Visual Analytics in Explaining Neural Networks with Neuron Clustering

Deep learning (DL) models have achieved state-of-the-art performance in many domains. The interpretation of their working mechanisms and decision-making process is essential because of their complex structure and black-box nature, especially for sensitive domains such as healthcare. Visual analytics (VA) combined with DL methods have been widely used to discover data insights, but they often encounter visual clutter (VC) issues. This study presents a compact neural network (NN) view design to reduce the visual clutter in explaining the DL model components for domain experts and end users. We utilized clustering algorithms to group hidden neurons based on their activation similarities. This design supports the overall and detailed view of the neuron clusters. We used a tabular healthcare dataset as a case study. The design for clustered results reduced visual clutter among neuron representations by 54% and connections by 88.7% and helped to observe similar neuron activations learned during the training process

An approach to operational modal analysis using the expectation maximization algorithm

This paper presents the Expectation Maximization algorithm (EM) applied to operational modal analysis of structures. The EM algorithm is a general-purpose method for maximum likelihood estimation (MLE) that in this work is used to estimate state space models. As it is well known, the MLE enjoys some optimal properties from a statistical point of view, which make it very attractive in practice. However, the EM algorithm has two main drawbacks: its slow convergence and the dependence of the solution on the initial values used. This paper proposes two different strategies to choose initial values for the EM algorithm when used for operational modal analysis: to begin with the parameters estimated by Stochastic Subspace Identification method (SSI) and to start using random points. The effectiveness of the proposed identification method has been evaluated through numerical simulation and measured vibration data in the context of a benchmark problem. Modal parameters (natural frequencies, damping ratios and mode shapes) of the benchmark structure have been estimated using SSI and the EM algorithm. On the whole, the results show that the application of the EM algorithm starting from the solution given by SSI is very useful to identify the vibration modes of a structure, discarding the spurious modes that appear in high order models and discovering other hidden modes. Similar results are obtained using random starting values, although this strategy allows us to analyze the solution of several starting points what overcome the dependence on the initial values used

An Injury Severity Prediction-Driven Accident Prevention System

Traffic accidents are inevitable events that occur unexpectedly and unintentionally. Therefore, analyzing traffic data is essential to prevent fatal accidents. Traffic data analysis provided insights into significant factors and driver behavioral patterns causing accidents. Combining these patterns and the prediction model into an accident prevention system can assist in reducing and preventing traffic accidents. This study applied various machine learning models, including neural network, ordinal regression, decision tree, support vector machines, and logistic regression to have a robust prediction model in injury severity. The trained model provides timely and accurate predictions on accident occurrence and injury severity using real-world traffic accident datasets. We proposed an informative negative data generator using feature weights derived from multinomial logit regression to balance the non-fatal accident data. Our aim is to resolve the bias that happens in the favor of the majority class as well as performance improvement. We evaluated the overall and class-level performance of the machine learning models based on accuracy and mean squared error scores. Three hidden layered neural networks outperformed the other models with 0.254 ± 0.038 and 0.173 ± 0.016 MSE scores for two different datasets. A neural network, which provides more accurate and reliable results, should be integrated into the accident prevention system

Post EVAR endovascular revision of late onset stent graft collapse due to Type 1 endoleak in a complicated case with left limb occlusion and solitary kidney

Type 1 endoleak is one of the most frequent complication usually seen at the initial phase of EVAR procedure. B alloon dilatation is mostly used to oversize the proximal or the distal part of the orifice to stabilize the attachment of the graft stent to the aortic wall. Late onset of type 1 endoleak with graft stents may cause severe lumen compression of the stent and aneurysm enlargement which might cause a serious problem especially in a patient whose graft stents left iliac branch is thrombosed and the left leg is supplied by the bypass graft from right CFA. Although operation was advised by the endovascular specialists the procedure was done in our hospital as the patient preferred the endovascular method instead of open surgery

