Enhancing CTR Prediction with Context-Aware Feature Representation Learning

CTR prediction has been widely used in the real world. Many methods model feature interaction to improve their performance. However, most methods only learn a fixed representation for each feature without considering the varying importance of each feature under different contexts, resulting in inferior performance. Recently, several methods tried to learn vector-level weights for feature representations to address the fixed representation issue. However, they only produce linear transformations to refine the fixed feature representations, which are still not flexible enough to capture the varying importance of each feature under different contexts. In this paper, we propose a novel module named Feature Refinement Network (FRNet), which learns context-aware feature representations at bit-level for each feature in different contexts. FRNet consists of two key components: 1) Information Extraction Unit (IEU), which captures contextual information and cross-feature relationships to guide context-aware feature refinement; and 2) Complementary Selection Gate (CSGate), which adaptively integrates the original and complementary feature representations learned in IEU with bit-level weights. Notably, FRNet is orthogonal to existing CTR methods and thus can be applied in many existing methods to boost their performance. Comprehensive experiments are conducted to verify the effectiveness, efficiency, and compatibility of FRNet.Comment: SIGIR 202

Leukocyte transcriptome of Cushing’s disease are associated with nerve impairment and psychiatric disorders

Introduction: The hypothalamus-pituitary-adrenal (HPA) axis and its end product cortisol is a major response mechanism to stress and plays a critical role in many psychiatric disorders. Cushing’s disease (CD) serves as a valuable in vivo “hyperexpression” model to elucidate the effect of cortisol on brain function and mental disorders. Changes in brain macroscale properties measured by magnetic resonance imaging (MRI) have been detailed demonstrated, but the biological and molecular mechanisms underlying these changes remain poorly understood. Material and methods: Here we included 25 CD patients and matched 18 healthy controls for assessment, and performed transcriptome sequencing of peripheral blood leukocytes. Weighted gene co-expression network analysis (WGCNA) was performed to construct a co-expression network of the relationships between genes and we identified a significant module and hub gene types associated with neuropsychological phenotype and psychiatric disorder identified in enrichment analysis. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis preliminarily explored the biological functions of these modules. Results: The WGCNA and enrichment analysis indicated that module 3 of blood leukocytes was enriched in broadly expressed genes and was associated with neuropsychological phenotypes and mental diseases enrichment. GO and KEGG enrichment analysis of module 3 identified enrichment in many biological pathways associated with psychiatric disorders. Conclusion: Leukocyte transcriptome of Cushing’s disease is enriched in broadly expressed genes and is associated with nerve impairment and psychiatric disorders, which may reflect some changes in the affected brain

Diagnostic performance of clinical properties and conventional magnetic resonance imaging for determining the IDH1 mutation status in glioblastoma: a retrospective study

Background Glioblastoma (GBM), the most malignant form of gliomas, is a relatively common primary brain tumor in adults. Preoperative identification of isocitrate dehydrogenase 1 (IDH1) mutations in GBM is of critical prognostic importance. The aim of the present study was to explore the feasibility and diagnostic performance of basic patient information combined with conventional magnetic resonance imaging (MRI) findings for determination of the IDH1 status (mutant vs wild type) in patients with GBM. Methods From January 1, 2016 to December 31, 2017, a consecutive series of 50 patients with GBM was retrospectively collected. The patients were divided into two group according to their IDH1 mutation status. Basic information and MRI features were analyzed for the establishment of a diagnostic prediction model using logistic regression. A receiver operating characteristic curve was used to evaluate the diagnostic performance. Results Patients with IDH1-mutant tumors were younger than those with IDH1-wild type tumors, and exhibited a larger tumor volume. The diagnostic predictive model established by combining age and the tumor size exhibited a sensitivity and specificity of 70% and 93%, respectively. The area under the curve was 0.88, which indicated high diagnostic performance. Conclusion Patient age and tumor volume can be used as indicators of IDH1 mutation status in patients with GBM, with high diagnostic performance for simple evaluations in clinical practice. The combined use of these two indicators can further enhance the diagnostic specificity

