Unsupervised Feature Learning through Divergent Discriminative Feature Accumulation

Unlike unsupervised approaches such as autoencoders that learn to reconstruct their inputs, this paper introduces an alternative approach to unsupervised feature learning called divergent discriminative feature accumulation (DDFA) that instead continually accumulates features that make novel discriminations among the training set. Thus DDFA features are inherently discriminative from the start even though they are trained without knowledge of the ultimate classification problem. Interestingly, DDFA also continues to add new features indefinitely (so it does not depend on a hidden layer size), is not based on minimizing error, and is inherently divergent instead of convergent, thereby providing a unique direction of research for unsupervised feature learning. In this paper the quality of its learned features is demonstrated on the MNIST dataset, where its performance confirms that indeed DDFA is a viable technique for learning useful features.Comment: Corrected citation formattin

Learning Behavior Characterizations for Novelty Search

Novelty search and related diversity-driven algorithms provide a promising approach to overcoming deception in complex domains. The behavior characterization (BC) is a critical choice in the application of such algorithms. The BC maps each evaluated individual to a behavior, i.e., some vector representation of what the individual is or does during evaluation. Search is then driven towards diversity in a metric space of these behaviors. BCs are built from hand-designed features that are limited by human expertise, or upon generic descriptors that cannot exploit domain nuance. The main contribution of this paper is an approach that addresses these shortcomings. Generic behaviors are recorded from evolution on several training tasks, and a new BC is learned from them that funnels evolution towards successful behaviors on any further tasks drawn from the domain. This approach is tested in increasingly complex simulated maze-solving domains, where it outperforms both hand-coded and generic BCs, in addition to outperforming objective-based search. The conclusion is that adaptive BCs can improve search in many-task domains with little human expertise

Comparison of Baseline Characteristics and Outcomes in Men Versus Women With Aortic Stenosis Undergoing Transcatheter Aortic Valve Implantation

Female gender has been linked to increased risk of adverse events after surgical aortic valve replacement; however, the evidence regarding the role of gender differences on clinical outcomes in patients who underwent transcatheter aortic valve implantation (TAVI) is still debated. This retrospective study included 910 consecutive patients with severe, symptomatic aortic stenosis who underwent TAVI in 2 institutions from January 2012 to July 2016. The primary end point was all-cause mortality at 1 year after TAVI in women versus men. Women had a higher incidence of in-hospital vascular complications (7.8% vs 4.1%) and major or life-threatening bleeding (4.0% vs 1.6%) than men. At 1 year, women showed a lower mortality rate than men (7.0% vs 12.7%, adjusted hazard ratio [HR] 0.42, 95% confidence interval [CI] [0.23 to 0.76], p = 0.004). When stratifying by specific subgroups of interest, the survival benefit in women persisted in (1) patients with a Society of Thoracic Surgery risk score ≤ 8 (adjusted HR 0.35, 95% CI [0.14 to 0.88], p = 0.026); (2) patients treated with first-generation devices (adjusted HR 0.46, 95% CI [0.24 to 0.86], p = 0.016); and (3) patients treated with balloon-expandable valves (adjusted HR 0.40, 95% CI [0.19 to 0.86], p = 0.019). In conclusion, in this large patient cohort, women had lower 1-year mortality after TAVI than men, particularly with an STS score ≤ 8, or treated with first-generation and balloon-expandable devices

Comparison of Efficacy and Safety of Transcatheter Aortic Valve Implantation in Patients With Bicuspid Versus Tricuspid Aortic Valves

Bicuspid aortic valve (BAV) stenosis has been considered a contraindication to transcatheter aortic valve implantation (TAVI). The aim of this study is to compare the efficacy and safety of TAVI in patients with BAV with those with tricuspid aortic valve (TAV) using balloon-expandable and self-expanding transcatheter heart valves. This retrospective study included 823 consecutive patients with severe, symptomatic aortic valve stenosis undergoing TAVI in 2 institutions, Baylor Heart and Vascular Hospital (Dallas, TX) and The Heart Hospital Baylor Plano (Plano, TX), from January 2012 to February 2016. Efficacy was evaluated by postprocedural valve function as mean gradient, peak velocity, effective orifice area, and ≥moderate paravalvular leak. Safety end points included all-cause 30-day and 1-year mortality, immediate postprocedural mortality and 30-day cardiovascular mortality, procedural success, pacemaker implantation, and procedural complications. Of the 823 included patients, 735 had TAV and 77 had BAV. Baseline characteristics were similar between the 2 groups. Procedural success was high in both BAV and TAV (98.7% vs 99.1%, p = ns). There were no significant differences between groups in valve hemodynamics after TAVI, pacemaker implantation rate, or procedural complications. There were no differences regarding immediate postprocedural mortality (BAV vs TAV, 1.1% vs 0.8%, p = ns), nor 30-day cardiovascular mortality (3.4% vs 2.3%, p = ns). All-cause mortality at 30 days (3.4% vs 3.1%, p = ns) and 1-year (8.5% vs 10.5%) were similar. Patients with BAV showed similar procedural and clinical outcomes to patients with TAV. Therefore, TAVI appears to be a safe and effective procedure for patients with BAVs as well as those with TAVs

