This paper introduces an explainable transformer model for predicting clinical trial outcomes. It combines entity-aware embeddings with label-guided attention to interpret patient responses over time, supporting evidence-based decisions in drug development and clinical research pipelines.

Liu Jian Tao, Xu Hao Ning, Gao Wen Rui, Chen Bo Liang, Zhang Li Sheng, Huang Yuan Feng

This study presents a transformer model for traffic prediction. By fusing spatiotemporal signals with dynamic attention at the region level, it improves the detection of congestion patterns and supports traffic optimization in real-time smart city applications.

Chen Ming Rui, Liu Zhi Wei, Zhang Hua Ping, Xu Jie Long, Gao Rong Xin, Huang Yao Lin

We propose a cardiac arrhythmia detection system leveraging multi-channel ECG signal augmentation. Incorporating self-attention layers, the model improves early classification accuracy and robustness across diverse patient groups in wearable health monitoring platforms.

Neha Ramesh Iyer, Taro Kenji Nakamoto, Elena Lucia Bianchi, Kunal Harish Deshmukh, Jean Claude Rousseau

This paper introduces a multi-task learning framework for legal text mining. It jointly performs entity recognition and relation extraction using attention layers, enhancing information retrieval and document structuring in multi-jurisdictional, multilingual legal environments.

Emily Thompson, Michael Grant, Olivia Simmons, Thomas Bradley, Sarah Jenkins

This work presents a graph convolutional model for detecting node failures in IIoT systems. It captures temporal drift and connectivity dynamics, ensuring robust predictions and reducing unplanned downtime across industrial sensor networks.

Chen Yu Bo, Liu Cheng Zhi, Gao Wen Liang, Zhang Ming Rui, Xu Hao Sheng

This research proposes a reinforcement learning framework for smart energy control. The system adjusts power consumption dynamically, optimizing for environmental inputs and user preferences while reducing energy costs and improving sustainability in intelligent building infrastructures.

Amit Raghav Mehta, Jean Louis Moreau, Priya Sushma Nair, Fatima Noor Al-Fayed, Carlos Manuel Torres