A vision for using online portals for surveillance of patient-centered communication in cancer care

The Veterans Health Administration (VHA) is charged with providing high-quality health care, not only in terms of technical competence but also with regard to patient-centered care experiences. Patient-centered coordination of care and communication are especially important in cancer care, as deficiencies in these areas have been implicated in many cases of delayed cancer diagnosis and treatment. Additionally, because cancer care facilities are concentrated within the VHA system, geographical and system-level barriers may present prominent obstacles to quality care. Systematic assessment of patient-centered communication (PCC) may help identify both individual veterans who are at risk of suboptimal care and opportunities for quality improvement initiatives at the service, facility, or system-wide level. In this manuscript, we describe our vision to implement an assessment of PCC through patient self-report to improve the quality of cancer care and other health services in the VHA. We outline a possible strategy to assess PCC that leverages the VHA’s existing initiative to promote use of an online personal health record for veterans (MyHealtheVet). Questionnaires administered periodically or following specific episodes of care can be targeted to assess PCC in cancer care. Assessment of PCC can also be tied to clinical and administrative data for more robust analysis of patient outcomes. Ultimately, the goal of any assessment of PCC is to gather valid, actionable data that can assist VHA clinicians and staff with providing the best possible care for veterans with cancer

Mirror-Descent Methods in Mixed-Integer Convex Optimization

In this paper, we address the problem of minimizing a convex function f over a convex set, with the extra constraint that some variables must be integer. This problem, even when f is a piecewise linear function, is NP-hard. We study an algorithmic approach to this problem, postponing its hardness to the realization of an oracle. If this oracle can be realized in polynomial time, then the problem can be solved in polynomial time as well. For problems with two integer variables, we show that the oracle can be implemented efficiently, that is, in O(ln(B)) approximate minimizations of f over the continuous variables, where B is a known bound on the absolute value of the integer variables.Our algorithm can be adapted to find the second best point of a purely integer convex optimization problem in two dimensions, and more generally its k-th best point. This observation allows us to formulate a finite-time algorithm for mixed-integer convex optimization

Computational Complexity in Electronic Structure

In quantum chemistry, the price paid by all known efficient model chemistries is either the truncation of the Hilbert space or uncontrolled approximations. Theoretical computer science suggests that these restrictions are not mere shortcomings of the algorithm designers and programmers but could stem from the inherent difficulty of simulating quantum systems. Extensions of computer science and information processing exploiting quantum mechanics has led to new ways of understanding the ultimate limitations of computational power. Interestingly, this perspective helps us understand widely used model chemistries in a new light. In this article, the fundamentals of computational complexity will be reviewed and motivated from the vantage point of chemistry. Then recent results from the computational complexity literature regarding common model chemistries including Hartree-Fock and density functional theory are discussed.Comment: 14 pages, 2 figures, 1 table. Comments welcom

Enhanced external counter pulsation in treatment of refractory angina pectoris: two year outcome and baseline factors associated with treatment failure

<p>Abstract</p> <p>Background</p> <p>Enhanced external counter pulsation (EECP) is a non-invasive treatment option for patients with refractory angina pectoris ineligible to further traditional treatment. The aim of this study was to evaluate the effect of EECP on patients at a Scandinavian medical centre and to investigate if outcome can be predicted by analysing baseline factors.</p> <p>Methods</p> <p>86 consecutive patients (70 male, 16 female) were treated with EECP and followed for two years post treatment. Canadian cardiovascular society (CCS) class was analysed, and medication and adverse clinical events were researched prior to EECP, at the end of the treatment, and at six, 12 and 24 months thereafter. Patients responding to therapy by improving at least one CCS class were compared with those who failed to respond. Any differences in background factors were recorded and analysed.</p> <p>Results</p> <p>79% of the patients responded to therapy by improving at least one CCS class. In general, the CCS class improved by one class after EECP treatment (3.05 before versus 2.14 after treatment). A total of 61.5% of the initial responders showed sustained improvement at the 12 month follow-up while 29% presented sustained improvement after 24 months. Treatment was most effective among patients suffering from CCS class III-IV angina pectoris, while patients suffering from CCS class II angina pectoris improved transiently but failed to show sustained improvement after the 12 month follow-up. Diabetes mellitus and calcium channel antagonists were more common among the non-responders (<it>p </it>< 0.05).</p> <p>Conclusion</p> <p>This study confirms the safety and efficiency of EECP as a treatment option for patients suffering from refractory angina pectoris. The therapy is most beneficial in patients suffering from severe angina (CCS III-IV) while sustained response to therapy could not be verified among patients suffering from CCS class II angina pectoris.</p

