A Pairwise Naïve Bayes Approach to Bayesian Classification

Despite the relatively high accuracy of the naïve Bayes (NB) classifier, there may be several instances where it is not optimal, i.e. does not have the same classification performance as the Bayes classifier utilizing the joint distribution of the examined attributes. However, the Bayes classifier can be computationally intractable due to its required knowledge of the joint distribution. Therefore, we introduce a “pairwise naïve” Bayes (PNB) classifier that incorporates all pairwise relationships among the examined attributes, but does not require specification of the joint distribution. In this paper, we first describe the necessary and sufficient conditions under which the PNB classifier is optimal. We then discuss sufficient conditions for which the PNB classifier, and not NB, is optimal for normal attributes. Through simulation and actual studies, we evaluate the performance of our proposed classifier relative to the Bayes and NB classifiers, along with the HNB, AODE, LBR and TAN classifiers, using normal density and empirical estimation methods. Our applications show that the PNB classifier using normal density estimation yields the highest accuracy for data sets containing continuous attributes. We conclude that it offers a useful compromise between the Bayes and NB classifiers

Challenges of Integrating an Evidence-based Intervention in Health Departments to Prevent Excessive Gestational Weight Gain among Low-income Women

To examine health departments’ (HD) capacity to adapt and implement an intervention to prevent excessive gestational weight gain

Normal prehospital electrocardiography is linked to long-term survival in patients presenting to the emergency department with symptoms of acute coronary syndrome

We studied 735 patients who activated “911” for chest pain and/or anginal equivalent symptoms and received 12-lead ECG monitoring with specialized ischemia monitoring software in the ambulance. Prehospital electrocardiograms (PH ECG) were analyzed to determine the proportion of patients who present with completely normal PH ECG findings (absence of ischemia/infarction, arrhythmia, or any other abnormality) and to compare outcomes amongst patients with and without any PH ECG abnormality

Episodic memory of odors stratifies Alzheimer biomarkers in normal elderly: POEM: Odor Memory Biomarker in Normal Elderly

To relate a novel test of identifying and recalling odor percepts to biomarkers of Alzheimer’s Disease (AD) in well-characterized elderly individuals, ranging from cognitively normal to demented

