Decisive Evidence Research Articles

«Проблемные ситуации»: апробация в качестве судебно-психиатрического метода исследования при изменении гражданско-правового статуса

<p style="text-align: justify;">As part of solving the task of developing methods to improve the quality and evidence of forensic psychiatric decisions, in a comparative non-randomized study the “Problem Situations” methodology was tested as a method of forensic psychiatric assessment in civil cases on applications for change civil legal status. The sample consisted of 67 subjects who underwent inpatient forensic psychiatric examination in connection with the decision on the issue of changing their civil status in 2021—2022. A conclusion corresponding to legal capacity was given in relation to 12 people; diminished legal capacity - 24 people; incapacity — 31 people. Pairwise group comparisons using Pearson’s goodness-of-fit test (Chi-square) and biclustering procedures confirmed the predictive validity of the method.</p>

The Use of Real-World Evidence for Regulatory Decisions in China.

There is a growing demand for the use of high-quality real-world evidence (RWE) to support regulatory decision-making worldwide and in China, which highlights the need for conducting literature reviews to evaluate the available data and evidence. This study aims to review the use of RWE in Chinese regulatory decisions and to summarize relevant regulatory and methodological considerations to inform the future use of RWE in China. We identified policy documents, technical guidance documents, and cases on official Chinese government websites and extracted their contents separately. We consulted experts from the National Medical Products Administration (NMPA) and academic institutes and searched case-related articles for enrichment. We also searched and included articles related to the use of RWE/Real-world data in Chinese regulatory decisions. Six trial versions of technical guidance documents, 7 case studies, and 40 articles related to the Chinese regulatory decisions were included in this study. Based on the technical guidance, data quality, and appropriate study design and statistical analysis are the main concerns for RWE generation. The cases and articles related to regulatory decisions revealed 9 main concerns, including data sources and applicability, data quality, strength of existing evidence, appropriate study design and statistical analysis, regulated and transparent process for analysis and evidence generation, product safety and efficacy, product characteristics and clinical needs, ethical considerations and data security, and communicate adequately with regulatory authorities. Among these concerns, data issues are central. Preliminary attempts have been made by the NMPA to promote the use of RWE, but substantial challenges still remain.

Metacognitive evaluation of postdecisional perceptual representations.

Perceptual confidence is thought to arise from metacognitive processes that evaluate the underlying perceptual decision evidence. We investigated whether metacognitive access to perceptual evidence is constrained by the hierarchical organization of visual cortex, where high-level representations tend to be more readily available for explicit scrutiny. We found that the ability of human observers to evaluate their confidence did depend on whether they performed a high-level or low-level task on the same stimuli, but was also affected by manipulations that occurred long after the perceptual decision. Confidence in low-level perceptual decisions degraded with more time between the decision and the response cue, especially when backward masking was present. Confidence in high-level tasks was immune to backward masking and benefitted from additional time. These results can be explained by a model assuming confidence heavily relies on postdecisional internal representations of visual stimuli that degrade over time, where high-level representations are more persistent.

Do not attempt cardiopulmonary resuscitation decision-making process: scoping review

ObjectivesTo conduct a scoping review to explore the evidence of the process of do not attempt cardiopulmonary resuscitation (DNACPR) decision-making.MethodsWe conducted a systematic search and review of articles from 1...

Role of Genetics in Diagnosis and Management of Hypertrophic Cardiomyopathy: A Glimpse into the Future.

Hypertrophic cardiomyopathy (HCM) is the most common inherited cardiomyopathy. It follows an autosomal dominant inheritance pattern in most cases, with incomplete penetrance and heterogeneity. It is familial in 60% of cases and most of these are caused by pathogenic variants in the core sarcomeric genes (MYH7, MYBPC3, TNNT2, TNNI3, MYL2, MYL3, TPM1, ACTC1). Genetic testing using targeted disease-specific panels that utilize next-generation sequencing (NGS) and include sarcomeric genes with the strongest evidence of association and syndrome-associated genes is highly recommended for every HCM patient to confirm the diagnosis, identify the molecular etiology, and guide screening and management. The yield of genetic testing for a disease-causing variant is 30% in sporadic cases and up to 60% in familial cases and in younger patients with typical asymmetrical septal hypertrophy. Genetic testing remains challenging in the interpretation of results and classification of variants. Therefore, in 2015 the American College of Medical Genetics and Genomics (ACMG) established guidelines to classify and interpret the variants with an emphasis on the necessity of periodic reassessment of variant classification as genetic knowledge rapidly expands. The current guidelines recommend focused cascade genetic testing regardless of age in phenotype-negative first-degree relatives if a variant with decisive evidence of pathogenicity has been identified in the proband. Genetic test results in family members guide longitudinal clinical surveillance. At present, there is emerging evidence for genetic test application in risk stratification and management but its implementation into clinical practice needs further study. Promising fields such as gene therapy and implementation of artificial intelligence in the diagnosis of HCM are emerging and paving the way for more effective screening and management, but many challenges and obstacles need to be overcome before establishing the practical implications of these new methods.

