Recoding between two types of STM representation revealed by the dynamics of memory search

Visual STM (VSTM) is thought to be related to visual attention in several ways. Attention controls access to VSTM during memory encoding and plays a role in the maintenance of stored information by strengthening memorized content. We investigated the involvement of visual attention in recall from VSTM. In two experiments, we measured electrophysiological markers of attention in a memory search task with varying intervals between VSTM encoding and recall, and so we were able to track recoding of representations in memory. Results confirmed the involvement of attention in VSTM recall. However, the amplitude of the N2pc and N3rs components, which mark orienting of attention and search within VSTM, decreased as a function of delay. Conversely, the amplitude of the P3 and sustained posterior contralateral negativity components increased as a function of delay, effectively the opposite of the N2pc and N3rs modulations. These effects were only observed when verbal memory was not taxed. Thus, the results suggested that gradual recoding from visuospatial orienting of attention into verbal recall mechanisms takes place from short to long retention intervals. Interestingly, recall at longer delays was faster than at short delays, indicating that verbal representation is coupled with faster responses. These results extend the orienting-of-attention hypothesis by including an account of representational recoding during short-term consolidation and its consequences for recall from VSTM

Lung cancer treatment costs, including patient responsibility, by disease stage and treatment modality, 1992 to 2003

AbstractObjectivesThe objective of this analysis was to estimate costs for lung cancer care and evaluate trends in the share of treatment costs that are the responsibility of Medicare beneficiaries.MethodsThe Surveillance, Epidemiology, and End Results (SEER)-Medicare data from 1991–2003 for 60,231 patients with lung cancer were used to estimate monthly and patient-liability costs for clinical phases of lung cancer (prediagnosis, staging, initial, continuing, and terminal), stratified by treatment, stage, and non-small- versus small-cell lung cancer. Lung cancer-attributable costs were estimated by subtracting each patient's own prediagnosis costs. Costs were estimated as the sum of Medicare reimbursements (payments from Medicare to the service provider), co-insurance reimbursements, and patient-liability costs (deductibles and “co-payments” that are the patient's responsibility). Costs and patient-liability costs were fit with regression models to compare trends by calendar year, adjusting for age at diagnosis.ResultsThe monthly treatment costs for a 72-year-old patient, diagnosed with lung cancer in 2000, in the first 6 months ranged from $2687 (no active treatment) to$9360 (chemo-radiotherapy); costs varied by stage at diagnosis and histologic type. Patient liability represented up to 21.6% of care costs and increased over the period 1992–2003 for most stage and treatment categories, even when care costs decreased or remained unchanged. The greatest monthly patient liability was incurred by chemo-radiotherapy patients, which ranged from $1617 to$2004 per month across cancer stages.ConclusionsCosts for lung cancer care are substantial, and Medicare is paying a smaller proportion of the total cost over time

CSNL: A cost-sensitive non-linear decision tree algorithm

This article presents a new decision tree learning algorithm called CSNL that induces Cost-Sensitive Non-Linear decision trees. The algorithm is based on the hypothesis that nonlinear decision nodes provide a better basis than axis-parallel decision nodes and utilizes discriminant analysis to construct nonlinear decision trees that take account of costs of misclassification. The performance of the algorithm is evaluated by applying it to seventeen datasets and the results are compared with those obtained by two well known cost-sensitive algorithms, ICET and MetaCost, which generate multiple trees to obtain some of the best results to date. The results show that CSNL performs at least as well, if not better than these algorithms, in more than twelve of the datasets and is considerably faster. The use of bagging with CSNL further enhances its performance showing the significant benefits of using nonlinear decision nodes. The performance of the algorithm is evaluated by applying it to seventeen data sets and the results are compared with those obtained by two well known cost-sensitive algorithms, ICET and MetaCost, which generate multiple trees to obtain some of the best results to date. The results show that CSNL performs at least as well, if not better than these algorithms, in more than twelve of the data sets and is considerably faster. The use of bagging with CSNL further enhances its performance showing the significant benefits of using non-linear decision nodes

