Traffic accident-related injuries and fatalities are a serious global public health and social development challenge. The accurate prediction of crash severity improves road safety and reduces casualties, as well as serving road managers and policy m...
Background: Acute pancreatitis is a common condition with a variable prognosis. While the overall mortality rate of acute pancreatitis is relatively low, ranging between 3 and 5% in most cases, severe forms can result in significantly higher morbidit...
Background: Early detection of severe dengue (SD) is crucial in preventing life-threatening complications. Despite its importance, comprehensive knowledge about these early indicators is still limited. This study aimed to identify predictors of SD in...
In this paper, a deep learning model using a Recurrent Neural Network (RNN) was developed and employed to predict the injury severity of traffic accidents based on 1130 accident records that have occurred on the North-South Expressway (NSE), Malaysia...
3 March 2022
Clinicians urgently need reliable and stable tools to predict the severity of COVID-19 infection for hospitalized patients to enhance the utilization of hospital resources and supplies. Published COVID-19 related guidelines are frequently being updat...
Traffic accidents on highway are often characterized by high destructiveness and severe casualties. Predicting accident severity and understanding its causes are crucial for enhancing highway safety. To address the issues of limited prediction accura...
Traffic accidents are inevitable events that occur unexpectedly and unintentionally. Therefore, analyzing traffic data is essential to prevent fatal accidents. Traffic data analysis provided insights into significant factors and driver behavioral pat...
Precisely assessing the severity of persons with COVID-19 at an early stage is an effective way to increase the survival rate of patients. Based on the initial screening, to identify and triage the people at highest risk of complications that can res...
Road traffic crashes (RTCs) have emerged as a major global cause of fatalities, with the number of accident-related deaths rising rapidly each day. To mitigate this issue, it is essential to develop early prediction methods that help drivers and ride...
Traffic accident avoidance and mitigation are the main targets of accident research and vehicle safety development worldwide. Despite improving advanced driver assistance systems (ADAS) and active safety systems, it will not be possible to avoid all...
Traffic accidents occur frequently, causing significant losses to people’s lives and property safety. Accurately predicting the severity level of traffic accidents is of great significance. Based on traffic accident data, this study comprehensi...
The severity of software bug reports plays an important role in maintaining software quality. Many approaches have been proposed to predict the severity of bug reports using textual information. In this research, we propose a deep learning framework...
Monitoring the condition of rotating machinery is critical in aerospace applications like aircraft engines and helicopter rotors. Faults in these components can lead to catastrophic outcomes, making early detection essential. This paper proposes a no...
This article presents a novel statistical approach for analyzing occupational accident data from the ESAW database, aiming to improve the evaluation and prediction of accident severity among specific groups of employees. The proposed method combines...
With the increasing acceptance of green, low-carbon, and sustainable development principles, the rising number of new energy vehicles (NEVs) has raised public concern over traffic safety risks associated with these vehicles. To assist traffic managem...
Background: Machine learning (ML) has emerged as a powerful approach for predicting outcomes based on patterns and inferences. Improving prediction of severe coronary artery disease (CAD) has the potential for personalizing prevention and treatment s...
Automatic severity assessment and progression prediction can facilitate admission, triage, and referral of COVID-19 patients. This study aims to explore the potential use of lung lesion features in the management of COVID-19, based on the assumption...
(1) Background: HELLP (hemolysis, elevated liver enzymes, and low platelets) syndrome is a rare and life-threatening complication of preeclampsia. The aim of this study was to evaluate and compare the predictive performances of four machine learning-...
The premise for this study emanated from the need to understand SARS-CoV-2 infections at the molecular level and to develop predictive tools for managing COVID-19 severity. With the varied clinical outcomes observed among infected individuals, creati...
Wildfires are one of the natural hazards that the European Union is actively monitoring through the Copernicus EMS Earth observation program which continuously releases public information related to such catastrophic events. Such occurrences are the...
Road traffic accident severity prediction is crucial for implementing effective safety measures and proactive traffic management strategies. Existing methods often treat this as a nominal classification problem and use traditional feature selection t...
Kingdom of Among the G20 countries, Saudi Arabia (KSA) is facing alarming traffic safety issues compared to other G-20 countries. Mitigating the burden of traffic accidents has been identified as a primary focus as part of vision 20230 goals. Driver...
Predicting the severity of traffic accidents remains challenging due to the limited ability of existing methods to extract deep semantic information from unstructured accident narratives, as traditional approaches typically depend on structured data...
Background/Objectives: Rapid and accurate assessment of lung diseases, like pneumonia, is critical for effective clinical decision-making, particularly during pandemics when disease progression can be severe. Early diagnosis plays a crucial role in p...
Motor vehicle crashes remain a leading cause of life and property loss to society. Autonomous vehicles can mitigate the losses by making appropriate emergency decision, and the crash injury severity prediction model is the basis for autonomous vehicl...
Traffic accidents are of worldwide concern, as they are one of the leading causes of death globally. One policy designed to cope with them is the design and deployment of road safety systems. These aim to predict crashes based on historical records,...