Perceptions of Clinical Experience and Scientific Evidence in Medical Decision Making: A Survey of a Stratified Random Sample of Swedish Health Care Professionals.

Evidence-based medicine recognizes that clinical expertise gained through experience is essential to good medical practice. However, it is not known what beliefs clinicians hold about how personal clinical experience and scientific knowledge contribute to their clinical decision making and how those beliefs vary between professions, which themselves vary along relevant characteristics, such as their evidence base. We investigate how years in the profession influence health care professionals' beliefs about science and their clinical experience through surveys administered to random samples of Swedish physicians, nurses, occupational therapists, dentists, and dental hygienists. The sampling frame was each profession's most recent occupational registry. Participants (N = 1,627, 46% response rate) viewed science as more important for decision making, more certain, and more systematic than experience. Differences among the professions were greatest for systematicity, where physicians saw the largest gap between the 2 types of knowledge across all levels of professional experience. The effect of years in the profession varied; it had little effect on assessments of importance across all professions but otherwise tended to decrease the difference between assessments of science and experience. Physicians placed the greatest emphasis on science over clinical experience among the 5 professions surveyed. Health care professions appear to share some attitudes toward professional knowledge, despite the variation in the age of the professions and the scientific knowledge base available to practitioners. Training and policy making about clinical decision making might improve by accounting for the ways in which knowledge is understood across the professions. Study participants, representing 5 health care professions-medicine, nursing, occupational therapy, dentistry, and dental hygiene-viewed science as more important for decision making, more certain, and more systematic than their personal clinical experience.Of all the professions represented in the study, physicians saw the greatest differences between the 2 types of knowledge.The effect of years of professional experience varied but tended to be small, attenuating the differences seen between science and clinical experience.

The value of multimodal treatment in anaplastic thyroid cancer patients with distant metastasis

BackgroundAnaplastic thyroid cancer (ATC) is a rare and aggressive malignancy with a poor prognosis, particularly in patients presenting with distant metastasis (DM). This study aimed to assess the effect of combination treatment strategies on survival in ATC patients with DM.MethodsA retrospective analysis was conducted using data from the Surveillance, Epidemiology, and End Results (SEER) database to identify primary ATC cases with DM at diagnosis. Univariate and multivariate Cox proportional hazards regression analyses were performed to identify independent risk factors for survival.ResultsOf the 315 ATC patients with DM included in the study, surgery to the primary tumor, radiotherapy, chemotherapy, and lung metastasis were identified as independent risk factors for survival. Patients who received primary tumor surgery plus chemotherapy or surgery plus chemoradiation exhibited a superior outcome compared to those who received only one treatment modality.ConclusionOur findings suggest that a combination treatment approach, particularly surgery combined with radiotherapy or surgery combined with chemoradiotherapy, may provide the most optimal treatment option for ATC patients with DM. These results may provide some evidence for clinical decision making, but larger sample cohorts are still needed for validation.

Quantifying Offense and Defense Workloads in Professional Rugby Union.

Rugby union is a contact team sport demanding high levels of physical capacity, and understanding the match workloads can be useful to inform training. In this study, the factors influencing locomotion and contact workloads for offensive and defensive ball-in-play periods are quantified. Locomotion and contact metrics were collected from global positioning system units and videos for 31 professional players of a Super Rugby team across 14 games in the 2021 season. Data were analyzed with a generalized mixed-model procedure that included effects for type of play, playing position, match outcome, and ball-in-play time. Magnitudes were assessed with standardization, and evidence for substantial magnitudes was derived from sampling uncertainty. When offense was compared to defense, most metrics showed decisively substantial increases (smalltomoderate) for forwards and backs. There was decisive evidence that locomotion metrics were substantially lower (large differences) and contact metrics were higher (very large differences) when comparing forwards to backs on offense and defense. When winning was compared to losing, there was good evidence that forwards experienced small increases in overall workload on defense, and backs experienced a small increase in high-speed running and a moderate decrease in contacts on offense. Match-to-match changes associated with ball-in-play time, attributed to fatigue, were decisive (moderatetovery large) across most metrics for forwards and backs in offense and defense. The increased locomotion and contact workloads in offensive periods and the differing physical requirements between positions and match outcomes for both types of play are novel findings that should aid practitioners in designing effective training.

