Publications by authors named "Mohd Hashim Siti Zaiton"

Article Synopsis
  • Acute myeloid leukemia (AML) is a severe type of cancer affecting white blood cells, necessitating prompt diagnosis for effective treatment.
  • The study introduces "CAE-ResVGG FusionNet," a computer-aided diagnostic system that uses advanced image processing techniques to accurately identify and classify immature white blood cells into four subtypes.
  • The framework includes stages for data preprocessing, feature extraction, classification using ensemble methods, and performance validation to ensure high accuracy and reliability in diagnosing AML.
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Recent advancements in artificial intelligence (AI) have led to numerous medical discoveries. The field of computer vision (CV) for medical diagnosis has received particular attention. Using images of peripheral blood (PB) smears, CV has been utilized in hematology to detect acute leukemia (AL).

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Mathematical modelling is fundamental to understand the dynamic behavior and regulation of the biochemical metabolisms and pathways that are found in biological systems. Pathways are used to describe complex processes that involve many parameters. It is important to have an accurate and complete set of parameters that describe the characteristics of a given model.

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Network lifetime and energy efficiency are crucial performance metrics used to evaluate wireless sensor networks (WSNs). Decreasing and balancing the energy consumption of nodes can be employed to increase network lifetime. In cluster-based WSNs, one objective of applying clustering is to decrease the energy consumption of the network.

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