This study presents a hybrid ensemble learning framework for the joint detection and motor severity prediction of Parkinson’s disease (PD) using biomedical voice features. The proposed architecture integrates a deep multimodal fusion model with...
Despite the agricultural sector’s consistently high injury rates, formal reporting is often limited, leading to sparse national datasets that hinder effective safety interventions. To address this, our study introduces a comprehensive framework...
The latest developments in Advanced Driver Assistance Systems (ADAS) have greatly enhanced the comfort and safety of drivers. These technologies can identify driver abnormalities like fatigue, inattention, and impairment, which are essential for aver...
Acute pancreatitis has a diverse etiology and natural history, and some patients have severe complications with a high risk of mortality. The prediction of the severity of acute pancreatitis should be achieved by a careful ongoing clinical assessment...
Background: The optimal management of patients with acute pancreatitis is directly related to the early detection of the mild, moderate, or severe forms of the disease, which remains a continuous challenge despite the availability of various severity...
Over the past decade, increased awareness about leptospirosis disease in developing and industrialized countries has resulted in increased numbers of leptospirosis cases being reported worldwide. About 5% to 15% of leptospirosis patients end up with...
Objectives: Assess the predictive accuracy of the WHO COVID-19 severity classification on COVID-19 hospitalized patients. The secondary aim was to compare its predictive power with a new prediction model, named COVID-19 EPI-SCORE, based on a Bayesian...
15 September 2018
Objectives: To study Malaysian dengue clinical practice guideline (CPG) warning signs (WS) in predicting severe dengue (SD) and its associated factors among confirmed cases presented to a teaching hospital in north-eastern Malaysia in 2014. Methods:...
Background/Objectives: Severe dengue infection remains a major public health burden in Thailand, where timely identification of high-risk patients is essential for effective clinical management. Existing predictive models are often complex and less f...
Severe convective weather is hugely destructive, causing significant loss of life and social and economic infrastructure. Based on the U-Net network with the attention mechanism, the recurrent convolution, and the residual module, a new model is prop...
Background: Severe obesity is a global public health threat of growing proportions. Accurate models to predict severe postoperative complications could be of value in the preoperative assessment of potential candidates for bariatric surgery. So far,...
Background: New tools for the assessment and prediction of the severity of hospitalized COVID-19 patients can help direct limited resources to patients with the greatest need. Circulating levels of calprotectin (S100A8/S100A9) reflect inflammatory ac...
Traffic accidents are among the most common causes of death worldwide. According to statistics from the World Health Organization (WHO), 50 million people are involved in traffic accidents every year. Canada, particularly Montreal, is not immune to t...
Large-truck crashes often result in substantial economic and social costs. Accurate prediction of the severity level of a reported truck crash can help rescue teams and emergency medical services take the right actions and provide proper medical care...
(1) Background: Heparin-Binding Epidermal Growth Factor-like Growth Factor (HB-EGF) is involved in wound healing, cardiac hypertrophy, and heart development processes. Recently, circulant HB-EGF was reported upregulated in severely hospitalized COVID...
Predicting the mortality risk of patients with Coronavirus Disease 2019 (COVID-19) can be valuable in allocating limited medical resources in the setting of outbreaks. This study assessed the role of a chest X-ray (CXR) scoring system in a multivaria...
The development of multiple organ failure and septic complications increases the cumulative risk of mortality in children with severe injury. Clinically available biochemical markers have shown promise in assessing the severity and predicting the dev...
Background/Objectives: Primary obstructive megaureter (POM) is a rare congenital urological condition usually diagnosed prenatally or in early childhood. Conservative management is increasingly preferred due to a high potential for spontaneous resolu...
To date, there is no clinically useful prediction model that is suitable for Japanese pediatric trauma patients. Herein, this study aimed to developed a model for predicting the survival of Japanese pediatric patients with blunt trauma and compare it...
The prediction of traffic accident severity is essential for traffic safety management and control. To achieve high prediction accuracy and model interpretability, we propose a hybrid model that integrates random forest (RF) and Bayesian optimization...
The prediction of disease outcomes in COVID-19 patients in the ICU is of critical importance, and the examination of host gene expressions is a promising tool. The 29-host mRNA Inflam-matix-Severity-3b (IMX-SEV-3b) classifier has been reported to pre...
Severe weather conditions not only damage electric power infrastructure, and energy systems, but also affect millions of users, including residential, commercial or industrial consumers. Moreover, power outages due to weather-related natural disaster...
To date, there is no severe acute respiratory syndrome coronavirus 2-(SARS-CoV-2)-specific prognostic biomarker available. We assessed whether SARS-CoV-2 cycle threshold (Ct) value at diagnosis could predict novel CoronaVirus Disease 2019 (COVID-19)...
Background: Severe hypoglycemia (SH) is a critical complication in children and adolescents with type 1 diabetes (T1D), associated with cognitive impairment, coma, and significant psychosocial burden. Despite advances in glucose monitoring, predictin...
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