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Dynamic Positron Emission Tomography (dPET) imaging and Time-Activity Curve (TAC) analyses are essential for understanding and quantifying the biodistribution of radiopharmaceuticals over time and space. Traditional compartmental modeling, while ...

Ports are primarily used for maritime activities such as cruising, maneuvering, and hoteling, which facilitate imports and exports. These activities are crucial for economic growth and development. However, when port activities are scaled up, they ...

In the context of in vitro fertilization (IVF), selecting embryos for transfer is critical in determining pregnancy outcomes, with implantation as the essential first milestone for a successful pregnancy. This study introduces the Bonna algorithm, ...

This study presents a comparative assessment of various machine learning models for predicting mortality in heart failure patients. Through a rigorous analytical approach, we have scrutinized models ranging from logistic regression and support ...

The growing demand for fitness facilities and activities has led to significant overcrowding in gyms, which has become a major concern. To solve this problem, there is an urgent need to develop an interpretable predictive model for this growing customer ...

Soil microbial fuel cells (SMFCs) are an emerging technology which offer clean and renewable energy in environments where more traditional power sources, such as chemical batteries or solar, are not suitable. With further development, SMFCs show great ...

The study aims to introduce a novel machine learning approach for the prediction of product lengths by addressing diverse data types including numeric, textual and categorical data and extracting valuable information from the dataset to enhance ...

This study examined the validity of early math skills as predictors of literacy skills. Data was collected from students using a home-based kindergarten readiness program. Performance on math domain metrics within a kindergarten readiness program ...

Accurate prediction of future traffic flow trends is essential to solve urban transportation problems. However, traffic flow prediction faces great challenges due to the multimodal nature of pedestrian behavior and the complexity of the traffic ...

Predicting customer behavior is crucial for businesses, including churn and purchasing behavior. We propose a tailored model for this purpose, applied to two types of problems: customer churn and purchasing behavior prediction. Our study incorporates ...

Child dehydration is a significant health concern, especially among children under 5 years of age, as they are more susceptible to conditions such as diarrhea and vomiting. In Afghanistan, the impact of severe diarrhea on child mortality is exacerbated ...

Order fulfilment is a key goal for retailers. It is impacted by item unavailability, poor item quality and delivery mishaps. Although the north star is to resolve these challenges completely, in practice, retailers would benefit by prioritizing perfect ...

Mental health and well-being are critical components of overall health: suffering from a mental illness can be both debilitating and life-threatening for individuals experiencing symptoms. Detecting symptoms of mental illness early-on and delivering ...

Prediction of the autogenous shrinkage referred to as the reduction of apparent volume of concrete under seal and isothermal conditions is of great significance in the service life analysis and design of durable concrete structures, especially with the ...

Cardiovascular Diseases (CVDs), or heart diseases, are one of the top-ranking causes of death worldwide. About 1 in every 4 deaths are related to heart diseases, which are broadly classified as various types of abnormal heart conditions. However, ...

Mental health issues affect a significant portion of the world’s population and can result in debilitating and life-threatening outcomes. To address this increasingly pressing healthcare challenge, there is a need to research novel approaches for early ...

The customer churn prediction (CCP) is one of the challenging problems in the telecom industry. With the advancement in the field of machine learning and artificial intelligence, the possibilities to predict customer churn has increased ...

Mental health issues affect a significant portion of the world’s population and can result in debilitating and life-threatening outcomes. To address this increasingly pressing healthcare challenge, there is a need to research novel approaches for early ...

The COVID-19 pandemic has infected millions of people around the world, spreading rapidly and causing a flood of patients that risk overwhelming clinical facilities. Whether in urban or rural areas, hospitals have limited resources and personnel to treat ...

Various data-driven models are often involved in epidemiological studies, wherein the availability of data is constantly increasing. Accurate and, at the same time, interpretable models are preferable from the practical point of view. Finding simple and ...