Recall Problems Research Articles

EPIDEMIOLOGICAL AND CLINICAL CHARACTERISTICS, CAUSATIVE DRUGS, AND DIAGNOSTIC CHALLENGES OF FIXED DRUG ERUPTION IN ELDERLY PATIENTS: IS BULLOUS TYPE A MORE COMMON CLINICAL PHENOTYPE?

Objective: The present study aimed to evaluate the epidemiological and clinical features, causative drugs, and diagnostic challenges of Fixed drug eruption (FDE) in elderly patients. Material and Methods: In this single-center, retrospective, cross-sectional study, we evaluated data of all consecutive adult patients (aged >18 years) with an established diagnosis of FDE between 1996-2018 in our tertiary referral center in Turkey. Elderly patients who were aged ≥60 years at the time of diagnosis were allocated to the study. Results: Among 182 adult FDE patients, 14 (7.7%) patients (male/ female=1/1.8) were in the elderly group (mean age=66.1±6.9 years). Fix drug eruption was induced by intermittently taken drugs in all patients, 50% of whom had polypharmacy (concurrent use of ≥5 medications). Trimethoprim-sulfamethoxazole (42.9%) and non-steroidal anti-inflammatory drugs (35.7%) were the main causative drugs, while ornidazole was a remarkable novel FDE inducer since 2011. Fix drug eruption was mostly located on the trunk and extremities. Mucosal involvement was less frequent. Ten (71.4%) patients had bullous FDE (BFDE). There were no statistically significant differences between the gender and mean ages of the patients with and without BFDE. Conclusion: Our long-term experience demonstrated that FDE may also affect elderly patients. Most of the patients had BFDE raising the question of whether the bullous type is a more common clinical phenotype in these patients. Among the important diagnostic challenges of FDE in this age group, e.g., polypharmacy, multimorbidity, recall problems, cognitive disorders, frailty, and immunosenescence, BFDE should also be kept in mind as it may clinically mimic Stevens-Johnson syndrome/toxic epidermal necrolysis, and autoimmune bullous diseases.

Cognition-Mortality Associations Are More Pronounced When Estimated Jointly in Longitudinal and Time-to-Event Models

With aging populations worldwide, there is growing interest in links between cognitive decline and elevated mortality risk—and, by extension, analytic approaches to further clarify these associations. Toward this end, some researchers have compared cognitive trajectories of survivors vs. decedents while others have examined longitudinal changes in cognition as predictive of mortality risk. A two-stage modeling framework is typically used in this latter approach; however, several recent studies have used joint longitudinal-survival modeling (i.e., estimating longitudinal change in cognition conditionally on mortality risk, and vice versa). Methodological differences inherent to these approaches may influence estimates of cognitive decline and cognition-mortality associations. These effects may vary across cognitive domains insofar as changes in broad fluid and crystallized abilities are differentially sensitive to aging and mortality risk. We compared these analytic approaches as applied to data from a large-sample, repeated-measures study of older adults (N = 5,954; ages 50–87 years at assessment; 4,453 deceased at last census). Cognitive trajectories indicated worse performance in decedents and when estimated jointly with mortality risk, but this was attenuated after adjustment for health-related covariates. Better cognitive performance predicted lower mortality risk, and, importantly, cognition-mortality associations were more pronounced when estimated in joint models. Associations between mortality risk and crystallized abilities only emerged under joint estimation. This may have important implications for cognitive reserve, which posits that knowledge and skills considered well-preserved in later life (i.e., crystallized abilities) may compensate for declines in abilities more prone to neurodegeneration, such as recall memory and problem solving. Joint longitudinal-survival models thus appear to be important (and currently underutilized) for research in cognitive epidemiology.

Research on the Management Information System of College Education and Teaching Based on Web

The traditional university education and teaching management information system has the problems of low information recall, poor information precision, and long query time. Therefore, this paper designs a university education and teaching management information system based on Web. Through the analysis of the requirements of the higher education and teaching management information system, the design principle of the system is determined, and the structure design of the higher education and teaching management information system is realized; the teaching management information system management process is determined. By calculating the complexity of university education and teaching management information, the priority of query information is determined to effectively improve the processing effect of the system. Finally, the relational database model is designed to realize the design of university education and teaching management information system. In order to verify the effectiveness of this method, comparative experiments are designed. Experimental results show that this method can effectively improve the low information recall and the poor information precision and shorten the query time.

