MASMDDI: multi-layer adaptive soft-mask graph neural network for drug-drug interaction prediction.

Accurately predicting Drug-Drug Interaction (DDI) is a critical and challenging aspect of the drug discovery process, particularly in preventing adverse reactions in patients undergoing combination therapy. However, current DDI prediction methods often overlook the interaction information between chemical substructures of drugs, focusing solely on the interaction information between drugs and failing to capture sufficient chemical substructure details. To address this limitation, we introduce a novel DDI prediction method: Multi-layer Adaptive Soft Mask Graph Neural Network (MASMDDI). Specifically, we first design a multi-layer adaptive soft mask graph neural network to extract substructures from molecular graphs. Second, we employ an attention mechanism to mine substructure feature information and update latent features. In this process, to optimize the final feature representation, we decompose drug-drug interactions into pairwise interaction correlations between the core substructures of each drug. Third, we use these features to predict the interaction probabilities of DDI tuples and evaluate the model using real-world datasets. Experimental results demonstrate that the proposed model outperforms state-of-the-art methods in DDI prediction. Furthermore, MASMDDI exhibits excellent performance in predicting DDIs of unknown drugs in two tasks that are more aligned with real-world scenarios. In particular, in the transductive scenario using the DrugBank dataset, the ACC and AUROC and AUPRC scores of MASMDDI are 0.9596, 0.9903, and 0.9894, which are 2% higher than the best performing baseline.

Health insurance fraud detection based on multi-channel heterogeneous graph structure learning.

Health insurance fraud is becoming more common and impacting the fairness and sustainability of the health insurance system. Traditional health insurance fraud detection primarily relies on recognizing established data patterns. However, with the ever-expanding and complex nature of health insurance data, it is difficult for these traditional methods to effectively capture evolving fraudulent activity and tactics and keep pace with the constant improvements and innovations of fraudsters. As a result, there is an urgent need for more accurate and flexible analytics to detect potential fraud. To address this, the Multi-channel Heterogeneous Graph Structured Learning-based health insurance fraud detection method (MHGSL) was proposed. MHGSL constructs a graph of health insurance data from various entities, such as patients, departments, and medicines, and employs graph structure learning to extract topological structure, features, and semantic information to construct multiple graphs that reflect the diversity and complexity of the data. We utilize deep learning methods such as heterogeneous graph neural networks and graph convolutional neural networks to combine multi-channel information transfer and feature fusion to detect anomalies in health insurance data. The results of extensive experiments on real health insurance data demonstrate that MHGSL achieves a high level of accuracy in detecting potential fraud, which is better than existing methods, and is able to quickly and accurately identify patients with fraudulent behaviors to avoid loss of health insurance funds. Experiments have shown that multi-channel heterogeneous graph structure learning in MHGSL can be very helpful for health insurance fraud detection. It provides a promising solution for detecting health insurance fraud and improving the fairness and sustainability of the health insurance system. Subsequent research on fraud detection methods can consider semantic information between patients and different types of entities.

Prediction of multiple types of drug interactions based on multi-scale fusion and dual-view fusion.

Potential drug-drug interactions (DDI) can lead to adverse drug reactions (ADR), and DDI prediction can help pharmacy researchers detect harmful DDI early. However, existing DDI prediction methods fall short in fully capturing drug information. They typically employ a single-view input, focusing solely on drug features or drug networks. Moreover, they rely exclusively on the final model layer for predictions, overlooking the nuanced information present across various network layers. To address these limitations, we propose a multi-scale dual-view fusion (MSDF) method for DDI prediction. More specifically, MSDF first constructs two views, topological and feature views of drugs, as model inputs. Then a graph convolutional neural network is used to extract the feature representations from each view. On top of that, a multi-scale fusion module integrates information across different graph convolutional layers to create comprehensive drug embeddings. The embeddings from the two views are summed as the final representation for classification. Experiments on two real-world datasets demonstrate that MSDF achieves higher accuracy than state-of-the-art methods, as the dual-view, multi-scale approach better captures drug characteristics.

An opponent model for agent-based shared decision-making via a genetic algorithm.