Deployment of spatial attention towards locations in memory representations: an EEG study

Recalling information from visual short-term memory (VSTM) involves the same neural mechanisms as attending to an actually perceived scene. In particular, retrieval from VSTM has been associated with orienting of visual attention towards a location within a spatially-organized memory representation. However, an open question concerns whether spatial attention is also recruited during VSTM retrieval even when performing the task does not require access to spatial coordinates of items in the memorized scene. The present study combined a visual search task with a modified, delayed central probe protocol, together with EEG analysis, to answer this question. We found a temporal contralateral negativity (TCN) elicited by a centrally presented go-signal which was spatially uninformative and featurally unrelated to the search target and informed participants only about a response key that they had to press to indicate a prepared target-present vs. -absent decision. This lateralization during VSTM retrieval (TCN) provides strong evidence of a shift of attention towards the target location in the memory representation, which occurred despite the fact that the present task required no spatial (or featural) information from the search to be encoded, maintained, and retrieved to produce the correct response and that the go-signal did not itself specify any information relating to the location and defining feature of the target

Prevention of childhood poisoning in the home: overview of systematic reviews and a systematic review of primary studies

Unintentional poisoning is a significant child public health problem. This systematic overview of reviews, supplemented with a systematic review of recently published primary studies synthesizes evidence on non-legislative interventions to reduce childhood poisonings in the home with particular reference to interventions that could be implemented by Children's Centres in England or community health or social care services in other high income countries. Thirteen systematic reviews, two meta-analyses and 47 primary studies were identified. The interventions most commonly comprised education, provision of cupboard/drawer locks, and poison control centre (PCC) number stickers. Meta-analyses and primary studies provided evidence that interventions improved poison prevention practices. Twenty eight per cent of studies reporting safe medicine storage (OR from meta-analysis 1.57, 95% CI 1.22–2.02), 23% reporting safe storage of other products (OR from meta-analysis 1.63, 95% CI 1.22–2.17) and 46% reporting availability of PCC numbers (OR from meta-analysis 3.67, 95% CI 1.84–7.33) demonstrated significant effects favouring the intervention group. There was a lack of evidence that interventions reduced poisoning rates. Parents should be provided with poison prevention education, cupboard/drawer locks and emergency contact numbers to use in the event of a poisoning. Further research is required to determine whether improving poison prevention practices reduces poisoning rates

A survey of cost-sensitive decision tree induction algorithms

The past decade has seen a significant interest on the problem of inducing decision trees that take account of costs of misclassification and costs of acquiring the features used for decision making. This survey identifies over 50 algorithms including approaches that are direct adaptations of accuracy based methods, use genetic algorithms, use anytime methods and utilize boosting and bagging. The survey brings together these different studies and novel approaches to cost-sensitive decision tree learning, provides a useful taxonomy, a historical timeline of how the field has developed and should provide a useful reference point for future research in this field

Breast cancer risk, worry, and anxiety: Effect on patient perceptions of false-positive screening results

OBJECTIVE: The impact of mammography screening recall on quality-of-life (QOL) has been studied in women at average risk for breast cancer, but it is unknown whether these effects differ by breast cancer risk level. We used a vignette-based survey to evaluate how women across the spectrum of breast cancer risk perceive the experience of screening recall. METHODS: Women participating in mammography or breast MRI screening were recruited to complete a vignette-based survey. Using a numerical rating scale (0-100), women rated QOL for hypothetical scenarios of screening recall, both before and after benign results were known. Lifetime breast cancer risk was calculated using Gail and BRCAPRO risk models. Risk perception, trait anxiety, and breast cancer worry were assessed using validated instruments. RESULTS: The final study cohort included 162 women at low (n = 43, 26%), intermediate (n = 66, 41%), and high-risk (n = 53, 33%). Actual breast cancer risk was not a predictor of QOL for any of the presented scenarios. Across all risk levels, QOL ratings were significantly lower for the period during diagnostic uncertainty compared to after benign results were known (p \u3c 0.05). In multivariable regression analyses, breast cancer worry was a significant predictor of decreased QoL for all screening scenarios while awaiting results, including scenarios with non-invasive imaging alone or with biopsy. High trait anxiety and family history predicted lower QOL scores after receipt of benign test results (p \u3c 0.05). CONCLUSIONS: Women with high trait anxiety and family history may particularly benefit from discussions about the risk of recall when choosing a screening regimen

