This paper presents an epidemiologic study of appendicitis in Taiwan over a twelve-year period. An analysis the incidence low-income population (LIP) is included to explore effects lower socioeconomic status on appendicitis.We analyzed epidemiological features using data from National Health Insurance Research Database (NHIRD) 2000 2011. All cases diagnosed as were enrolled.The overall incidences appendicitis, primary appendectomy, and perforated 107.76, 101.58, 27.20 per 100,000 year,...

Abstract Background With the rapid growth of healthcare services, health insurance fraud detection has become an important measure to ensure efficient use public funds. Traditional methods have tended focus on attributes a single visit and ignored behavioural relationships multiple visits by patients. Methods We propose model based multilevel attention mechanism that we call MHAMFD. Specifically, attributed heterogeneous information network (AHIN) different types objects their rich...

Health insurance fraud is becoming more common and impacting the fairness sustainability of health system. Traditional detection primarily relies on recognizing established data patterns. However, with ever-expanding complex nature data, it difficult for these traditional methods to effectively capture evolving fraudulent activity tactics keep pace constant improvements innovations fraudsters. As a result, there an urgent need accurate flexible analytics detect potential fraud. To address...

Controversy surrounding the role of percutaneous cholecystostomy (PC) is fed by absence large amounts data concerning its outcomes, and many authors have maintained that there no evidence to support a recommendation for PC rather than cholecystectomy (CCS) in elderly or critically ill patients with acute cholecystitis (AC). We conducted this study tracking trends utilization outcomes CCS using longitudinal health research Taiwan. Analyses were on 236,742 patients, 11,184 whom had undergone...

Although numerous epidemiological studies on appendicitis have been conducted worldwide, only a few paid attention to the effect of socioeconomic status appendicitis, particularly focusing low-income population (LIP).We analyzed features in Taiwan using data from National Health Insurance Research Database 2003 2011. All cases diagnosed as were enrolled.Between and 2011, 2,916 patients LIP 209,206 normal (NP) with appendicitis. Our finding revealed that ratios comorbidities, complicated...

Graph attention network can generate effective feature embedding by specifying different weights to nodes. The key of the research on heterogeneous graph is way combine its rich structural information with semantic relations aggregate neighborhood information. Most existing representation learning methods guide selection neighbors defining various meta-paths graphs. However, these models only consider contained in nodes under paths and ignore potential relationships neighbor structures,...

Background . From the viewpoint of prehospital emergency medicine, a greater proportion pelvic fractures not life-threatening status but combined with other injuries need more comprehensive recognition. Methods A 12-year nationwide health database inpatients was reviewed. All cases diagnosed as were enrolled. The associated classified into 20 categories further analyzed. Results During 2000–2011, hospitalized incidence in Taiwan ranged from 17.17 to 19.42 per 100,000, and an increasing trend...

Accurately predicting Drug-Drug Interaction (DDI) is a critical and challenging aspect of the drug discovery process, particularly in preventing adverse reactions patients undergoing combination therapy. However, current DDI prediction methods often overlook interaction information between chemical substructures drugs, focusing solely on drugs failing to capture sufficient substructure details. To address this limitation, we introduce novel method: Multi-layer Adaptive Soft Mask Graph Neural...

<title>Abstract</title> Graph Convolutional Networks (GCNs) is a dominant approach for graph representation learning through neighborhood aggregation.However, existing GCN methods rely on single structural view that only captures direct connections. This limitation overlooks important long-range dependencies and global topological patterns, leading to suboptimal node representations downstream tasks. To address these limitations, we propose Multi-Block Network (MBGCN) constructs two...

Although numerous epidemiological studies on cholecystectomy have been conducted worldwide, only a few considered the effect of socioeconomic inequalities outcomes. Specifically, focused low-income population (LIP).A nationwide prospective study based Taiwan National Health Insurance dataset was during 2003-2012. The International Classification ICD-9-CM procedure codes 51.2 and 51.21-51.24 were identified as inclusion criteria for cholecystectomy. Temporal trends analyzed using joinpoint...