Patient reminder and recall interventions to improve immunization rates

BackgroundImmunization rates for children and adults are rising, but coverage levels have not reached optimal goals. As a result, vaccine-preventable diseases still occur. In an era of increasing complexity of immunization schedules, rising expectations about the performance of primary care, and large demands on primary care providers, it is important to understand and promote interventions that work in primary care settings to increase immunization coverage. One common theme across immunization programs in many nations involves the challenge of implementing a population-based approach and identifying all eligible recipients, for example the children who should receive the measles vaccine. However, this issue is gradually being addressed through the availability of immunization registries and electronic health records. A second common theme is identifying the best strategies to promote high vaccination rates. Three types of strategies have been studied: (1) patient-oriented interventions, such as patient reminder or recall, (2) provider interventions, and (3) system interventions, such as school laws. One of the most prominent intervention strategies, and perhaps best studied, involves patient reminder or recall systems. This is an update of a previously published review.ObjectivesTo evaluate and compare the effectiveness of various types of patient reminder and recall interventions to improve receipt of immunizations.Search methodsWe searched CENTRAL, MEDLINE, Embase and CINAHL to January 2017. We also searched grey literature and trial registers to January 2017.Selection criteriaWe included randomized trials, controlled before and after studies, and interrupted time series evaluating immunization-focused patient reminder or recall interventions in children, adolescents, and adults who receive immunizations in any setting. We included no-intervention control groups, standard practice activities that did not include immunization patient reminder or recall, media-based activities aimed at promoting immunizations, or simple practice-based awareness campaigns. We included receipt of any immunizations as eligible outcome measures, excluding special travel immunizations. We excluded patients who were hospitalized for the duration of the study period.Data collection and analysisWe used the standard methodological procedures expected by Cochrane and the Cochrane Effective Practice and Organisation of Care (EPOC) Group. We present results for individual studies as relative rates using risk ratios, and risk differences for randomized trials, and as absolute changes in percentage points for controlled before-after studies. We present pooled results for randomized trials using the random-effects model.Main resultsThe 75 included studies involved child, adolescent, and adult participants in outpatient, community-based, primary care, and other settings in 10 countries.Patient reminder or recall interventions, including telephone and autodialer calls, letters, postcards, text messages, combination of mail or telephone, or a combination of patient reminder or recall with outreach, probably improve the proportion of participants who receive immunization (risk ratio (RR) of 1.28, 95% confidence interval (CI) 1.23 to 1.35; risk difference of 8%) based on moderate certainty evidence from 55 studies with 138,625 participants.Three types of single-method reminders improve receipt of immunizations based on high certainty evidence: the use of postcards (RR 1.18, 95% CI 1.08 to 1.30; eight studies; 27,734 participants), text messages (RR 1.29, 95% CI 1.15 to 1.44; six studies; 7772 participants), and autodialer (RR 1.17, 95% CI 1.03 to 1.32; five studies; 11,947 participants). Two types of single-method reminders probably improve receipt of immunizations based on moderate certainty evidence: the use of telephone calls (RR 1.75, 95% CI 1.20 to 2.54; seven studies; 9120 participants) and letters to patients (RR 1.29, 95% CI 1.21 to 1.38; 27 studies; 81,100 participants).Based on high certainty evidence, reminders improve receipt of immunizations for childhood (RR 1.22, 95% CI 1.15 to 1.29; risk difference of 8%; 23 studies; 31,099 participants) and adolescent vaccinations (RR 1.29, 95% CI 1.17 to 1.42; risk difference of 7%; 10 studies; 30,868 participants). Reminders probably improve receipt of vaccinations for childhood influenza (RR 1.51, 95% CI 1.14 to 1.99; risk difference of 22%; five studies; 9265 participants) and adult influenza (RR 1.29, 95% CI 1.17 to 1.43; risk difference of 9%; 15 studies; 59,328 participants) based on moderate certainty evidence. They may improve receipt of vaccinations for adult pneumococcus, tetanus, hepatitis B, and other non-influenza vaccinations based on low certainty evidence although the confidence interval includes no effect of these interventions (RR 2.08, 95% CI 0.91 to 4.78; four studies; 8065 participants).Authors' conclusionsPatient reminder and recall systems, in primary care settings, are likely to be effective at improving the proportion of the target population who receive immunizations

A Pairwise Naïve Bayes Approach to Bayesian Classification

Despite the relatively high accuracy of the naïve Bayes (NB) classifier, there may be several instances where it is not optimal, i.e. does not have the same classification performance as the Bayes classifier utilizing the joint distribution of the examined attributes. However, the Bayes classifier can be computationally intractable due to its required knowledge of the joint distribution. Therefore, we introduce a “pairwise naïve” Bayes (PNB) classifier that incorporates all pairwise relationships among the examined attributes, but does not require specification of the joint distribution. In this paper, we first describe the necessary and sufficient conditions under which the PNB classifier is optimal. We then discuss sufficient conditions for which the PNB classifier, and not NB, is optimal for normal attributes. Through simulation and actual studies, we evaluate the performance of our proposed classifier relative to the Bayes and NB classifiers, along with the HNB, AODE, LBR and TAN classifiers, using normal density and empirical estimation methods. Our applications show that the PNB classifier using normal density estimation yields the highest accuracy for data sets containing continuous attributes. We conclude that it offers a useful compromise between the Bayes and NB classifiers

Normal prehospital electrocardiography is linked to long-term survival in patients presenting to the emergency department with symptoms of acute coronary syndrome

AIMS/METHODS: We studied 735 patients who activated “911” for chest pain and/or anginal equivalent symptoms and received 12-lead ECG monitoring with specialized ischemia monitoring software in the ambulance. Prehospital electrocardiograms (PH ECG) were analyzed to determine the proportion of patients who present with completely normal PH ECG findings (absence of ischemia/infarction, arrhythmia, or any other abnormality) and to compare outcomes amongst patients with and without any PH ECG abnormality. RESULTS: Of 735 patients (mean age 70.5, 52.4% male), 68 (9.3%) patients had completely normal PH ECG findings. They experienced significantly less adverse hospital outcomes (12% vs 37%), length of stay (1.19 vs 3.86 days), and long-term mortality (9% vs 28%) than those with any PH ECG abnormality (p<.05). CONCLUSION: Normal PH ECG findings are associated with better short and long-term outcomes in ambulance patients with ischemic symptoms. These findings may enhance early triage and risk stratification in emergency cardiac care