Commentary on Hey, Hunter, Muller et al. A Never-ending Story: Evaluating Evidence in Medicinal Product Decision Making

Decision making in medicinal product development and regulatory approval for marketing authorization are intended to be evidence based. While decision making based on evidence is documented to be a millennial old process, particularly for making legal and economic determinations, the nature and use of evidence continues to evolve, particularly when new technologies need to be factored in. The formal use of evidence for medicinal product evaluation has been in practice for less than 75 years and remains a dynamic process among all stakeholders. The nature of decision making for marketing authorization is particularly complex as it occurs on at least five levels: Causative, Generalizability, Clinical Significance, Risk to Benefit, and Value. Consequently, all stakeholders including product developers and regulatory authorities must communicate and coordinate to ensure functionality, as all are constantly learning to integrate new technologies, ever increasing knowledge of biology and disease, and improved understanding of the decision making process and its consequences. Structured interactions in the form of Scientific Advice with the European regulatory authorities were developed to facilitate knowledge sharing. The Scientific Advice process itself is dynamic and benefits from structured input on how it can better serve the needs and expectations of stakeholders. To that end, Hey, Hunter, Muller, et al provide suggestions in a manuscript following an initial consultative phase and then a peer review phase. The manuscript is an example of the type of engagement and good citizenship that can facilitate the efficient generation and use of evidence to support the complex decision making to which the evidence is applied.

Mild exogenous inflammation blunts neural signatures of bounded evidence accumulation and reward prediction error processing in healthy male participants

BackgroundAltered neural haemodynamic activity during decision making and learning has been linked to the effects of inflammation on mood and motivated behaviours. So far, it has been reported that blunted mesolimbic dopamine reward signals are associated with inflammation-induced anhedonia and apathy. Nonetheless, it is still unclear whether inflammation impacts neural activity underpinning decision dynamics. The process of decision making involves integration of noisy evidence from the environment until a critical threshold of evidence is reached. There is growing empirical evidence that such process, which is usually referred to as bounded accumulation of decision evidence, is affected in the context of mental illness. MethodsIn a randomised, placebo-controlled, crossover study, 19 healthy male participants were allocated to placebo and typhoid vaccination. Three to four hours post-injection, participants performed a probabilistic reversal-learning task during functional magnetic resonance imaging. To capture the hidden neurocognitive operations underpinning decision-making, we devised a hybrid sequential sampling and reinforcement learning computational model. We conducted whole brain analyses informed by the modelling results to investigate the effects of inflammation on the efficiency of decision dynamics and reward learning. ResultsWe found that during the decision phase of the task, typhoid vaccination attenuated neural signatures of bounded evidence accumulation in the dorsomedial prefrontal cortex, only for decisions requiring short integration time. Consistent with prior work, we showed that, in the outcome phase, mild acute inflammation blunted the reward prediction error in the bilateral ventral striatum and amygdala. ConclusionsOur study extends current insights into the effects of inflammation on the neural mechanisms of decision making and shows that exogenous inflammation alters neural activity indexing efficiency of evidence integration, as a function of choice discriminability. Moreover, we replicate previous findings that inflammation blunts striatal reward prediction error signals.

