Comparison of Artificial Neural Network and Logistic Regression Models for Predicting In-Hospital Mortality after Primary Liver Cancer Surgery

BACKGROUND: Since most published articles comparing the performance of artificial neural network (ANN) models and logistic regression (LR) models for predicting hepatocellular carcinoma (HCC) outcomes used only a single dataset, the essential issue of internal validity (reproducibility) of the models has not been addressed. The study purposes to validate the use of ANN model for predicting in-hospital mortality in HCC surgery patients in Taiwan and to compare the predictive accuracy of ANN with that of LR model. METHODOLOGY/PRINCIPAL FINDINGS: Patients who underwent a HCC surgery during the period from 1998 to 2009 were included in the study. This study retrospectively compared 1,000 pairs of LR and ANN models based on initial clinical data for 22,926 HCC surgery patients. For each pair of ANN and LR models, the area under the receiver operating characteristic (AUROC) curves, Hosmer-Lemeshow (H-L) statistics and accuracy rate were calculated and compared using paired T-tests. A global sensitivity analysis was also performed to assess the relative significance of input parameters in the system model and the relative importance of variables. Compared to the LR models, the ANN models had a better accuracy rate in 97.28% of cases, a better H-L statistic in 41.18% of cases, and a better AUROC curve in 84.67% of cases. Surgeon volume was the most influential (sensitive) parameter affecting in-hospital mortality followed by age and lengths of stay. CONCLUSIONS/SIGNIFICANCE: In comparison with the conventional LR model, the ANN model in the study was more accurate in predicting in-hospital mortality and had higher overall performance indices. Further studies of this model may consider the effect of a more detailed database that includes complications and clinical examination findings as well as more detailed outcome data

Learning environment associated with use of mixed mode delivery model among secondary business studies students in Singapore

At many teacher education institutes around the world, preservice teachers are empowered to use pedagogical tools and strategies that engage their students. We used a modified version of the Constructivist Learning Environment Survey (CLES) to evaluate the effectiveness of a pedagogical model known as the Mixed Mode Delivery (MMD) model in terms of the CLES’s five scales of personal relevance, uncertainty, critical voice, shared control and negotiation. Comparisons were made between 2,216 secondary school students taught by the preservice teachers in an MMD group and 991 students in a control group in terms of the relative magnitudes of the gap between the actual and preferred learning environment in students’ school classrooms. The findings supported the positive impact of using MMD in terms of students’ perceptions of their classroom environments for all CLES scales

Pan-cancer analysis of whole genomes

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe

Science laboratory classroom environments in Korean high schools

In order to investigate the learning environment of senior high school science laboratory classrooms in Korea, the Science Laboratory Environment Inventory (SLEI) was translated into Korean and administered to 439 students (99 science-independent stream students, 195 science-oriented stream students and 145 humanities stream students). Data analyses attested to the sound factorial validity and internal consistency reliability of the SLEI, as well as its ability to differentiate between the perceptions of students in different classrooms. Students in the science-independent stream generally perceived their science laboratory classroom environment more favourably than did students in either the humanities or science-oriented stream. Associations were found between various measures of students’ attitudes to science and their perceptions on SLEI scales; in particular, as in past research in other countries, integration between theory and practical classes was a statistically significant predictor of all attitude criteria when the other SLEI scales were mutually controlled

GADOBENATE DIMEGLUMINE-ENHANCED MRI OF THE BREAST: ANALYSIS OF DOSE RESPONSE AND COMPARISON WITH GADOPENTETATE DIMEGLUMINE

OBJECTIVE: The purpose of this study was to evaluate the clinical efficacy and dose response relationship of three doses of gadobenate dimeglumine for MRI of the breast and to compare the results with those obtained after a dose of 0.1 mmol/kg of body weight of gadopentetate dimeglumine. SUBJECTS AND METHODS. Gadobenate dimeglumine at 0.05, 0.1, or 0.2 mmol/kg of body weight or gadopentetate dimeglumine at 0.1 mmol/kg of body weight was administered by IV bolus injection to 189 patients with known or suspected breast cancer. Coronal three-dimensional T1-weighted gradient-echo images were acquired before and at 0, 2, 4, 6, and 8 min after the administration of the dose. Images were evaluated for lesion presence, location, size, morphology, enhancement pattern, conspicuity, and type. Lesion signal intensity-time curves were acquired, and lesion matching with on-site final diagnosis was performed. A determination of global lesion detection from unenhanced to contrast-enhanced and combined images was performed, and evaluations were made of the diagnostic accuracy for lesion detection and characterization. A full safety evaluation was conducted. RESULTS: Significant dose-related increases in global lesion detection were noted for patients who received gadobenate dimeglumine (p < 0.04, all evaluations). The sensitivity for detection was comparable for 0.1 and 0.2 mmol/kg of gadobenate dimeglumine, and specificity was highest with the 0.1 mmol/kg dose. Higher detection scores and higher sensitivity values for lesion characterization were found for 0.1 mmol/kg of gadobenate dimeglumine compared with 0.1 mmol/kg of gadopentetate dimeglumine, although more variable specificity values were obtained. No differences in safety were observed, and no serious adverse events were reported. CONCLUSION: Gadobenate dimeglumine is a capable diagnostic agent for MRI of the breast. Although preliminary, our results suggest that 0.1 mmol/kg of gadobenate dimeglumine may offer advantages over doses of 0.05 and 0.2 mmol/kg of gadobenate dimeglumine and 0.1 mmol/kg of gadopentetate dimeglumine for breast lesion detection and characterization