Research on self-incremental expansion method of knowledge base based on deep learning

In order to overcome the problems of low recall, low precision and long time consuming in current knowledge-base expansion algorithms, a new knowledge-base self-increment expansion algorithm based on deep learning is proposed. The data in the knowledge base is preprocessed by concept stratification, and the running example diagram of the knowledge base is designed according to concept stratification theory. Deep learning tool is used to expand the initial query words of knowledge base, and Word2vec is used to train the document set to build the knowledge base by calculating the cosine similarity. Based on the knowledge base, the noise detection model is constructed by convolution neural network. Through the deep learning, the extended words are filtered to realise the self-expanding of knowledge base. Experimental results show that the proposed algorithm has high recall rate, precision rate, and the algorithm takes less time, which verifies the effectiveness of the proposed algorithm.

Research on self-incremental expansion method of knowledge base based on deep learning

In order to overcome the problems of low recall, low precision and long time consuming in current knowledge-base expansion algorithms, a new knowledge-base self-increment expansion algorithm based on deep learning is proposed. The data in the knowledge base is preprocessed by concept stratification, and the running example diagram of the knowledge base is designed according to concept stratification theory. Deep learning tool is used to expand the initial query words of knowledge base, and Word2vec is used to train the document set to build the knowledge base by calculating the cosine similarity. Based on the knowledge base, the noise detection model is constructed by convolution neural network. Through the deep learning, the extended words are filtered to realise the self-expanding of knowledge base. Experimental results show that the proposed algorithm has high recall rate, precision rate, and the algorithm takes less time, which verifies the effectiveness of the proposed algorithm.

Multi-tag cleaning software for cyclic redundant data stream based on RFID in cloud computing

In order to overcome the problems of poor accuracy and recall and low data integrity existing in the current research results of multi-tag cleaning for cyclic redundant data streams, this paper designs a multi-tag cleaning software for cyclic redundant data streams in cloud computing based on RFID. According to the factor graph model, the software models cloud computing network, infers the overall quality of network link connection by cyclic reliability propagation method, and realises data acquisition by probability graph reasoning. The improved RFID reader reads the information of the tag data to realise the preliminary processing of the cyclic redundant data stream. Multi-label cleaner and RFID reader cooperate to complete multi-label cleaning of cyclic redundant data stream under cloud computing. The experimental results show that the proposed multi-tag cleaning software for cyclic redundant data streams has higher accuracy and recall than the results of references, and has higher data integrity.

An Electronic Component Recognition Algorithm Based on Deep Learning with a Faster SqueezeNet

Electronic component recognition plays an important role in industrial production, electronic manufacturing, and testing. In order to address the problem of the low recognition recall and accuracy of traditional image recognition technologies (such as principal component analysis (PCA) and support vector machine (SVM)), this paper selects multiple deep learning networks for testing and optimizes the SqueezeNet network. The paper then presents an electronic component recognition algorithm based on the Faster SqueezeNet network. This structure can reduce the size of network parameters and computational complexity without deteriorating the performance of the network. The results show that the proposed algorithm performs well, where the Receiver Operating Characteristic Curve (ROC) and Area Under the Curve (AUC), capacitor and inductor, reach 1.0. When the FPR is less than or equal 10 − 6 level, the TPR is greater than or equal to 0.99; its reasoning time is about 2.67 ms, achieving the industrial application level in terms of time consumption and performance.

Medical Students’ Exposure to Ethics Conflicts in Clinical Training: Implications for Timing UME Bioethics Education

While there is significant consensus that undergraduate medical education (UME) should include bioethics training, there is widespread debate about how to teach bioethics to medical students. Educators disagree about course methods and approaches, the topics that should be covered, and the effectiveness and metrics for UME ethics training. One issue that has received scant attention is the timing of bioethics education during medical training. The existing literature suggests that most medical ethics education occurs in the pre-clinical years. Follow-up studies indicate that medical students in their clinical rotations have little recall or ability to apply ethics concepts that were learned in their pre-clinical training. Trainees also report a desire for medical ethics to be taught in the context of practical application, which would suggest that the timing of pre-clinical ethics education is flawed. However, moving bioethics training to the clinical years should not be assumed to be the solution to the problems of recall and theory application. We argue that the effectiveness of timing bioethics education will depend on when medical students witness or experience particular categories of ethical dilemmas during their training. Our overarching hypothesis is that ethics education will be most effective when the bioethics training on a particular topic correlates to experiential exposure to that ethical issue. The purpose of our current study was to describe medical students exposure to particular categories of ethical conflicts, dilemmas, or issues. Our results may help bioethics educators better strategize about the most effective timing of medical ethics training in UME.