재조합 인플루엔자 백신과 불활성화 인플루엔자 백신의 면역원성 비교

To compare surrogate markers of immunogenicity between recombinant and inactivated influenza vaccines, this study conducted a systematic review and meta-analysis for each strain. Three databases of Medline (Pubmed), Embase and Cochrane Central were searched to identify all published literature up to July 2023. Out of a total of 1,658 initially identified articles, 14 randomized controlled trials were selected based on inclusion and exclusion criteria. The program R version 4.3.1 was used to estimate the mean difference of geometric mean titer (GMT) and the pooled risk ratio (RR) of seroconversion and seroprotection with 95% confidence intervals. The meta-analysis results found higher GMT effect sizes for recombinant influenza vaccines compared to inactivated vaccines for A/H3N2 (MD=124.87, 95% CI 52.63-197.11) and B/Yamagata (MD=19.89, 95% CI 7.61-32.17) strains. In terms of seroconversion rates, recombinant influenza vaccines exhibited higher seroconversion for A/H3N2 (RR=1.33, 95% CI 1.26-1.40) and B/Yamagata (RR=1.75, 95% CI 1.06-2.89) strains. Slightly higher seroprotection rates were observed for A/H3N2 (RR=1.04, 95% CI 1.02-1.07) and B/Yamagata (RR=1.07, 95% CI 1.01-1.13) strains with recombinant vaccines. The findings from this study contribute valuable evidence for regulatory decisions when introducing recombinant vaccines in South Korea.

Audiovestibular adverse events following COVID-19 vaccinations

IntroductionEvidence regarding audiovestibular adverse events post COVID-19 vaccination to date has been inconclusive regarding a potential association. This study aimed to determine if there was an increase in audiovestibular events following COVID-19 vaccination in South-eastern Australia during January 2021–March 2023. MethodsA multi-data source approach was applied. First, a retrospective observational analysis of spontaneous reports of audiovestibular events to a statewide vaccine safety surveillance service, SAEFVIC. Second, a self-controlled case series analysis using general practice data collected via the POpulation Level Analysis and Reporting (POLAR) tool. Results and conclusionsThis study is the first to demonstrate an increase in general practice presentations of vertigo following mRNA vaccines (RI = 1.40, P <.001), and tinnitus following both the Vaxzevria® adenovirus vector and mRNA vaccines (RI = 2.25, P <.001 and 1.53, P <.001 respectively). There was no increase in hearing loss following any COVID-19 vaccinations. Our study, however, was unable to account for the potential of concurrent COVID-19 infections, which literature has indicated to be associated with audiovestibular events.Healthcare providers and vaccinees should be alert to potential audiovestibular complaints after COVID-19 vaccination. Our analysis highlights the importance of using large real-world datasets to gather reliable evidence for public health decision making.

Outpatient hysteroscopy impact on subsequent assisted reproductive technology: a systematic review and meta-analysis in patients with normal transvaginal sonography or hysterosalpingography images

BackgroundStandard management for intrauterine lesions typically involves initial imaging followed by operative hysteroscopy for suspicious findings. However, the efficacy of routine outpatient hysteroscopy in women undergoing assisted reproductive technology (ART) remains uncertain due to a lack of decisive high-quality evidence. This study aimed to determine whether outpatient hysteroscopy is beneficial for infertile women who have unremarkable imaging results prior to undergoing ART.MethodsA systematic review and meta-analysis were conducted following PRISMA guidelines, incorporating data up to May 31, 2023, from databases such as PubMed, Embase, and the Cochrane Library. The primary outcome assessed was the live birth rate, with secondary outcomes including chemical pregnancy, clinical pregnancy rates, and miscarriage rates. Statistical analysis involved calculating risk ratios with 95% confidence intervals and assessing heterogeneity with the I2 statistic.ResultsThe analysis included ten randomized control trials. Receiving outpatient hysteroscopy before undergoing ART was associated with increased live birth (RR 1.22, 95% CI 1.03–1.45, I2 61%) and clinical pregnancy rate (RR 1.27 95% CI 1.10–1.47, I2 53%). Miscarriage rates did not differ significantly (RR 1.25, CI 0.90–1.76, I2 50%). Subgroup analyses did not show a significant difference in clinical pregnancy rates when comparing normal versus abnormal hysteroscopic findings (RR 1.01, CI 0.78–1.32, I2 38%). We analyzed data using both intention-to-treat and per-protocol approaches, and our findings were consistent across both analytical methods.ConclusionsOffice hysteroscopy may enhance live birth and clinical pregnancy rates in infertile women undergoing ART, even when previous imaging studies show no apparent intrauterine lesions. Treating lesions not detected by imaging may improve ART outcomes. The most commonly missed lesions are endometrial polyps, submucosal fibroids and endometritis, which are all known to affect ART success rates. The findings suggested that hysteroscopy, given its diagnostic accuracy and patient tolerability, should be considered in the management of infertility.Database registrationThe study was registered in the International Prospective Register of Systemic Review database (CRD42023476403).

