Communication is essential for success in today's world, making English language learning (ELL) a crucial skill. Innovative solutions are required to tackle complex language learning issues and meet the various demands of learners. Personalized learn...
Breast cancer ranks among the most prevalent cancers in women globally, with its treatment efficacy heavily reliant on the early identification and diagnosis of the disease. The importance of early detection and diagnosis cannot be overstated in enha...
Scene categorization is the dominant proxy for visual understanding, yet humans can perform a large number of visual tasks within any scene. Consequently, we know little about how different tasks change how a scene is processed, represented, and its ...
There are an estimated 1.3 million cases of cancer globally each year, making it one of the most serious types of urinary tract cancer. The methods used today for diagnosing and monitoring bladder cancer are intrusive, costly, and time-consuming. In ...
Brain-computer interface (BCI) systems allow users to communicate with external devices by translating neural signals into real-time commands. Convolutional neural networks (CNNs) have been effectively utilized for decoding motor imagery electroencep...
As social media platforms evolve, hate speech increasingly manifests across multiple modalities, including text, images, audio, and video, challenging traditional detection systems focused on single modalities. Hence, this research proposes a novel M...
Blending poly (lactic acid) (PLA) with poly (vinyl alcohol) (PVA) improves the strength and hydrophilicity of nanofibers, making them suitable for biomedical applications like wound dressings. This study explores how electrospinning parameters-applie...
Clear cell renal cell carcinoma (ccRCC) is the most prevalent type of renal cell carcinoma. However, our understanding of ccRCC risk genes remains limited. This gap in knowledge poses challenges to the effective diagnosis and treatment of ccRCC. To a...
AIM: The adoption of artificial intelligence (AI) tools is gaining traction in maternal mental health (MMH) research. Despite its growing usage, little is known about its prospects and challenges in low- and middle-income countries (LMICs). This stud...
PURPOSE: To develop an artificial intelligence (AI) system for detecting pathological patterns of diabetic macular oedema (DME) with fine-grained image categorisation using optical coherence tomography (OCT) images.
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