A cluster randomized, controlled trial of breast and cervix cancer screening in Mumbai, India: methodology and interim results after three rounds of screening

Cervix and Breast cancers are the most common cancers among women worldwide and extract a large toll in developing countries. In May 1998, supported by a grant from the NCI (US), the Tata Memorial Hospital, Mumbai, India, started a cluster-randomized, controlled, screening-trial for cervix and breast cancer using trained primary health workers to provide health-education, visual-inspection of cervix (with 4% acetic acid-VIA) and clinical breast examination (CBE) in the screening arm, and only health education in the control arm. Four rounds of screening at 2-year intervals will be followed by 8 years of monitoring for incidence and mortality from cervix and breast cancers. The methodology and interim results after three rounds of screening are presented here. Good randomization was achieved between the screening (n = 75360) and control arms (n = 76178). In the screening arm we see: High screening participation rates; Low attrition; Good compliance to diagnostic confirmation; Significant downstaging; Excellent treatment completion rate; Improving case fatality ratios. The ever-screened and never-screened participants in the screening arm show significant differences with reference to the variables religion, language, age, education, occupation, income and health-seeking behavior for gynecological and breast-related complaints. During the same period, in the control arm we see excellent participation rate for health education; Low attrition and a good number of symptomatic referrals for both cervix and breast

Probabilistic reframing for cost-sensitive regression

© ACM, 2014. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in ACM Transactions on Knowledge Discovery from Data (TKDD), VOL. 8, ISS. 4, (October 2014) http://doi.acm.org/10.1145/2641758Common-day applications of predictive models usually involve the full use of the available contextual information. When the operating context changes, one may fine-tune the by-default (incontextual) prediction or may even abstain from predicting a value (a reject). Global reframing solutions, where the same function is applied to adapt the estimated outputs to a new cost context, are possible solutions here. An alternative approach, which has not been studied in a comprehensive way for regression in the knowledge discovery and data mining literature, is the use of a local (e.g., probabilistic) reframing approach, where decisions are made according to the estimated output and a reliability, confidence, or probability estimation. In this article, we advocate for a simple two-parameter (mean and variance) approach, working with a normal conditional probability density. Given the conditional mean produced by any regression technique, we develop lightweight “enrichment” methods that produce good estimates of the conditional variance, which are used by the probabilistic (local) reframing methods. We apply these methods to some very common families of costsensitive problems, such as optimal predictions in (auction) bids, asymmetric loss scenarios, and rejection rules.This work was supported by the MEC/MINECO projects CONSOLIDER-INGENIO CSD2007-00022 and TIN 2010-21062-C02-02, and TIN 2013-45732-C4-1-P and GVA projects PROMETEO/2008/051 and PROMETEO2011/052. Finally, part of this work was motivated by the REFRAME project (http://www.reframe-d2k.org) granted by the European Coordinated Research on Long-term Challenges in Information and Communication Sciences & Technologies ERA-Net (CHIST-ERA) and funded by Ministerio de Economia y Competitividad in Spain (PCIN-2013-037).Hernández Orallo, J. (2014). Probabilistic reframing for cost-sensitive regression. ACM Transactions on Knowledge Discovery from Data. 8(4):1-55. https://doi.org/10.1145/2641758S15584G. Bansal, A. Sinha, and H. Zhao. 2008. 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