Modeling Magnitude Discrimination: Effects of Internal Precision and Attentional Weighting of Feature Dimensions.

Given a rich environment, how do we decide on what information to use? A view of a single entity (e.g., a group of birds) affords many distinct interpretations, including their number, average size, and spatial extent. An enduring challenge for cognition, therefore, is to focus resources on the most relevant evidence for any particular decision. In the present study, subjects completed three tasks-number discrimination, surface area discrimination, and convex hull discrimination-with the same stimulus set, where these three features were orthogonalized. Therefore, only the relevant feature provided consistent evidence for decisions in each task. This allowed us to determine how well humans discriminate each feature dimension and what evidence they relied on to do so. We introduce a novel computational approach that fits both feature precision and feature use. We found that the most relevant feature for each decision is extracted and relied on, with minor contributions from competing features. These results suggest that multiple feature dimensions are separately represented for each attended ensemble of many items and that cognition is efficient at selecting the appropriate evidence for a decision.

TINJAUAN HUKUM PEMBUKTIAN TERHADAP PENYELESAIAN SENGKETA PERALIHAN STATUS HARTA PUSAKO RENDAH MENJADI HARTA PUSAKO TINGGI DI PENGADILAN

The aim of this research is to test whether the considerations of judges who decide on customary land disputes in Minangkabau are perfect enough in assessing whether a land object is an implant asset, namely a low pusako which is inserted into a high pusako. This research is a case study with a review of the Law of Evidence of the Padang High Court Decision No.121/PDT/2023/PT.PDG in resolving the dispute over the transfer of the status of Pusako Tinggi assets to Pusako Tinggi assets. This research is research using a normative juridical approach, namely legal research that uses secondary data sources obtained from library materials. The research results show that the conditions that must be met so that the status of low pusako assets can be changed to high pusako are 1. There has been inheritance or maintenance from generation to generation for 3 (three) to 4 (four) generations; 2. The origin of ownership of the property is no longer in question or in other words there is no dispute regarding who has the right to the property. Regarding the legal review of evidence regarding the judge's considerations in the Padang High Court Decision No. 121/PDT//2023/PT.PDG is the possibility of negligence or error by the judge in applying imperfect evidence law.

Concurrent predictors of mathematics achievement for 9-year-old children with Williams syndrome

Research on mathematics achievement by children with Williams syndrome (WS) has been very limited. We describe the math achievement of 72 9-year-olds with WS, compare their math and reading achievement, and explore concurrent predictors of math achievement using the Wechsler Individual Achievement Test-III (WIAT-III) to measure achievement and the Differential Ability Scales-II (DAS-II) to measure cognitive abilities. For both Numerical Operations and Math Problem Solving, mean standard scores (SSs) were in the mild disability range with a full range from severe disability to average ability. Bayesian robust estimation indicated decisive evidence that average reading performance was higher than average math performance. Bayesian multiple linear regression models with informative priors accounted for 60% of the variance in Numerical Operations SS with decisive evidence supporting an effect of Working Memory SS and strong evidence for Nonverbal Reasoning SS and Spatial SS and 71% of the variance in Math Problem Solving SS with decisive evidence supporting effects of Working Memory and Nonverbal Reasoning SS, strong evidence for Verbal SS, and substantial evidence for Spatial SS. These predictors are consistent with those for typically developing individuals, supporting consideration of interventions that have been highly effective for children with math difficulties in the general population.

A Pavement Crack Detection and Evaluation Framework for a UAV Inspection System Based on Deep Learning

Existing studies often lack a systematic solution for an Unmanned Aerial Vehicles (UAV) inspection system, which hinders their widespread application in crack detection. To enhance its substantial practicality, this study proposes a formal and systematic framework for UAV inspection systems, specifically designed for automatic crack detection and pavement distress evaluation. The framework integrates UAV data acquisition, deep-learning-based crack identification, and road damage assessment in a comprehensive and orderly manner. Firstly, a flight control strategy is presented, and road crack data are collected using DJI Mini 2 UAV imagery, establishing high-quality UAV crack image datasets with ground truth information. Secondly, a validation and comparison study is conducted to enhance the automatic crack detection capability and provide an appropriate deployment scheme for UAV inspection systems. This study develops automatic crack detection models based on mainstream deep learning algorithms (namely, Faster-RCNN, YOLOv5s, YOLOv7-tiny, and YOLOv8s) in urban road scenarios. The results demonstrate that the Faster-RCNN algorithm achieves the highest accuracy and is suitable for the online data collection of UAV and offline inspection at work stations. Meanwhile, the YOLO models, while slightly lower in accuracy, are the fastest algorithms and are suitable for the lightweight deployment of UAV with online collection and real-time inspection. Quantitative measurement methods for road cracks are presented to assess road damage, which will enhance the application of UAV inspection systems and provide factual evidence for the maintenance decisions made by road authorities.

