healing outcomes. Clinicians may consider more aggressive and timely treatment with allograft for refractory VLU