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An approach to the construction of classifiers from imbalanced datasets is described. A dataset is imbalanced if the classification categories are not approximately equally represented. Often real-world data sets are pre...

Nutritional status of toddlers was considered a key indicator for assessing nutritional problems among children. According to the Banyuwangi Regency Health Profile, the prevalence of undernutrition based on the weight-fo...

One such serious problem in machine learning (ML) is imbalanced datasets. Minority class samples are usually sparse but hold significant meaning. The model can become biased toward the majority class due to unbalanced cl...

Disease classification based on drug prescription data plays a crucial role in helping healthcare professionals understand patient health conditions and supporting clinical decision-making. Drug prescription data actuall...

Imbalanced data is an important issues and challenges faced in data classification. This will lead to poor performance of binary classifiers, this is due to bias in classification in favour of the majority class and lack...

Reliable beat-level arrhythmia detection from electrocardiogram (ECG) signals is essential for continuous patient monitoring. However, many existing deep learning models remain computationally expensive and are sensitive...

E-commerce companies face fierce competition. For e-commerce companies to succeed, they must keep and attract customers by offering them the best affordable services. Taking appropriate and timely actions to keep custome...

Abstract Early and reliable smoke detection is critical for preventing fire-related disasters, safeguarding human lives, and ensuring infrastructure safety. Conventional sensor-based systems, however, are often constrain...

Direktorat Jenderal Bea & Cukai (DJBC) merupakan lembaga instansi pemerintah yang bertugas mengawal dan melayani kegiatan ekspor dan import di Indonesia sejak berdiri pada tahun 1946 yang diharapkan oleh masyarakat sebag...

Traditional malware detection techniques frequently fail to detect and stop malicious activity in an era where cyber threats are becoming more complex. Any software that enters a computer system without the administrator...

Class imbalance remains a critical challenge in medical data classification, particularly in diabetes prediction, as it significantly degrades minority-class sensitivity. This study proposes an Adaptive Feature-Aware Hyb...

The swift expansion of the digital gaming sector, especially online games like Free Fire, has produced extensive user feedback via platforms like the Google Play Store. This research utilizes the K-Nearest Neighbor (KNN)...

Lifeng Yao, Yijun Chen, Jing Shen, Junge Zhang, Yiwei Zhang, Guojin Liang, Yiqin Ji Department of Anesthesiology, The First Affiliated Hospital of Ningbo University, Ningbo, Zhejiang, People’s Republic of ChinaCorrespo...

In recent years, the frequency and complexity of financial fraud have been rising and have become an urgent challenge for the global financial system. Traditional rule-based detection methods struggle to cope with new ty...

BackgroundTo develop and externally validate a coronary heart disease (CHD) risk model from routine clinical indicators and identify key predictors.MethodsThe Framingham Heart Study cohort (n = 4,240) was used. Missi...

Fast and accurate identification of skin lesions is important for the outcome of patients. The evaluation of lesions is subjective, and poor quality images may limit accuracy. Deep learning models can be an alternative; ...

Imbalance of data between classes can result in incorrect predictions in classification, which can cause problems in decision making. Eastern Indonesia (KTI) is one of the regions that has a Human Development Index (HDI)...

Financial institutions constantly face at the risk of default by borrowers which can result in significant financial losses. It is essential to develop an appropriate predictive model for loan default to reduce these ris...

Abstract Accurate classification of phonocardiogram (PCG) signals is vital for the early detection of cardiovascular diseases (CVDs), a leading cause of global mortality. However, conventional machine learning and deep l...

ObjectiveCongenital Hypogonadotropic Hypogonadism (CHH) is a rare disease with an extremely low incidence, and the outcomes of fertility induction therapy in CHH patients exhibit significant interindividual heterogeneity...

At an early phase, chronic kidney disease (CKD) is usually not obvious. An appreciable reduction in kidney function is the primary sign of the disease. If CKD can be identified early, the rate at which CKD is advancing c...

Abstract Background Understanding how the respiratory microbiota matures with age is key to improving poultry health and pathogen surveillance, yet the ecological processes shaping this transition remain elusive. We aime...

Abstract Upper-limb prosthesis users usually lack comprehensive feedback or touch. This significantly hinders their ability to interact with their environment and lead normal lives. This research involves the development...

"Esta tesis presenta un estudio multifactorial sobre el problema de la detección de fraude financiero mediante modelos de aprendizaje automático. Se evaluaron tres algoritmos ampliamente utilizados —Regresión Logís...