We are pleased to announce that the paper “A Power-Efficient Analog Integrated Decision Tree Classifier for Dementia Prediction” received the Silver Leaf Certificate at the 20th International Conference on PhD Research in Microelectronics and Electronics (PRIME 2025), held in Taormina, Italy, on 21–24 September 2025.

The Award-Winning paper was co-authored by Anna Mylona (Diploma Student, ECE-NTUA and Researcher Archimedes/Athena RC – first author), Dr. Vassilis Alimisis (Researcher, ECE-NTUA and Postdoctoral Researcher Archimedes/Athena RC), Kostantinos Cheliotis (Diploma Student, ECE-NTUA and Researcher Archimedes/Athena RC), Vasileios Moustakas (PhD Student, ECE-NTUA and Researcher Archimedes/Athena RC) and Paul P. Sotiriadis (Professor, ECE-NTUA; Lead Researcher, Archimedes/Athena RC; IEEE, AIIA & AAIA Fellow).

ABSTRACT: An analog integrated decision tree classifier designed for real-time dementia prediction with low power consumption is presented in this work. The design uses sub-threshold analog circuitry, including a squarer circuit, analog multiplier, and current comparator, to achieve an exceptionally low power consumption of 729 nW and a classification speed of 570K inferences per second. It is developed using the TSMC 65nm CMOS process. The classifier consistently performed well despite process, voltage, and temperature fluctuations, achieving an average accuracy of 90.63% when tested on a dataset representative of machine operating conditions. Through the prediction of dementia neurological disorder, this method offers effective, real-time, edge-based classification in biomedical settings.