Buscar recursos académicos

Graph-based text classification has become an effective paradigm for modeling corpus-level structure, particularly under limited supervision. However, most existing approaches rely on document–word representations...

IntroductionThe complex interplay between environmental dynamics, biodiversity loss, and public health necessitates advanced methodologies for quantifying and interpreting their interactions. Respiratory health, highly s...

Abstract Quality defects in substandard medicines represent a threat to public health. Rapid and accurate identification of these defects is critical to prioritise the cases and implement regulatory measures. However, th...

Abstract Precise extraction of medical phenotypes and entities from electronic health record (EHR) text is vital for numerous clinical research tasks, including cohort classification, tracking temporal patterns in diseas...

This study aims to identify the best predictive model for analysing online product reviews (OPRs) in the electronics industry, with a secondary focus on leveraging unstructured customer feedback to support product improv...

Abstract Understanding human emotions across multiple modalities such as text and images, is increasingly important for applications including content personalization, social media analysis, and Human–Computer Interact...

IntroductionWeather classification plays a crucial role in applications such as environmental monitoring, disaster management, and smart city infrastructure. Accurate and efficient classification of weather conditions fr...

Abstract Classifying exam questions using Bloom’s Taxonomy is a critical task in education. However, performing this classification manually is often inefficient, prone to subjective errors and demands significant time...

The effect of imbalanced data on the optical character recognition of Braille text is investigated by applying two techniques to a set of convolutional neural network image classification models. A multilabel classificat...

With the rapid advancement of online education, students’ sentiment feedback serves as a pivotal factor in enhancing course quality and refining pedagogical strategies. However, conventional sentiment analysis approach...

This paper introduces CONV_GBERT, a hybrid deep learning framework for robust sentiment classification. The model integrates the bidirectional contextual understanding of BERT, the generative capabilities of GPT, and the...

This paper presents allocate connections between texts (ACT), a novel three-stage algorithm for the automatic detection of biblical quotations in Rabbinic literature. Unlike existing text reuse frameworks that struggle w...

Benign–malignant classification of pulmonary nodules from chest computed tomography (CT) is essential for early lung cancer screening and for reducing unnecessary biopsies and follow-up examinations, yet it remains cha...

The classification of Chinese phrase structures has traditionally been based on formal configuration, especially categories such as subject-predicate, verb-object, and modifier-head constructions. Although this approach ...

Abstract Purpose Structured reporting (SR) offers standardized radiological documentation, enhancing clarity and reproducibility. However, its role in contrast-enhanced ultrasound (CEUS) for testicular tumors remains und...

Abstract Remote sensing is increasingly employed today for the creation of wall-to-wall vegetation maps of protected areas. The main objective of this study was to evaluate whether it is feasible to develop a remote sens...

This study addresses the need to detect the severity of acne in skin care and beauty, particularly in managing the diagnosis of acne severity more efficiently and objectively. Acne, a common skin problem, can significant...

Triple-negative breast cancer (TNBC) is a subtype of breast cancer with strong invasiveness, limited treatment options, and poor prognosis. Its early accurate diagnosis and individualized treatment are major challenges f...

Options trading is a type of financial trading that can offer significant profit opportunities depending on market conditions, but its profit and loss structure is complex. Traditional trading decisions are often made ba...

Purpose: Dental caries is one of the most prevalent oral diseases worldwide, and predicting Early Enamel Caries (EEC) and Advanced Enamel Caries (AEC) in intraoral imaging is a significant clinical research challenge. To...

Importance Emergency departments (EDs) face significant documentation burdens due to reliance on unstructured clinical narratives, hindering efficiency, particularly in pediatric care. Large language models (LLMs) offer ...

This research aims to implement web scraping techniques to collect testimonial data from the CeriaMultimedia website and perform sentiment analysis to evaluate service quality. The collected data consists of a limited nu...

Early detection of Parkinson’s disease (PD) through speech analysis offers significant clinical advantages, yet no validated tools exist for Arabic-speaking populations, representing a critical gap in global healthcare...

Unmanned Aerial Vehicles (UAVs) have become a prevalent tool for aerial image analysis, thanks to their agility in low-altitude flight and real-time sensing. However, objects in UAV imagery typically occupy minimal pixel...