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Acceleration of the SPADE Method Using a Custom-Tailored FP-Growth Implementation.

ABSTRACT: The SPADE (spatio-temporal Spike PAttern Detection and Evaluation) method was developed to find reoccurring spatio-temporal patterns in neuronal spike activity (parallel spike trains). However, depending on the number of spike trains and the length of recording, this method can exhibit long runtimes. Based on a realistic benchmark data set, we identified that the combination of pattern mining (using the FP-Growth algorithm) and the result filtering account for 85-90% of the method's total runtime. Therefore, in this paper, we propose a customized FP-Growth implementation tailored to the requirements of SPADE, which significantly accelerates pattern mining and result filtering. Our version allows for parallel and distributed execution, and due to the improvements made, an execution on heterogeneous and low-power embedded devices is now also possible. The implementation has been evaluated using a traditional workstation based on an Intel Broadwell Xeon E5-1650 v4 as a baseline. Furthermore, the heterogeneous microserver platform RECS|Box has been used for evaluating the implementation on two HiSilicon Hi1616 (Kunpeng 916), an Intel Coffee Lake-ER Xeon E-2276ME, an Intel Broadwell Xeon D-D1577, and three NVIDIA Tegra devices (Jetson AGX Xavier, Jetson Xavier NX, and Jetson TX2). Depending on the platform, our implementation is between 27 and 200 times faster than the original implementation. At the same time, the energy consumption was reduced by up to two orders of magnitude.

SUBMITTER: Porrmann F

PROVIDER: S-EPMC8483730 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundThe aim was to identify the most important determinants of practice for the implementation of person-centered tools which enhance work participation for patients with chronic health conditions.MethodsA mixed-method study was conducted consisting of semi-structured interviews, a focus group and a survey. Various stakeholders were involved including (representatives of) workers with chronic health conditions, insurance physicians, occupational physicians, other healthcare professionals, researchers, employers, and policymakers. The semi-structured interviews were performed to identify implementation determinants, followed by a focus group to validate resulting determinants. To conclude, a survey was conducted to select the most important implementation determinants through prioritization by ranking the order of importance. The Tailored Implementation of Chronic Diseases checklist (TICD) was used as concept-driven coding frame for the qualitative analysis of the interviews and focus group. The self-developed survey was based on the domains of the TICD. The survey was analyzed by frequency count of first ranking of determinants per and between domains of the TICD.ResultsVarious stakeholders participated (N = 27) in the interviews and focus group. The qualitative data retrieved yielded a list of determinants with additional in-depth themes according to the TICD. For the selection of the most important determinants, a survey with 101 respondents was conducted, consisting of occupational physicians, insurance physicians and workers with a chronic health condition. From the seven domains of the TICD, respondents emphasized the importance of taking into account the needs and factors associated with workers with a chronic health condition as this determinant ranked highest. Taking into account the individual needs and wishes of workers was mentioned to enable successful implementation, whereas stress of the workers was indicated to impede implementation. Other important determinants included 'being able to work with the tools' in terms of time and usability or 'cognitions, beliefs and attitudes of occupational and insurance physicians' to be able to use the tools.ConclusionThis study identified the most important determinants from the perspective of various stakeholders involved in the implementation of client-centered tools in occupational health for workers with chronic health conditions. Furthermore, by prioritizing the most important determinants, targeted implementation strategies can be developed.

Project description:PurposeMany patients living with bladder cancer do not undergo surveillance that is aligned with their risk for recurrence or progression, which exposes them to unnecessary risk and burden of procedures. To implement risk-aligned surveillance as recommended by multiple guidelines, we need to understand patient-, provider-, and system-level factors contributing to the delivery of risk-aligned surveillance. In this study, we sought to systematically assess patient-level factors.Participants and methodsGuided by the Tailored Implementation for Chronic Diseases framework, we conducted semistructured interviews with 22 patients with bladder cancer undergoing surveillance cystoscopy procedures at three facilities within the Department of Veterans Affairs. Patients were sampled using quantitative data on bladder cancer risk category (low v high) and on surveillance category (aligned v not aligned with cancer risk). Interview transcripts were analyzed using a priori codes from the Tailored Implementation for Chronic Diseases framework. Quantitative and qualitative data were integrated by cross-tabulating determinants across risk and surveillance categories.ResultsParticipants included seven low-risk and 15 high-risk patients; 10 underwent risk-aligned surveillance and 12 did not. In mixed-methods analyses, perception of risk appropriately differed by risk but not by surveillance category. Participants understood the recommended surveillance schedule according to their risk category. Participants emphatically expressed that adhering to providers' recommendations is prudent; intentions to adhere did not vary across risk and surveillance categories.ConclusionParticipants intended to adhere to providers' recommendations and strongly endorsed the importance of adherence. These findings suggest implementation strategies to improve risk-aligned surveillance may be most effective when targeting provider- and system-level factors rather than patient-level factors.

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Acceleration of the SPADE Method Using a Custom-Tailored FP-Growth Implementation.

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