ALL-Net: integrating CNN and explainable-AI for enhanced diagnosis and interpretation of acute lymphoblastic leukemia.

This article presents a new model, ALL-Net, for the detection of acute lymphoblastic leukemia (ALL) using a custom convolutional neural network (CNN) architecture and explainable Artificial Intelligence (XAI). A dataset consisting of 3,256 peripheral blood smear (PBS) images belonging to four classes-benign (hematogones), and the other three Early B, Pre-B, and Pro-B, which are subtypes of ALL, are utilized for training and evaluation. The ALL-Net CNN is initially designed and trained on the PBS image dataset, achieving an impressive test accuracy of 97.

iBlock: An Intelligent Decentralised Blockchain-based Pandemic Detection and Assisting System.

The recent COVID-19 outbreak highlighted the requirement for a more sophisticated healthcare system and real-time data analytics in the pandemic mitigation process. Moreover, real-time data plays a crucial role in the detection and alerting process. Combining smart healthcare systems with accurate real-time information about medical service availability, vaccination, and how the pandemic is spreading can directly affect the quality of life and economy.

Wide-area measurement system-based supervision of protection schemes with minimum number of phasor measurement units.

Cascade tripping of power lines triggered by maloperation of zone-3 relays during stressed system conditions, such as load encroachment, power swing and voltage instability, has led to many catastrophic power failures worldwide, including Indian blackouts in 2012. With the introduction of wide-area measurement systems (WAMS) into the grids, real-time monitoring of transmission network condition is possible. A phasor measurement unit (PMU) sends time-synchronized data to a phasor data concentrator, which can provide a control signal to substation devices.