BACKGROUND: Acute kidney injury (AKI) is a critical complication in intensive care units (ICUs) that is known to have multifaceted impacts. However, as AKI is often detected too late, early prediction is crucial for timely intervention.
Carboxylesterases (CES) are pivotal enzymes in the hydrolysis of carboxylic esters, playing fundamental roles in both biological systems and biotechnological applications. This study investigates CES from the Amycolatopsis genus, characterized by its...
When a deep learning model is trained sequentially on different datasets, it often forgets the knowledge learned from previous data, a problem known as catastrophic forgetting. This damages the model's performance on diverse datasets, which is critic...
Microsurgical suturing demands a high level of precision, skill, and extensive training to ensure success in delicate procedures. In this study, we created a deep-learning approach for automating phase recognition and skill assessment in microsurgica...
Malaria remains a critical health challenge in developing countries, particularly in Africa, where it disproportionately affects vulnerable populations. Accurate malaria severity prediction is important for proper treatment and improved patient survi...
Brain tumours continue to be a primary cause of worldwide death, highlighting the critical need for effective and accurate diagnostic tools. This article presents MK-YOLOv8, an innovative lightweight deep learning framework developed for the real-tim...
BACKGROUND: Identifying surgical phases is a crucial component of surgical workflow analysis, facilitating the automated evaluation of surgical procedures' performance and efficiency. A significant challenge in developing neural networks for surgical...
BACKGROUND: Oral cavity carcinoma remains a major public health concern, where early and accurate detection is vital for improving patient outcomes and survival rates. Current diagnostic systems often face challenges such as limited feature selection...
Deep complex-valued neural networks (CVNNs) provide a powerful way to leverage complex number operations and representations and have succeeded in several phase-based applications. However, previous networks have not fully explored the impact of comp...