BACKGROUND: Identifying neuroinfectious disease (NID) cases using International Classification of Diseases billing codes is often imprecise, while manual chart reviews are labor-intensive. Machine learning models can leverage unstructured electronic ...
BACKGROUND: Bleeding adverse drug events (ADEs), particularly among older inpatients receiving antithrombotic therapy, represent a major safety concern in hospitals. These events are often underdetected by conventional rule-based systems relying on s...
PURPOSE: Hirschsprung's disease (HSCR) is an intestinal disorder characterized by the absence of nerve cells in parts of the intestinal tract. The definitive diagnosis is confirmed by a full-thickness rectal biopsy to verify the absence of ganglion c...
Prediction-powered inference (PPI) (Angelopoulos et al., Science 382(6671):669-674, 2023) and its subsequent development called PPI++ (Angelopoulos et al., 2023) provide a novel approach to standard statistical estimation, leveraging machine learning...
Agriculture 5.0 is a principal economic activity in the world with major workforce dependent crops cultivation. An automated system for crops field insect pest identification can help decrease labour, while also improving the speed and precision in c...
Manual diagnosis of hematological cancers like leukemia through bone marrow smear analysis is labor-intensive, prone to errors, and highly dependent on expert knowledge. To overcome these limitations, this study introduces a comprehensive deep learni...
The analysis of Arabic Twitter data sets is a highly active research topic, particularly since the outbreak of COVID-19 and subsequent attempts to understand public sentiment related to the pandemic. This activity is partially driven by the high numb...
The rapid evolution of intelligent manufacturing systems necessitates the integration of advanced robotics to meet increasing demands for productivity, precision, and adaptability. Robots play an indispensable role across a spectrum of operations, fr...
This paper presents a novel hybrid combined neural network and fuzzy logic adaptive proportional, integral, and derivative(NNPID+FPID) control strategy that integrates neural networks and fuzzy logic for optimizing Unmanned Aerial Vehicle(UAV) dynami...
In response to the low accuracy and recall of current English translation text error recognition methods, this paper proposes a research on English translation text error recognition based on an improved decision tree algorithm. Firstly, use mutual i...
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