Drug–drug interaction (DDI) prediction has received considerable attention from industry and academia. Most existing methods predict DDIs drug attributes or relationships with neighbors, which does not guarantee that informative embeddings for will be obtained. To address this limitation, we propose a multitype method based on the deep fusion of features topological relationships, abbreviated DM-DDI. The proposed adopts strategy to combine topologies learn representative DDI prediction....

Numerous epidemiological studies have compared outcomes between laparoscopic appendectomies (LA) and open (OA); however, few assessed the efficacy of LA specifically in a low-income population (LIP). We analyzed trends utilization versus OA an LIP Taiwan using data from National Health Insurance (NHI) Research Database. Steady temporal growth were observed for patients who underwent both general (GP); each study year, proportion was lower than GP procedure. The more susceptible to payment...

In this paper, we devote to aggregating longitudinal and multi-modal information from heterogeneous neighbors obtain an accurate node embedding on the dynamic graph. Recently, Heterogeneous Graph Neural Networks (GNNs) have attracted extensive attention in fraud detection. However, when faced with data such as health insurance records, existing GNN-based detectors always discard (e.g., medication treatment) of ignore inconsistent claimer behavior records. To fully utilize information,...

The traditional support vector machine (SVM) was mainly used well on balanced data classification, but didn't perform at imbalance dataset classification. In order to improve classification effects of SVM algorithm for dataset, the present paper combined merits FCM cluster and create a new (referred as FCM-SVM algorithm). Meanwhile, we adopted F-measure evaluation indicators, combining with predicting accuracy recall minority class, evaluate performance. Effectiveness FCM-SCM verified by...

Abstract The evolving intercloud enables idle resources to be traded among cloud providers facilitate utilization optimization and improve the cost-effectiveness of service for consumers. However, several challenges are raised this multi-tier dynamic market, in which not only compete consumer requests but also cooperate with each other. To establish a healthier more efficient ecosystem, paper agent-based fuzzy constraint-directed negotiation (AFCN) model fully distributed environment without...

Potential drug-drug interactions (DDI) can lead to adverse drug reactions (ADR), and DDI prediction help pharmacy researchers detect harmful early. However, existing methods fall short in fully capturing information. They typically employ a single-view input, focusing solely on features or networks. Moreover, they rely exclusively the final model layer for predictions, overlooking nuanced information present across various network layers. To address these limitations, we propose multi-scale...

Drug-drug interaction prediction plays an important role in pharmacology and clinical applications. Most traditional methods predict drug interactions based on attributes or network structure. They usually have three limitations: 1) failing to integrate features structures well, resulting less informative embeddings; 2) being restricted a single view of relationships; 3) ignoring the importance different neighbors. To tackle these challenges, this paper proposed multiview fusion dual-level...

In this paper, we use a fixed point principle regarding condensing mapping with some measure of noncompactness.We assume there is no compactness assumption, and give sufficient conditions for the existence mild solutions to classes impulsive neutral evolution differential inclusions infinite delay.A concrete example presented in end illustrate abstract theorem.

Stockpiling and scheduling plans for medical supplies represent essential preventive control measures in major public health events. In the face of infectious diseases, such as novel coronavirus disease (COVID-19), outbreak trend variability strains are often unpredictable. Hence, it is necessary to optimally adjust prevention dispatching strategy according circumstances locations maintain economic development while ensuring human survival, however, many models this scenario seldom consider...

The clinical practice of shared decision-making (SDM) has grown in importance. However, most studies on SDM concentrated providing auxiliary knowledge from the third-party standpoint without consideration for value preferences doctors and patients. essences these methods are complete manual negotiation, problems high cost, time consumption, delayed response, decision fatigue serious.

BACKGROUND: Sleep is a natural periodic state of rest for body and mind daily sleep affects physical mental health. However, it essential to address intensity characteristics affecting the memory capacity humans positively or negatively. OBJECTIVE: Using wearable devices o bserve assess effect on college students. METHODS: This study assessed 39 students who used wrist-worn devices. The spatial span test (SST) was evaluate capacity. RESULTS: indicated negative correlation between awake count...