Bus ridership and its determinants in Beijing: A spatial econometric perspective

Understanding the temporal and spatial dynamics and determinants of public transport ridership play an important role in urban planning. Previous studies have focused on exploring the determinants at the station level using global models, or a local model, geographically weighted regression (GWR), which cannot reveal spatial autocorrelation at the global level. This study explores the factors affecting bus ridership considering spatial autocorrelation using the spatial Durbin model (SDM). Taking the community in Beijing as the basic study unit, this study aims to explore the temporal and spatial dynamics of bus ridership and identify its key determinants considering neighboring effects. The results show the following: (1) The temporal dynamics are quite distinct on weekdays and weekends as well as at different time slots of the day. (2) The spatial patterns of bus ridership varied across different time slots, and the hot areas are mainly located near the central business district (CBD), transport hubs, and residential areas. (3) Key determinants of bus ridership varied across weekends and weekdays and varied at different time slots per day. (4) The spatial neighboring effects had been verified. This study provides a common analytical framework for analyzing the spatiotemporal dynamics and determinants of bus ridership at the community level

Comparison of endoscopic evacuation, stereotactic aspiration and craniotomy for the treatment of supratentorial hypertensive intracerebral haemorrhage: study protocol for a randomised controlled trial

Abstract Background Hypertensive intracerebral haemorrhage (HICH) is the most common form of haemorrhagic stroke with the highest morbidity and mortality of all stroke types. The choice of surgical or conservative treatment for patients with HICH remains controversial. In recent years, minimally invasive surgeries, such as endoscopic evacuation and stereotactic aspiration, have been attempted for haematoma removal and offer promise. However, research evidence on the benefits of endoscopic evacuation or stereotactic aspiration is still insufficient. Methods/design A multicentre, randomised controlled trial will be conducted to compare the efficacy of endoscopic evacuation, stereotactic aspiration and craniotomy in the treatment of supratentorial HICH. About 1350 eligible patients from 10 neurosurgical centres will be randomly assigned to an endoscopic group, a stereotactic group and a craniotomy group at a 1:1:1 ratio. Randomisation is undertaken using a 24-h randomisation service accessed by telephone or the Internet. All patients will receive the corresponding surgery based on their grouping. They will be followed-up at 1, 3 and 6 months after surgery. The primary outcome is the modified Rankin Scale at 6-month follow-up. Secondary outcomes include: haematoma clearance rate; Glasgow Coma Scale 7 days after surgery; rebleeding rate; intracranial infection rate; hospitalisation time; mortality at 1 month and 3 months after surgery; the Barthel Index and the WHO quality of life at 3 months and 6 months after surgery. Discussion The trial aims to investigate whether endoscopic evacuation and stereotactic aspiration could improve the outcome of supratentorial HICH compared with craniotomy. The trial will help to determine the best surgical method for the treatment of supratentorial HICH. Trial registration ClinicalTrials.gov, ID: NCT02811614 . Registered on 20 June 2016

Three-Dimensional Semantic Segmentation of Pituitary Adenomas Based on the Deep Learning Framework-nnU-Net: A Clinical Perspective

This study developed and evaluated nnU-Net models for three-dimensional semantic segmentation of pituitary adenomas (PAs) from contrast-enhanced T1 (T1ce) images, with aims to train a deep learning-based model cost-effectively and apply it to clinical practice. Methods: This study was conducted in two phases. In phase one, two models were trained with nnUNet using distinct PA datasets. Model 1 was trained with 208 PAs in total, and model 2 was trained with 109 primary nonfunctional pituitary adenomas (NFPA). In phase two, the performances of the two models were investigated according to the Dice similarity coefficient (DSC) in the leave-out test dataset. Results: Both models performed well (DSC > 0.8) for PAs with volumes > 1000 mm3, but unsatisfactorily (DSC 3. Conclusions: Both nnU-Net models showed good segmentation performance for PAs > 1000 mm3 (75% of the dataset) and limited performance for PAs 3 (25% of the dataset). Model 2 trained with fewer samples was more cost-effective. We propose to combine the use of model-based segmentation for PA > 1000 mm3 and manual segmentation for PA 3 in clinical practice at the current stage

Additional file 1: of Comparison of endoscopic evacuation, stereotactic aspiration and craniotomy for the treatment of supratentorial hypertensive intracerebral haemorrhage: study protocol for a randomised controlled trial

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