Introduction: Shared decision-making (SDM) has received a great deal of attention as an effective way to achieve patient-centered medical care. SDM aims to bring doctors and patients together to develop treatment plans through negotiation. However, time pressure and subjective factors such as medical illiteracy and inadequate communication skills prevent doctors and patients from accurately expressing and obtaining their opponent's preferences. This problem leads to SDM being in an incomplete information environment, which significantly reduces the efficiency of the negotiation and even leads to failure. Methods: In this study, we integrated a negotiation strategy that predicts opponent preference using a genetic algorithm with an SDM auto-negotiation model constructed based on fuzzy constraints, thereby enhancing the effectiveness of SDM by addressing the problems posed by incomplete information environments and rapidly generating treatment plans with high mutual satisfaction. Results: A variety of negotiation scenarios are simulated in experiments and the proposed model is compared with other excellent negotiation models. The results indicated that the proposed model better adapts to multivariate scenarios and maintains higher mutual satisfaction. Discussion: The agent negotiation framework supports SDM participants in accessing treatment plans that fit individual preferences, thereby increasing treatment satisfaction. Adding GA opponent preference prediction to the SDM negotiation framework can effectively improve negotiation performance in incomplete information environments.

Health insurance fraud detection by using an attributed heterogeneous information network with a hierarchical attention mechanism.

BACKGROUND: With the rapid growth of healthcare services, health insurance fraud detection has become an important measure to ensure efficient use of public funds. Traditional fraud detection methods have tended to focus on the attributes of a single visit and have ignored the behavioural relationships of multiple visits by patients. METHODS: We propose a health insurance fraud detection model based on a multilevel attention mechanism that we call MHAMFD. Specifically, we use an attributed heterogeneous information network (AHIN) to model different types of objects and their rich attributes and interactions in a healthcare scenario. MHAMFD selects appropriate neighbour nodes based on the behavioural relationships at different levels of a patient's visit. We also designed a hierarchical attention mechanism to aggregate complex semantic information from the interweaving of different levels of behavioural relationships of patients. This increases the feature representation of objects and makes the model interpretable by identifying the main factors of fraud. RESULTS: Experimental results using real datasets showed that MHAMFD detected health insurance fraud with better accuracy than existing methods. CONCLUSIONS: Experiment suggests that the behavioral relationships between patients' multiple visits can also be of great help to detect health care fraud. Subsequent research fraud detection methods can also take into account the different behavioral relationships between patients.

MFDA: Multiview fusion based on dual-level attention for drug interaction prediction.

Drug-drug interaction prediction plays an important role in pharmacology and clinical applications. Most traditional methods predict drug interactions based on drug attributes or network structure. They usually have three limitations: 1) failing to integrate drug features and network structures well, resulting in less informative drug embeddings; 2) being restricted to a single view of drug interaction relationships; 3) ignoring the importance of different neighbors. To tackle these challenges, this paper proposed a multiview fusion based on dual-level attention to predict drug interactions (called MFDA). The MFDA first constructed multiple views for the drug interaction relationship, and then adopted a cross-fusion strategy to deeply fuse drug features with the drug interaction network under each view. To distinguish the importance of different neighbors and views, MFDA adopted a dual-level attention mechanism (node level and view level) to obtain the unified drug embedding for drug interaction prediction. Extensive experiments were conducted on real datasets, and the MFDA demonstrated superior performance compared to state-of-the-art baselines. In the multitask analysis of new drug reactions, MFDA obtained higher scores on multiple metrics. In addition, its prediction results corresponded to specific drug reaction events, which achieved more accurate predictions.

Multitype drug interaction prediction based on the deep fusion of drug features and topological relationships.

Drug-drug interaction (DDI) prediction has received considerable attention from industry and academia. Most existing methods predict DDIs from drug attributes or relationships with neighbors, which does not guarantee that informative drug embeddings for prediction will be obtained. To address this limitation, we propose a multitype drug interaction prediction method based on the deep fusion of drug features and topological relationships, abbreviated DM-DDI. The proposed method adopts a deep fusion strategy to combine drug features and topologies to learn representative drug embeddings for DDI prediction. Specifically, a deep neural network model is first used on the drug feature matrix to extract feature information, while a graph convolutional network model is employed to capture structural information from the adjacency matrix. Then, we adopt delivery operations that allow the two models to exchange information between layers, as well as an attention mechanism for a weighted fusion of the two learned embeddings before the output layer. Finally, the unified drug embeddings for the downstream task are obtained. We conducted extensive experiments on real-world datasets, the experimental results demonstrated that DM-DDI achieved more accurate prediction results than state-of-the-art baselines. Furthermore, in two tasks that are more similar to real-world scenarios, DM-DDI outperformed other prediction methods for unknown drugs.