Hemobilia caused by a ruptured hepatic cyst: a case report

<p>Abstract</p> <p>Introduction</p> <p>Hemobilia is a rare cause of upper gastrointestinal bleeding. More than 50% of hemobilia cases are related to iatrogenic trauma from hepatobiliary procedures, and needle biopsy of the liver represents the most common cause. A minority of hemobilia cases are due to hepatobiliary disorders such as cholangitis, hepatobiliary cancers, choledocholithiasis, and vascular abnormalities in the liver. The classic presentation of hemobilia is the triad of right upper quadrant (biliary) pain, obstructive jaundice, and upper gastrointestinal bleeding. We report a rare case of hemobilia caused by a spontaneous hepatic cyst rupture, where our patient presented without the classical symptoms, in the absence of therapeutic or pathological coagulopathy, and in the absence of spontaneous or iatrogenic trauma.</p> <p>Case presentation</p> <p>A 91-year-old African-American woman was referred to our out-patient gastroenterology clinic for evaluation of mild epigastric pain and intermittent melena. An abdominal computed tomography scan was remarkable for multiple hepatic cysts. Esophagogastroduodenoscopy revealed multiple blood clots at the ampulla of Vater. Endoscopic retrograde cholangiopancreatography showed a single 18 mm-sized filling defect in the common hepatic duct wall at the junction of the right and left hepatic duct, adjacent to one of the hepatic cysts. The ruptured hepatic cyst communicated to the bile ducts and was the cause of hemobilia with an atypical clinical presentation.</p> <p>Conclusion</p> <p>Hemobilia is an infrequent cause of upper gastrointestinal bleeding and rarely occurs due to hepatic cyst rupture. To the best of our knowledge, this is only the second case report in the literature that describes hemobilia due to hepatic cyst rupture. However, it is the first case in the literature of hemobilia due to hepatic cyst rupture in the absence of iatrogenic or spontaneous trauma, and in the absence of a spontaneous or pathological coagulopathy.</p

Transternal repair of a giant Morgagni hernia causing cardiac tamponade in a patient with coexisting severe aortic valve stenosis

<p>Abstract</p> <p>Background</p> <p>Foramen of Morgagni hernias have traditionally been repaired by laparotomy, lapascopy or even thoracoscopy. However, the trans-sternal approach should be used when these rare hernias coexist with other cardiac surgical diseases.</p> <p>Case presentation</p> <p>We present the case of a 74 year-old symptomatic male with severe aortic <b>valve </b>stenosis and global respiratory failure due to a giant Morgagni hernia causing additionally cardiac tamponade. The patient underwent simultaneous repair of the hernia defect and aortic valve replacement under cardiopulmonary bypass. The hernia was repaired through the sternotomy approach, without opening of its content and during cardiopulmonary reperfusion.</p> <p>Conclusions</p> <p>Morgagni hernia can rarely accompany cardiac surgical pathologies. The trans-sternal approach for its management is as effective as other popular reconstructive procedures, <b>unless viscera strangulation and necrosis are suspected</b>. If severe compressive effects to the heart dominate the patient's clinical presentation correction during the cardiopulmonary reperfusion period is mandatory.</p

Complexity of Discrete Energy Minimization Problems

Discrete energy minimization is widely-used in computer vision and machine learning for problems such as MAP inference in graphical models. The problem, in general, is notoriously intractable, and finding the global optimal solution is known to be NP-hard. However, is it possible to approximate this problem with a reasonable ratio bound on the solution quality in polynomial time? We show in this paper that the answer is no. Specifically, we show that general energy minimization, even in the 2-label pairwise case, and planar energy minimization with three or more labels are exp-APX-complete. This finding rules out the existence of any approximation algorithm with a sub-exponential approximation ratio in the input size for these two problems, including constant factor approximations. Moreover, we collect and review the computational complexity of several subclass problems and arrange them on a complexity scale consisting of three major complexity classes -- PO, APX, and exp-APX, corresponding to problems that are solvable, approximable, and inapproximable in polynomial time. Problems in the first two complexity classes can serve as alternative tractable formulations to the inapproximable ones. This paper can help vision researchers to select an appropriate model for an application or guide them in designing new algorithms.Comment: ECCV'16 accepte

LogicWiSARD: Memoryless synthesis of weightless neural networks

Weightless neural networks (WNNs) are an alternative pattern recognition technique where RAM nodes function as neurons. As both training and inference require mostly table lookups, few additions, and no multiplications, WNNs are suitable for high-performance and low-power embedded applications. This work introduces a novel approach to implement WiSARD, the leading WNN state-of-the-art architecture, completely eliminating memories and arithmetic circuits and utilizing only logic functions. The approach creates compressed minimized implementations by converting trained WNN nodes from lookup tables to logic functions. The proposed LogicWiSARD is implemented in FPGA and ASIC technologies to illustrate its suitability for edge inference. Experimental results show more than 80% reduction in energy consumption when the proposed LogicWiSARD model is compared with a multilayer perceptron network (MLP) of equivalent accuracy. Compared to previous work on FPGA implementations for WNNs, convolutional neural networks, and binary neural networks, the energy savings of LogicWiSARD range between 32.2% and 99.6%.info:eu-repo/semantics/acceptedVersio

Pruning weightless neural networks

Weightless neural networks (WNNs) are a type of machine learning model which perform prediction using lookup tables (LUTs) instead of arithmetic operations. Recent advancements in WNNs have reduced model sizes and improved accuracies, reducing the gap in accuracy with deep neural networks (DNNs). Modern DNNs leverage “pruning” techniques to reduce model size, but this has not previously been explored for WNNs. We propose a WNN pruning strategy based on identifying and culling the LUTs which contribute least to overall model accuracy. We demonstrate an average 40% reduction in model size with at most 1% reduction in accuracy.info:eu-repo/semantics/publishedVersio