Research on local feature indexing of multimedia video based on intelligent soft computing

Aiming at the problems of poor precision and recall, long retrieval time and high energy consumption in current video image indexing methods, a local feature indexing method for multimedia video based on intelligent soft computing is proposed. Video image is segmented by maximum entropy threshold method. Based on the result of segmentation, features are clustered in two-dimensional space. Each video image is divided into several feature groups. Unified descriptors are generated for each feature group. The descriptors of each feature group are coded by binary coding. The similarity between index items and video images in database is calculated, and local feature indexing of media video is realized by looking up tables. The experimental results show that the method has high index precision and recall, low energy consumption and real-time performance. The proposed method has excellent performance and robustness.

An investigation of methods to improve recall for the patient-reported outcome measurement in COPD patients: a pilot randomised control trial and feasibility study protocol

BackgroundPatient-reported outcomes (PRO) are used to measure the effectiveness of interventions for management of chronic conditions such as chronic obstructive pulmonary disease. Many of these instruments require respondents to describe the change in their health status from baseline to a follow-up assessment and poor recall of previous health status often limits the usefulness and validity of these PRO measures. The use of technology has recently increased in PRO measurement. This study aims to mitigate the problems of poor recall by evaluating different strategies as a way to improve the validity of recall of health status among adults with COPD.MethodsA pilot randomised controlled trial of three strategies to improve patient recall will be tested in an acute care clinical environment. The first strategy is the use of tablet computer technology’s audio-visual facility, the second strategy is the provision of base line PRO responses prior to patients completing their follow-up questionnaires and third is standard practice of completing a questionnaire independently of previous responses. The feasibility of conducting this study in a busy clinical environment will be ascertained using the NIHR criteria for assessing feasibility.DiscussionThere is variability in a person’s ability to recall past events. With studies utilising patient-reported outcome measurement, it has become critically important to develop strategies and ways of supporting the patient to be more accurate recalling their health status. The adaptation of various technological features within mobile devices may provide an opportunity in clinical research studies to improve patient recall of their health status.Trial registrationANZCTR12618001605280.

Feature-enriched matrix factorization for relation extraction

Relation extraction aims at finding meaningful relationships between two named entities from within unstructured textual content. In this paper, we define the problem of information extraction as a matrix completion problem where we employ the notion of universal schemas formed as a collection of patterns derived from open information extraction systems as well as additional features derived from grammatical clause patterns and statistical topic models. One of the challenges with earlier work that employ matrix completion methods is that such approaches require a sufficient number of observed relation instances to be able to make predictions. However, in practice there is often insufficient number of explicit evidence supporting each relation type that could be used within the matrix model. Hence, existing work suffer from a low recall. In our work, we extend the work in the state of the art by proposing novel ways of integrating two sets of features, i.e., topic models and grammatical clause structures, for alleviating the low recall problem. More specifically, we propose that it is possible to (1) employ grammatical clause information from textual sentences to serve as an implicit indication of relation type and argument similarity. The basis for this is that it is likely that similar relation types and arguments are observed within similar grammatical structures, and (2) benefit from statistical topic models to determine similarity between relation types and arguments. We employ statistical topic models to determine relation type and argument similarity based on their co-occurrence within the same topics. We have performed extensive experiments based on both gold standard and silver standard datasets. The experiments show that our approach has been able to address the low recall problem in existing methods, by showing an improvement of 21% on recall and 8% on f-measure over the state of the art baseline.

Factors Affecting Academic Success -A Study on 10th Class Students of Rural and Urban Government Schools, Guntur, Andhra Pradesh, India

Student’s academic success depends and various factors, some of them are concentration, memory, friends, health, handwriting, fears and phobias, etc. Six questions were put before the students and the response was taken. A total of 1198, 10th class students was participated from rural (517) and urban (681) schools, in and around Guntur Municipal Corporation. The study revealed that significant variation is present between rural and urban students in relation to memory and handwriting. 34.15% of rural students were expressed recall problem against 19.41% of urban school students. But 22.45% of urban students were highlighted handwriting problem. It is only 14.15%, in the case of rural students. The percentage of other factors were more or less similar for rural and urban students.

How to Identify Exposed Women Who Are Infected with Neisseria gonorrhoeae.