Fuzzy constraint-based agent negotiation framework for doctor-patient shared decision-making.

BACKGROUND: The clinical practice of shared decision-making (SDM) has grown in importance. However, most studies on SDM practice concentrated on providing auxiliary knowledge from the third-party standpoint without consideration for the value preferences of doctors and patients. The essences of these methods are complete and manual negotiation, and the problems of high cost, time consumption, delayed response, and decision fatigue are serious. METHODS: In response to the above limitations, this article proposes a fuzzy constraint-directed agent-based negotiation and recommendation framework for bilateral and multi-issue preference negotiation in SDM (PN-SDM). Its purpose is to provide preference information and intellectualize PN-SDM to promote SDM practice. We modeled PN-SDM problems as distributed fuzzy constraint satisfaction problems and designed the doctor agent and patient agent to negotiate on behalf of the doctor and patient. The negotiation result was then transformed into treatment plans by the recommendation model. The proposed negotiation and recommendation models were introduced in detail by an instance. RESULTS: The proposed method with different strategies and negotiation pairs achieves good performance in terms of negotiation running time, negotiation rounds, and combined aggregated satisfaction value. Specifically, it can feasibly and effectively complete multiple rounds of PN-SDM in a few seconds and obtain higher satisfaction. CONCLUSION: The experimental results indicate that the negotiation model can effectively simulate preference negotiation and relieve the pressure of increasing issues. The recommendation model can assist in decision-making and help to realize SDM. In addition, it can flexibly cope with various negotiation scenarios by using different negotiation strategies (e.g., collaborative, win-win, and competitive).

Investigating the effect of daily sleep on memory capacity in college students.

BACKGROUND: Sleep is a natural periodic state of rest for body and mind and daily sleep affects physical and mental health. However, it is essential to address intensity of sleep characteristics affecting the memory capacity of humans positively or negatively. OBJECTIVE: Using wearable devices to observe and assess the effect of daily sleep on memory capacity of college students. METHODS: This study assessed the daily sleep characteristics and memory capacity of 39 college students who used wrist-worn devices. The spatial span test (SST) was used to evaluate the memory capacity. RESULTS: The study indicated a negative correlation between memory capacity and awake count on the test date and during the week before the test date (r=-0.153 (95% CI: -0.032, -0.282), r=-0.391 (95% CI: -0.520, -0.235), respectively). However, the minutes asleep on the test date and during the week before the test date positively affected memory capacity (r= 0.127 (95% CI: 0.220, 0.025), r= 0.370 (95% CI: 0.208, 0.500), respectively). In addition, spending ⩾ 6 hours and 42 minutes asleep on the test date or ⩾ 6 hours and 37 minutes asleep per day on average during the week before the test date resulted in a better memory capacity. CONCLUSIONS: A lower awake count led to a higher memory capacity in college students, as did more minutes asleep.

Effect of socioeconomic inequalities on cholecystectomy outcomes: a 10-year population-based analysis.

BACKGROUND: Although numerous epidemiological studies on cholecystectomy have been conducted worldwide, only a few have considered the effect of socioeconomic inequalities on cholecystectomy outcomes. Specifically, few studies have focused on the low-income population (LIP). METHODS: A nationwide prospective study based on the Taiwan National Health Insurance dataset was conducted during 2003-2012. The International Classification of ICD-9-CM procedure codes 51.2 and 51.21-51.24 were identified as the inclusion criteria for cholecystectomy. Temporal trends were analyzed using a joinpoint regression, and the hierarchical linear modeling (HLM) method was used as an analytical strategy to evaluate the group-level and individual-level factors. Interactions between age, gender and SES were also tested in HLM model. RESULTS: Analyses were conducted on 225,558 patients. The incidence rates were 167.81 (95% CI: 159.78-175.83) per 100,000 individuals per year for the LIP and 123.24 (95% CI: 116.37-130.12) per 100,000 individuals per year for the general population (GP). After cholecystectomy, LIP patients showed higher rates of 30-day mortality, in-hospital complications, and readmission for complications, but a lower rate of routine discharge than GP patients. The hospital costs and length of stay for LIP patients were higher than those for GP patients. The multilevel analysis using HLM revealed that adverse socioeconomic status significantly negatively affects the outcomes of patients undergoing cholecystectomy. Additionally, male sex, advanced age, and high Charlson Comorbidity Index (CCI) scores were associated with higher rates of in-hospital complications and 30-day mortality. We also observed that the 30-day mortality rates for patients who underwent cholecystectomy in regional hospitals and district hospitals were significantly higher than those of patients receiving care in a medical center. CONCLUSION: Patients with a disadvantaged finance status appeared to be more vulnerable to cholecystectomy surgery. This result suggested that further interventions in the health care system are necessary to reduce this disparity.

