Jenhui Chen

Multimodal GPT-5 for Predicting Poor Functional Outcomes After Intracerebral Hemorrhage in the Emergency Department: Validation Study

Koutarou Matsumoto, Ken Ishihara, Ryota Tamba, Yusuke Fujiyoshi et autres

Background: In the emergency department, rapid prognostic assessment of patients with intracerebral hemorrhage (ICH) is essential for guiding early management decisions, particularly when stroke specialists are not immediately available. Recent advances in large language models have generated interest in their potential utility …

jp, tw (code pays fourni par la source)

WiFi-Based Assessment of Scoliosis-Related Spinal Postures

Xichen Gao, Lei Wang, Jenhui Chen, Jiancheng Chi et autres

With the widespread adoption of WiFi technology, WiFi-based human sensing has shown significant potential in healthcare applications, particularly for spinal posture assessment. Conventional diagnostic methods, such as X-ray imaging, involve radiation exposure and require specialized equipment, making them costly and unsuitable for …

cn, jp, tw (code pays fourni par la source)

Adaptive Split Federated Learning With Behavioral Digital Twins and Multi-Head Temporal Networks for Internet of Vehicles Security

Farhan Ullah, Khalid Mahmood, Umar Raza, Jawad Ahmad et autres

The rapid growth of the Internet of Vehicles (IoV) ecosystem has produced complicated security concerns that require a modern Intrusion Detection System (IDS) that can respond to emerging threats and maintain data protection. The dynamic behavior of clients and the heterogeneity of …

sa, tw, gb, pk, cn (code pays fourni par la source)

Entropy-based Cluster Selection for Unsupervised Lifelong Person Re-identification

Yuk Yii Chan, Chih-Wei Chen, Ashu Abdul, Jenhui Chen

CIWGS-FedMed: Channel-Importance Weighted Gradient Sparsification for Communication Efficient Federated Medical Image Segmentation

Moneeb Abbas, Wen‐Chung Kuo, Khalid Mahmood, Muhammad Asad Saleem et autres

tw, sa (code pays fourni par la source)

ESCA-Net: Knowledge-Guided Encoder-Shared Classification and Auxiliary Segmentation Network for Multi-Label Catheter Malposition Assessment in Chest Radiographs

Moneeb Abbas, Wen‐Chung Kuo, Khalid Mahmood, Shakila Basheer et autres

Malpositioned medical tubes and catheters are a persistent source of iatrogenic harm in critical care, yet the radiographic interpretation burden on intensive care units remains substantial. We present ESCA-Net, a knowledge-guided dual-task deep learning framework for simultaneous multi-label classification of endotracheal tubes …

tw, sa, in (code pays fourni par la source)

Multimodal GPT-5 for Predicting Poor Functional Outcomes After Intracerebral Hemorrhage in the Emergency Department: Validation Study (Preprint)

Koutarou Matsumoto, Ken Ishihara, Ryota Tamba, Yusuke Fujiyoshi et autres

BACKGROUND In the emergency department (ED), rapid prognostic assessment of patients with intracerebral hemorrhage (ICH) is essential for guiding treatment, even when stroke specialists are unavailable. Recent advances in large language models have triggered the increased application of machine learning (ML) models …

A lightweight image segmentation network leveraging inception and squeeze-excitation modules for efficient skin lesion analysis

Woei-Hwa Tarn, C.P. Chong, Lei Wang, Chang‐Fu Kuo et autres

cn, tw, us (code pays fourni par la source)

Grading of Foveal Hypoplasia Using Deep Learning on Retinal Fundus Images

Tsung‐Ying Tsai, Ying-Feng Chang, Eugene Yu‐Chuan Kang, Kuan‐Jen Chen et autres

Purpose: This study aimed to develop and evaluate a deep learning model for grading foveal hypoplasia using retinal fundus images. Methods: This retrospective study included patients with foveal developmental disorders, using color fundus images and optical coherence tomography scans taken between January …

tw (code pays fourni par la source)

Performance of multimodal prediction models for intracerebral hemorrhage outcomes using real-world data

Koutarou Matsumoto, Masahiro Suzuki, Kazuaki Ishihara, Koki Tokunaga et autres

BACKGROUND: We aimed to develop and validate multimodal models integrating computed tomography (CT) images, text and tabular clinical data to predict poor functional outcomes and in-hospital mortality in patients with intracerebral hemorrhage (ICH). These models were designed to assist non-specialists in emergency …

jp, tw (code pays fourni par la source)

Novel Photonic Mems Smart Glass - Huge Energy Savings in Buildings and Personalized Lighting

Hartmut Hillmer, Mustaqim Siddi Que Iskhandar, Muhammad Kamrul Hasan, Shilby Baby et autres

Nowadays buildings consume the largest amount of primary energy only to cover lighting, heating and cooling. This is a major contribution to rapid global warming, rising sea levels, and profound changes in ocean ecosystems by emitting a massive amount of$\text{CO}_{2}$. MEMS11micro-electro-mechanical-systems. micromirror …

de (code pays fourni par la source)

ISLS: IoT-Based Smart Lighting System for Improving Energy Conservation in Office Buildings

P.C. Obioma, Obinna Agbodike, Jenhui Chen, Lei Wang

With the Internet of Things (IoT) fostering seamless device-to-human and device-to-device interactions, the domain of intelligent lighting systems have evolved beyond simple occupancy and daylight sensing towards autonomous monitoring and control of power consumption and illuminance levels. To this regard, this paper …