Treatment trials of antibiotics for Neisseria gonorrhoeae infections frequently enroll primarily men with urethritis, as the diagnosis of acute gonococcal infection in men with urethritis is easily made by Gram stain of the urethral exudate, followed by confirmatory culture or nucleic acid amplification tests (NAATs). Enrolling women in treatment trials is of great importance, but N. gonorrhoeae cervical infections cause nonspecific symptoms. This makes it difficult to conduct interventional trials, as large numbers of women with nonspecific symptoms need to be screened for infection. Gram stain of cervical secretions has a strikingly low sensitivity, and culture and/or NAAT results are not available at the time of screening. This necessitates recall and delayed treatment of infected women who may not return and who may spread the infection during the interval. In this chapter we present an algorithm, derived from a comparison of women who did, or did not, become infected during exposure, which identifies those women who are highly likely to be infected before culture and/or NAAT results are available. The algorithm provides an efficient way to conduct interventional trials in women without the problem of recall and delayed treatment.

Problems of Recall on Consumer Product and Measures for Resolution

Problems of Recall on Consumer Product and Measures for Resolution

Orthopedic In-Training Examination: An Analysis of the Sports Medicine Section—An Update

Previously published studies have evaluated Orthopedic In-Training Examination sports medicine questions, but none have evaluated whether question difficulty has changed over time. Sports medicine subsection questions between 2012 and 2016 were evaluated and compared with previously published data on Orthopedic In-Training Examination from 2004 to 2009. Question categories were classified into 1 of 3 taxonomy levels-basic recall, diagnosis, and advanced problem solving. Medical University of South Carolina; Charleston, SC, 29425; Institution. Two residents evaluated the Sports Subsection questions separately. Then an attending physician evaluated the questions to resolve discrepancies. A statistician was used for analysis. Utilization of imaging modalities averaged 37%, with 28% (11/39) of the questions containing 2 or more imaging modalities. There were increases in utilization of advanced problem-solving questions (45% vs. 27%, p = 0.002) and decreases in basic recall questions (49% vs. 67%, p = 0.008) compared with previously published data. While the percentage of the Orthopedic In-Training Examination represented by sports medicine has remained relatively unchanged, there were fewer questions requiring residents to demonstrate simple recall and diagnosis, and increased demand to perform advanced problem solving while utilizing multiple imaging modalities.

"Knowledge base recall: detecting and resolving the unknown unknowns" by Simon Razniewski and Gerhard Weikum with Martin Vesely as coordinator

Knowledge bases about entities like people, places and products have become key assets of search and recommender systems. The largest of them contain many millions of entities and billions of facts about them. Nevertheless, they have major gaps and limitations in what they cover, thus posing the challenge of detecting and resolving these "unknown unknowns". This paper provides an overview on the problems in mapping knowledge base recall and the existing approaches to address these issues. Specifically, we discuss i) formalisms and tools for describing incompleteness, ii) rule mining methods to assess recall, iii) text mining methods to this end, and iv) approaches towards relative recall and informativeness.

Safeguarding practice in England where access to an adult at risk is obstructed by a third party: findings from a survey

Purpose Being able to speak in private to an adult about whom there is a safeguarding concern is central to English local authorities’ duty under the Care Act 2014 to make enquiries in such cases. While there has been an on-going debate about whether social workers or others should have new powers to effect these enquiries, it has been unclear how common obstructive behaviour by third parties is and how often this causes serious problems or is unresolved. The purpose of this paper is to address this knowledge gap. Design/methodology/approach A survey of local authority adult safeguarding managers was conducted in 2016 and interviews were undertaken with managers and social workers in three local authorities. Data were analysed descriptively. Findings Estimates of numbers and frequency of cases of obstruction varied widely. Most survey respondents and interview participants described situations where there had been some problems in accessing an adult at risk. Those that were serious and long-standing problems of access were few in number, but were time consuming and often distressing for the professionals involved. Research limitations/implications Further survey research on the prevalence of obstructive behaviour of third parties may not command greater response rates unless there is a specific policy proposal or a case that has “hit the headlines”. Other forms of data collection and reporting may be worth considering. Interview data likewise potentially suffer from problems of recall and definition. Practical implications At times professionals will hear of, or encounter, difficulties in accessing an adult at risk about whom there is concern. Support from supervisors and managers is needed by practitioners as such cases can be distressing. Localities may wish to collect and reflect upon such cases so that there is learning from practice about possible resolution and outcomes. Social implications There is no evidence of large numbers of cases where access is denied or very difficult. Those cases where there are problems are memorable to practitioners. Small numbers of cases, however, do not necessarily mean that the problem of gaining access is insignificant. Originality/value This study addressed a question which is topical in England and provides evidence about the frequency of the problem of gaining access to adults at risk. There has been no comparable study in England.