The incidence and factors of hip fractures and subsequent morbidity in Taiwan: An 11-year population-based cohort study.

Hip fractures are a major problem to elder population, but subsequent morbidity is unclear about environmental factors and socioeconomic conditions. The study aims to investigate the incidence of hip fractures treated by the surgery; to compare the sequelae and temporal trends of hip fractures; to evaluate the seasonal effects in the subsequent short-term and long-term morbidities after hip fractures. A cohort study design is conducted using national health research datasets between 2000 and 2010. The ICD-9-CM diagnostic codes were utilized to investigate the incidence of hip fractures and the corresponding treatments. Hierarchical modeling was used to analyze the factors associated with various types of hip fractures. The results indicated that females had a lower incidence in the 30-44 age group, but a significantly higher incidence than males among those aged 60 years or older (adjusted rates 232.1 vs. 100.3 per 100,000 persons, p<0.001). The incidence of hip fractures in the low-income group showed no significant difference compared to that in the general population. There was a temporal trend of a 8.6% increase in the incidence of all types of hip fractures over the period of 2000-2010. A summer-winter variation is observed among the elderly. Hip fractures and subsequent morbidity are increasing in Taiwan's aging society. Older age, female gender, and time periods were independent risk factors for subsequent morbidities after surgical treatment. The result of this study is useful to the healthcare policy makers and to raise the public awareness of hip fractures.

Outcome comparison between percutaneous cholecystostomy and cholecystectomy: a 10-year population-based analysis.

BACKGROUND: Controversy surrounding the role of percutaneous cholecystostomy (PC) is fed by the absence of large amounts of data concerning its outcomes, and many authors have maintained that there is no evidence to support a recommendation for PC rather than cholecystectomy (CCS) in elderly or critically ill patients with acute cholecystitis (AC). METHODS: We conducted this study by tracking trends in the utilization and outcomes of PC and CCS using longitudinal health research data in Taiwan. RESULTS: Analyses were conducted on 236,742 patients, 11,184 of whom had undergone PC and 225,558 of whom had undergone CCS. Average annual percentage changes (AAPCs) from 2003 to 2012 increased significantly by 18.34% each year for PC and by 2.82% each year for CCS. The subset analyzes showed that the mortality rates were far higher in patients underwent PC than in patients underwent CCS in all subgroups, which increased from a minimum of 1.45-fold to a maximum of 34.22-fold. The gap of the mortality rates between PC group and CCS group narrowed as the patients aged and with the seriousness of the diseases increased. Most patients with PC or CCS who died in-hospital or within 30 days after discharge were 70 years of age or older, and a large number of them received a CCI score of at least 1. The AAPCs of the overall mortality rates from 2003 to 2012 decreased by 6.78% each year for PC and by 7.33% each year for CCS. PC was related to a higher rate of cholecystitis recurrence and readmission for complications, but a lower rate of in-hospital complications and routine discharge than CCS, and 36.41% of all patients treated with PC underwent subsequent CCS. Additionally, the patients with PC experienced longer hospital stays and generated higher costs than the patients with CCS. CONCLUSION: Patients who underwent PC demonstrated poorer prognoses than did patients who underwent CCS. The role of PC in the Tokyo guidelines may be overstated; it is not as safe as the Tokyo guidelines have suggested in moderate-grade cholecystitis cases, and it should be limited to only the elderly and sicker patients.