Clinical Relevance of Baseline TCP in Transcatheter Aortic Valve Replacement

AIMS: To investigate the influence of baseline thrombocytopenia (TCP) on short-term and long-term outcomes after transcatheter aortic valve replacement (TAVR). METHODS AND RESULTS: A total of 732 consecutive patients with severe, symptomatic aortic stenosis undergoing TAVR from January 2012 to December 2015 were included. Primary outcomes of interest were the relationship of baseline TCP with 30-day and 1-year all-cause mortality. Secondary outcomes of interest were procedural complications and in-hospital mortality in the same subgroups. The prevalence of TCP (defined as platelet count <150 × 109/L) at baseline was 21.9%, of whom 4.0% had moderate/severe TCP (defined as platelet count <100 × 109/L). Compared to no or mild TCP, moderate/severe TCP at baseline was associated with a significantly higher 30-day mortality (23.3% vs 2.3% and 3.1%, respectively; P<.001) and 1-year mortality (40.0% vs 8.3% and 13.4%, respectively; P<.001). In Cox regression analysis, moderate/severe baseline TCP was an independent predictor of 30-day and 1-year mortality (hazard ratio [HR], 13.18; 95% confidence interval [CI], 4.49-38.64; P<.001 and HR, 5.90; 95% CI, 2.68-13.02; P<.001, respectively). CONCLUSIONS: In conclusion, baseline TCP is a strong predictor of mortality in TAVR patients, possibly identifying a specific subgroup of frail patients; therefore, it should be taken into account when addressing TAVR risk

Worldwide Infrastructure for Neuroevolution: A Modular Library to Turn Any Evolutionary Domain into an Online Interactive Platform

Across many scientific disciplines, there has emerged an open opportunity to utilize the scale and reach of the Internet to collect scientific contributions from scientists and non-scientists alike. This process, called citizen science, has already shown great promise in the fields of biology and astronomy. Within the fields of artificial life (ALife) and evolutionary computation (EC) experiments in collaborative interactive evolution (CIE) have demonstrated the ability to collect thousands of experimental contributions from hundreds of users across the glob. However, such collaborative evolutionary systems can take nearly a year to build with a small team of researchers. This dissertation introduces a new developer framework enabling researchers to easily build fully persistent online collaborative experiments around almost any evolutionary domain, thereby reducing the time to create such systems to weeks for a single researcher. To add collaborative functionality to any potential domain, this framework, called Worldwide Infrastructure for Neuroevolution (WIN), exploits an important unifying principle among all evolutionary algorithms: regardless of the overall methods and parameters of the evolutionary experiment, every individual created has an explicit parent-child relationship, wherein one individual is considered the direct descendant of another. This principle alone is enough to capture and preserve the relationships and results for a wide variety of evolutionary experiments, while allowing multiple human users to meaningfully contribute. The WIN framework is first validated through two experimental domains, image evolution and a new two-dimensional virtual creature domain, Indirectly Encoded SodaRace (IESoR), that is shown to produce a visually diverse variety of ambulatory creatures. Finally, an Android application built with WIN, filters, allows users to interactively evolve custom image effects to apply to personalized photographs, thereby introducing the first CIE application available for any mobile device. Together, these collaborative experiments and new mobile application establish a comprehensive new platform for evolutionary computation that can change how researchers design and conduct citizen science online

Frequency of and Prognostic Significance of Atrial Fibrillation in Patients Undergoing Transcatheter Aortic Valve Implantation

The prognostic implications of preexisting atrial fibrillation (AF) and new-onset AF (NOAF) in transcatheter aortic valve implantation (TAVI) remain uncertain. This study assesses the epidemiology of AF in patients treated with TAVI and evaluates their outcomes according to the presence of preexisting AF or NOAF. A retrospective analysis of 708 patients undergoing TAVI from 2 heart hospitals was performed. Patients were divided into 3 study groups: sinus rhythm (n = 423), preexisting AF (n = 219), and NOAF (n = 66). Primary outcomes of interest were all-cause death and stroke both at 30-day and at 1-year follow-up. Preexisting AF was present in 30.9% of our study population, whereas NOAF was observed in 9.3% of patients after TAVI. AF and NOAF patients showed a higher rate of 1-year all-cause mortality compared with patients in sinus rhythm (14.6% vs 6.5% for preexisting AF and 16.3% vs 6.5% for NOAF, p = 0.007). No differences in 30-day mortality were observed between groups. In patients with AF (either preexisting and new-onset), those discharged with single antiplatelet therapy displayed higher mortality rates at 1 year (42.9% vs 11.7%, p = 0.006). Preexisting AF remained an independent predictor of mortality at 1-year follow-up (hazard ratio [HR] 2.34, 95% CI 1.22 to 4.48, p = 0.010). Independent predictors of NOAF were transapical and transaortic approach as well as balloon postdilatation (HR 3.48, 95% CI 1.66 to 7.29, p = 0.001; HR 5.08, 95% CI 2.08 to 12.39, p <0.001; HR 2.76, 95% CI 1.25 to 6.08, p = 0.012, respectively). In conclusion, preexisting AF is common in patients undergoing TAVI and is associated with a twofold increased risk of 1-year mortality. This negative effect is most pronounced in patients discharged with single antiplatelet therapy compared with other antithrombotic regimens