Validating morphometrics as a nonlethal tool to determine Arctic Grayling sex

AbstractObjectiveSome graylings Thymallus spp. possess an elongated dorsal fin and other morphological traits that can be sexually dimorphic, as demonstrated in the European Grayling T. thymallus. North American Arctic Grayling T. arcticus are assumed to follow these trends, but decisive evidence is lacking. This study aimed to determine whether sexually dimorphic characteristics, including posterior dorsal height, can be used to accurately predict the sex of Arctic Grayling in Interior Alaska.MethodsWe used computer imaging software to measure 22 morphometrics on 97 Arctic Grayling of known sex from streams in Interior Alaska, and we developed a set of binomial models to evaluate the validity of morphometrics as predictors of Arctic Grayling sex.ResultPosterior dorsal height was a reasonably accurate predictor of sex (~90% accurate at fork lengths ≥300 mm), although models containing additional morphometrics were more accurate (100% accuracy at fork lengths ≥250 mm).ConclusionThis study presents an affordable, noninvasive, and replicable method for nonlethal determination of Arctic Grayling sex by using digital images from the field, with potential application to other salmonids.

User-experience testing of an evidence-to-decision framework for selecting essential medicines.

Essential medicine lists (EMLs) are important medicine prioritization tools used by the World Health Organization (WHO) EML and over 130 countries. The criteria used by WHO's Expert Committee on the Selection and Use of Essential Medicines has parallels to the GRADE Evidence-to-Decision (EtD) frameworks. In this study, we explored the EtD frameworks and a visual abstract as adjunctive tools to strengthen the integrate evidence and improve the transparency of decisions of EML applications. We conducted user-experience testing interviews of key EML stakeholders using Morville's honeycomb model. Interviews explored multifaceted dimensions (e.g., usability) on two EML applications for the 2021 WHO EML-long-acting insulin analogues for diabetes and immune checkpoint inhibitors for lung cancer. Using a pre-determined coding framework and thematic analysis we iteratively improved both the EtD framework and the visual abstract. We coded the transcripts of 17 interviews with 13 respondents in 103 locations of the interview texts across all dimensions of the user-experience honeycomb. Respondents felt the EtD framework and visual abstract presented complementary useful and findable adjuncts to the traditional EML application. They felt this would increase transparency and efficiency in evidence assessed by EML committees. As EtD frameworks are also used in health practice guidelines, including those by the WHO, respondents articulated that the adoption of the EtD by EML applications represents a tangible mechanism to align EMLs and guidelines, decrease duplication of work and improve coordination. Improvements were made to clarify instructions for the EtD and visual abstract, and to refine the design and content included. 'Availability' was added as an additional criterion for EML applications to highlight this criterion in alignment with WHO EML criteria. EtD frameworks and visual abstracts present additional important tools to communicate evidence and support decision-criteria in EML applications, which have global health impact. Access to essential medicines is important for achieving universal health coverage, and the development of essential medicine lists should be as evidence-based and trustworthy as possible.

MemeNet: Toward a Reliable Local Projection for Image Recognition via Semantic Featurization.

When we recognize images with the help of Artificial Neural Networks (ANNs), we often wonder how they make decisions. A widely accepted solution is to point out local features as decisive evidence. A question then arises: Can local features in the latent space of an ANN explain the model output to some extent? In this work, we propose a modularized framework named MemeNet that can construct a reliable surrogate from a Convolutional Neural Network (CNN) without changing its perception. Inspired by the idea of time series classification, this framework recognizes images in two steps. First, local representations named memes are extracted from the activation map of a CNN model. Then an image is transformed into a series of understandable features. Experimental results show that MemeNet can achieve accuracy comparable to most models' through a set of reliable features and a simple classifier. Thus, it is a promising interface to use the internal dynamics of CNN, which represents a novel approach to constructing reliable models.