Outcomes in the Utilization of Single Percutaneous Cholecystostomy in a Low-Income Population.

Numerous studies have investigated the applicable populations for percutaneous cholecystostomy (PC) procedures, but the outcomes of PC in low-income populations (LIPs) have been insufficiently studied. Data for 11,184 patients who underwent PC were collected from the National Health Insurance Research Database of Taiwan during 2003 and 2012. The overall crude rate of single PC for the LIP was 64% higher than that for the general population (GP). After propensity score matching for the LIP and GP at a ratio of 1:5, the outcome analysis of patients who underwent PC showed that in-hospital mortality was significantly higher in the LIP group than in the GP group, but one-year recurrence was lower. The rates of 30-day mortality and in-hospital complications were higher for the LIP patients than for the GP patients, and the rate of routine discharge was lower, but the differences were not significant. In conclusion, LIP patients undergoing PC exhibit poor prognoses relative to GP patients, indicating that a low socioeconomic status has an adverse impact on the outcome of PC. We suggest that surgeons fully consider the patient's financial situation during the operation and further consider the possible poor post-surgical outcomes for LIP patients.

Trends and outcomes in the utilization of laparoscopic appendectomies in a low-income population in Taiwan from 2003 to 2011.

BACKGROUND: Numerous epidemiological studies have compared outcomes between laparoscopic appendectomies (LA) and open appendectomies (OA); however, few studies have assessed the efficacy of LA specifically in a low-income population (LIP). METHODS: We analyzed the trends in the utilization and outcomes of LA versus OA in an LIP in Taiwan using data from the National Health Insurance (NHI) Research Database. RESULTS: Steady temporal growth trends were observed for the patients who underwent LA in both the LIP and general population (GP); however, in each study year, the proportion of LIP patients who underwent LA was lower than the proportion of GP patients who underwent the procedure. The LIP patients were more susceptible to payment policies than the GP patients; thus, more attention should be paid to vulnerable patient populations when formulating and revising NHI payment policies. Compared with OAs, LAs were associated with a slightly higher rate of routine patient discharges and a lower rate of in-hospital complications (1.48% vs. 3.76%, p < 0.05). The rate of readmission for complications was lower in patients after LA than in patients after OA (1.64% vs. 3.89%, p < 0.05). The overall case-fatality rate of LIP patients who underwent LA was lower than that of those who underwent OA. LA was correlated with a significantly shorter length of hospital stay (LOS) compared with OA (3.80 ± 0.08 vs. 5.51 ± 0.11, p < 0.05). The average hospital cost for LA was slightly less than that for OA (1178 ± 13 vs. 1191 ± 19 USD, p < 0.05). A higher percentage of patients who underwent OA required an LOS longer than 14 days compared to patients who underwent LA (7.73% vs. 1.97%, p < 0.05). Regarding hospital costs and LOS, LA showed significant advantages over OA in the subpopulations of male patients, patients 45 years old and older, patients with Charlson Comorbidity Index (CCI) scores of two or more, and patients with complicated cases of appendicitis. CONCLUSION: The LIP patients benefited more from the LA approach than the OA approach in the treatment of appendicitis, especially regarding LOS, in-hospital complications, in-hospital mortality, and routine discharge rates.

Epidemiology and socioeconomic features of appendicitis in Taiwan: a 12-year population-based study.

INTRODUCTION: This paper presents an epidemiologic study of appendicitis in Taiwan over a twelve-year period. An analysis of the incidence in the low-income population (LIP) is included to explore the effects of lower socioeconomic status on appendicitis. METHODS: We analyzed the epidemiological features of appendicitis in Taiwan using data from the National Health Insurance Research Database (NHIRD) from 2000 to 2011. All cases diagnosed as appendicitis were enrolled. RESULTS: The overall incidences of appendicitis, primary appendectomy, and perforated appendicitis were 107.76, 101.58, and 27.20 per 100,000 per year, respectively. The highest incidence of appendicitis was found in persons aged 15 to 29 years; males had higher rates of appendicitis than females at all ages except for 70 years and older. Appendicitis rates were 11.76 % higher in the summer than in the winter months. A multilevel analysis with hierarchical linear modeling (HLM) revealed that male patients, younger patients (aged ≤14 years), and elderly patients (aged ≥60 years) had a higher risk of perforated appendicitis; among adults, the incidence increased with age. Moreover, the risk of perforation was higher in patients with one or more comorbidities. LIP patients comprised 1.25 % of the total number of patients with appendicitis from 2000 to 2011. The overall incidence of appendicitis was 34.99 % higher in the LIP than in the normal population (NP), and the incidence of perforated appendicitis was 40.40 % higher in the LIP than in the NP. After multivariate adjustment, the adjusted hospital costs and length of hospital stay (LOS) for the LIP patients were higher than those for the NP patients. CONCLUSIONS: Appendicitis and appendectomy in Taiwan had similar overall incidences, seasonality patterns, and declining trends compared to numerous previous studies. Compared to NP patients, LIP patients had a higher risk of appendicitis, longer LOS and higher hospital costs as a result of appendectomy.