Discrepancy between radiological and pathological size of renal masses

<p>Abstract</p> <p>Background</p> <p>Tumor size is a critical variable in staging for renal cell carcinoma. Clinicians rely on radiological estimates of pathological tumor size to guide patient counseling regarding prognosis, choice of treatment strategy and entry into clinical trials. If there is a discrepancy between radiological and pathological measurements of renal tumor size, this could have implications for clinical practice. Our study aimed to compare the radiological size of solid renal tumors on computed tomography (CT) to the pathological size in an Australian population.</p> <p>Methods</p> <p>We identified 157 patients in the Westmead Renal Tumor Database, for whom data was available for both radiological tumor size on CT and pathological tumor size. The paired Student's <it>t</it>-test was used to compare the mean radiological tumor size and the mean pathological tumor size. Statistical significance was defined as <it>P </it>< 0.05. We also identified all cases in which post-operative down-staging or up-staging occurred due to discrepancy between radiological and pathological tumor sizes. Additionally, we examined the relationship between Fuhrman grade and radiological tumor size and pathological T stage.</p> <p>Results</p> <p>Overall, the mean radiological tumor size on CT was 58.3 mm and the mean pathological size was 55.2 mm. On average, CT overestimated pathological size by 3.1 mm (<it>P </it>= 0.012). CT overestimated pathological tumor size in 92 (58.6%) patients, underestimated in 44 (28.0%) patients and equaled pathological size in 21 (31.4%) patients. Among the 122 patients with pT1 or pT2 tumors, there was a discrepancy between clinical and pathological staging in 35 (29%) patients. Of these, 21 (17%) patients were down-staged post-operatively and 14 (11.5%) were up-staged. Fuhrman grade correlated positively with radiological tumor size (<it>P </it>= 0.039) and pathological tumor stage (<it>P </it>= 0.003).</p> <p>Conclusions</p> <p>There was a statistically significant but small difference (3.1 mm) between mean radiological and mean pathological tumor size, but this is of uncertain clinical significance. For some patients, the difference leads to a discrepancy between clinical and pathological staging, which may have implications for pre-operative patient counseling regarding prognosis and management.</p

Right liver lobe hypoplasia and related abnormalities

BACKGROUND: Hypoplasia and agenesis of the liver lobe is a rare abnormality. It is associated with biliary system abnormalities, high location of the right kidney, and right colon interposition. These patients are prone to gallstones, portal hypertension and possible surgical complications because of anatomical disturbance. CASE REPORT: Magnetic resonance imaging features of a rare case of hypoplasia of the right lobe of the liver in a sigmoid cancer patient are presented. CONCLUSIONS: Hypoplasia of the right liver should not be confused with liver atrophy; indeed, associations with other coexistent abnormalities are also possible. Awareness and familiarity with these anomalies are necessary to avoid fatal surgical and interventional complications

On Miniaturization and Performance Improvement of Planar Wideband Bandpass Filters Without Coupled Lines

Two classical approaches are compared in various respects for the design of wideband planar BPF's without parallel coupled lines, namely, BPF's designed by pole placement with contributing Unit Elements (UE) and inverter coupled resonator filters designed from LP prototypes. It is shown that the circuit obtained by direct BP synthesis is a special case of inverter coupled filter with inverters converted into single Unit Elements. It is also shown that if the inverters are converted into odd number of UE's then they become contributing UE's which can be used to improve skirt slopes considerably. For transversal size reduction and reshaping the stopband response, equivalent circuits of all-stub resonators are derived by starting from distributed element resonator models. The techniques are applied on a Unit Element coupled all-stub resonator BP filters resulting in wide spurious free stopbands with reduced size

Metástases nas leptomeninges da espinal medula num doente com carcinoma de céculas escamosas do pulmão Spinal leptomeningeal metastasis in a patient with squamous cell lung cancer

As metástases nas leptomeninges da espinal medula ocorrem raramente nos tumores sólidos e o prognóstico é bastante reservado. Os adenocarcinomas e os carcinomas de pequenas células são os grupos histológicos mais envolvidos no que se refere aos tumores pulmonares. Um homem de 58 anos com história de carcinoma de células escamosas do pulmão com inversão mediastínica e metástases cerebrais apresenta lombalgias e fraqueza em ambos os membros inferiores. A RMN da coluna vertebral revelou espessamento na espinal medula e múltiplos nódulos do grupo das fibras da cauda equina. Tanto quanto sabemos, trata-se do segundo caso relatado de carcinoma pulmonar de células escamosas que apresenta metástases nas leptomeninges da espinal medula.Spinal leptomeningeal metastasis occurs rarely in solid tumors, and the prognosis is extremely poor. Adenocarcinomas and small-cell carcinomas are the most common histological type detected among lung tumors. A 58-year-old man with a history of squamous-cell lung carcinoma with mediastinal invasion and brain metastasis was examined because of his low back pain and weakness in both lower limbs. Spinal MRI revealed subpial enhancement in the spinal cord; and innumerable nodules with thickening of the cauda equina fibres. To our knowledge, this is the second reported case of squamous cell lung cancer with spinal leptomeningeal metastasis

Unilateral cervical and petrosal segment agenesis of the internal carotid artery with rete mirabile

The carotid rete mirabile (RM) is a physiological network between the internal and external carotid arterial systems. In this paper, an extremely rare case is presented, in which internal–external carotid artery anastomoses and a dilated ascending pharyngeal artery, due to unilateral agenesis of the cervical and petrous segments of the internal carotid artery (ICA), is presented. © 2019 Elsevier Inc