Who Has Trouble Reporting Prior Day Events?

Research has shown that surveys that require respondents to recall events can be subject to fairly high measurement error. Recall error tends be less problematic for highly salient events and events that have recently occurred. However, there is less information on whether some respondents are more or less prone to having problems with answering questions that involve recalling an event. This research uses data from the American Driving Study where people are asked to report the length of driving trips that they made yesterday. We analyze of over 16,000 reported driving trips from data collected from 7,913 respondents who reported having been the driver for at least one driving trip on the day before they were interviewed (yesterday). For this analysis, we are concerned with two types of recall problems; 1) the inability of the respondent to provide an estimate of either the length or duration of a driving trip; 2) providing an estimate of miles driven that is inconsistent given the duration and purpose of the trip. This paper finds difference in the characteristics of respondents who are more likely to have problems reporting their prior day driving behavior. But, the main finding is that longer trips were harder to report on and have a bigger impact on key survey estimates. We conclude with some discussion of important considerations that survey practitioners should keep in mind when designing surveys that include recall questions.

Variations in cognitive abilities across the life course: Cross-sectional evidence from Understanding Society: The UK Household Longitudinal Study

BackgroundPopulations worldwide are aging. Cognitive decline is an important precursor of dementia, illness and death and, even within the normal range, is associated with poorer performance on everyday tasks. However, the impact of age on cognitive function does not always receive the attention it deserves. MethodsWe have explored cross-sectional associations of age with five cognitive tests (word recall, verbal fluency, subtraction, number sequence, and numerical problem solving) in a large representative sample of over 40,000 men and women aged 16 to 100 living in the UK. ResultsWomen performed better on word recall tests and men had higher scores for subtraction, number sequence and numerical problem solving. However, age-cognition associations were generally similar in both genders. Mean word recall and number sequence scores decreased from early adulthood with steeper declines from the mid-60s onwards Verbal fluency, subtraction and numerical problem solving scores remained stable or increased from early to mid-adulthood, followed by approximately linear declines from around age 60. Performance on all tests was progressively lower in respondents with increasingly worse self-rated health and memory. Age-related declines in word recall, verbal fluency and number sequence started earlier in those with the worst self-rated health. There was no compelling evidence for age dedifferentiation (that the general factor of cognitive ability changes in strength with age). ConclusionsWe have confirmed previously observed patterns of cognitive aging using a large representative population sample.

Comparison of Cognitive Parameters Between Bilateral and Unilateral Hippocampal Sclerosis.

Recent studies showed that hippocampal sclerosis (HS) patients with unilateral involvement had more diffuse cognitive impairment than expected. Therefore, we aimed to compare the cognitive profiles of bilateral HS (BHS) patients with unilateral HS (UHS) patients. Consecutive patients, diagnosed with epilepsy, who fulfilled two major magnetic resonance imaging (MRI) criteria (T1 atrophy and T2-FLAIR hyperintensity) for HS were included. Standard neuro-psychological test (NPT) battery consisted of the Turkish version of 15-word verbal memory processes test, Wechsler memory scale visual reproduction subtest, forward and backward digit span, phonemic and semantic fluency, and Stroop test were applied; and the groups with right HS, left HS, and bilateral HS were compared statistically. Ninety-one patients, completing the NPT (34 males, 57 females)-16 with BHS, 36 with right HS, and 39 with left HS-were included. Six out of 43 operated patients had BHS. There were no significant differences in education and handedness of the groups. Even though NPT performances of the BHS group were found to be poor compared to UHS subgroups, this was beyond statistical significance. Comparison of BHS with the right HS group showed a significant difference in the learning score of the Verbal Memory Processes Test, but recognition scores were found to be similar in all groups. Compared to the BHS group, both right and left HS groups revealed a significant difference in delayed recall score of the Verbal Memory Processes Test. Although there were no significant differences in the postoperative parameters of the BHS group, UHS subgroups had deficits in many postoperative parameters. Our study revealed that bilateral involvement of the hippocampi was correlated with a poor cognitive performance. Retrieval failure, rather than a total recall problem, in the memory of the patients resembles a more diffuse involvement not only limited to limbic structures.