Epidemiology of appendicitis and appendectomy for the low-income population in Taiwan, 2003-2011.

BACKGROUND: Although numerous epidemiological studies on appendicitis have been conducted worldwide, only a few studies have paid attention to the effect of socioeconomic status on appendicitis, particularly studies focusing on the low-income population (LIP). METHODS: We analyzed the epidemiological features of appendicitis in Taiwan using data from the National Health Insurance Research Database from 2003 to 2011. All cases diagnosed as appendicitis were enrolled. RESULTS: Between 2003 and 2011, 2,916 patients from the LIP and 209,206 patients from the normal population (NP) were diagnosed with appendicitis. Our finding revealed that the ratios of comorbidities, complicated appendicitis, and readmissions in LIP patients were slightly higher than those of NP patients. LIP patients were more likely to live in suburban and rural areas, and hence a higher proportion of them were hospitalized in a district or regional hospital compared with NP patients. The crucially finding was that the overall incidence ratios of appendicitis, acute appendicitis, and perforated appendicitis in the LIP were substantially higher than those in the NP (36.25%, 35.33%, and 37.28%, respectively). The mean LOS in LIP patients was longer than that of NP patients. The overall case-fatality ratio of appendectomy in the LIP was higher when compared with the NP (0.41% versus 0.12%, p < 0.05). We also observed that appendicitis was occurred frequently in male patients, with a higher incidence for those aged 15-29 years in both the LIP and NP. The incidences of incidental appendectomy showed a decreasing trend in both the LIP and NP. Finally, a valuable discovery was that the total hospital cost was comparable between the laparoscopic appendectomy (LA) and open appendectomy (OA) (1,178 ± 13 USD versus 1,191 ± 19 USD, p < 0.05) in LIP patients because they saved more hospitalization costs than NP patients when the previous one chose the LA. CONCLUSION: This study confirmed that a lower socioeconomic status has significantly negative impact on the occurrence and treatment of appendicitis and appendectomy. In terms of hospital costs and LOS, LIP patients benefit more from the LA approach than they do from the OA approach in the treatment of appendicitis.

Epidemiology of hospitalized traumatic pelvic fractures and their combined injuries in Taiwan: 2000-2011 National Health Insurance data surveillance.

BACKGROUND: From the viewpoint of prehospital emergency medicine, a greater proportion of pelvic fractures not of a life-threatening status but combined with other injuries need more comprehensive recognition. METHODS: A 12-year nationwide health database of inpatients was reviewed. All cases diagnosed as pelvic fractures were enrolled. The associated injuries classified into 20 categories were further analyzed. RESULTS: During 2000-2011, the hospitalized incidence of pelvic fractures in Taiwan ranged from 17.17 to 19.42 per 100,000, and an increasing trend with age was observed. The mean case-fatality rate was 1.6% for females and 2.1% for males; male patients with pelvic fractures had a significantly higher risk of death than female patients after adjusting for other covariates. 74.2% of these cases were combined with other injuries. The most common associated injuries in an identified body region were other orthopedic fractures of the lower limbs (21.50%), spine/trunk (20.97%), or upper limbs (18.18%), followed by significant head injuries (17.59%), intra-abdominal injuries (11.00%), and thoracic injuries (7.20%). CONCLUSION: The incidence of hospitalized pelvic fractures in Taiwan was low and the case-fatality rate was lower than those of other countries. Concurrently, coexistence of major combined injuries with pelvic fractures was easily treated at medical centers.