Efficient Vision Transformers for Ophthalmic Images Classification: A Comparative Study of Supervised, Semi-Supervised, and Unsupervised Learning Approaches [0.03%]
眼科图像分类的高效视觉Transformer：监督、半监督和无监督学习方法的比较研究
Ahmed Shakir Al-Wassiti,Mohammed Tareq Mutar,Ahmed Sermed Al Sakini et al.
Ahmed Shakir Al-Wassiti et al.
This study explored the integration of supervised, semi-supervised, and unsupervised learning strategies to classify ophthalmic images under label-scarce conditions. Given the high cost of annotations in medical imaging, the goal was to imp...
Comparative Study
Journal of medical systems. 2025 Nov 17;49(1):160. DOI:10.1007/s10916-025-02292-y 2025
Gianluca Aguzzi,Matteo Magnini,Aqila Farahmand et al.
Gianluca Aguzzi et al.
Chronic disease management requires continuous monitoring, lifestyle modification and therapy adherence, thus requiring constant support from healthcare professionals. Chatbots have proven to be a promising approach for engaging patients in...
Evaluating the Performance of DeepSeek-R1 as a Patient Education Tool [0.03%]
评估DeepSeek-R1作为患者教育工具的性能
Jiating Hu,Junnan Wang,Lu He et al.
Jiating Hu et al.
The cost-effective open-source artificial intelligence (AI) model DeepSeek-R1 in China holds significant potential for healthcare applications. As a health education tool, it could help patients acquire health science knowledge and improve ...
Estimating LVEF from ECG with GPT-4o Fine-Tuned Vision: A Novel Approach in AI-Driven Cardiac Diagnostics [0.03%]
基于GPT-4微调视觉的ECG估计LVEF值：人工智能驱动的心脏诊断新方法
Haya Engelstein,Roni Ramon-Gonen,Israel Barbash et al.
Haya Engelstein et al.
Background: Assessing Left Ventricular Ejection Fraction (LVEF) is crucial for diagnosing reduced systolic function, yet echocardiography (ECHO) may not always be readily available, potentially delaying treatment. Electro...
Generalist Models in Specialized Domains: Evaluating Contrastive Language-image Pre-training for Zero-shot Anomaly Detection in Brain MRI [0.03%]
通用模型在专业领域的应用：评估对比语言-图像预训练在脑MRI零样本异常检测中的表现
Aldo Marzullo,Nicolò Cappa,Matteo Morellini et al.
Aldo Marzullo et al.
Zero-shot anomaly detection (ZSAD) is gaining traction in medical imaging as a way to identify abnormalities without task-specific supervision. In this work, we benchmark state-of-the-art CLIP-based ZSAD models -originally developed for ind...
Leveraging Customer Data Platforms for Public Health: a Strategic Perspective [0.03%]
利用客户数据平台进行公共卫生：战略视角
Gianmarco Sirago,Marcello Benevento,Francesco De Micco et al.
Gianmarco Sirago et al.
Public health increasingly relies on digital infrastructures, yet data remains fragmented across clinical, behavioral, and social domains. Customer Data Platforms (CDPs), originally created in marketing to unify diverse information into dyn...
Trust is all you Need: Reinforcing the Patient-physician Bond in Times of AI [0.03%]
信任是唯一需要的：在人工智能时代巩固医患关系
Florian Reis,Moritz Reis,Norman Michael Drzeniek et al.
Florian Reis et al.
A Feature Extraction and Selection Framework for Electrocorticography-Based Neural Activity Classification [0.03%]
一种基于脑电皮层记录的神经活动分类的特征提取与选择框架
Resul Adanur,Ebubekir Enes Arslan,Uğurhan Kutbay et al.
Resul Adanur et al.
Electrocorticography (ECoG) signals provide a valuable window into neural activity, yet their complex structure makes reliable classification challenging. This study addresses the problem by proposing a feature-selective framework that inte...
Virtual Reality (VR) Paradigm-Agnostic Motor Imagery Decoding Using Lightweight Network With Adaptive Attention Mechanism [0.03%]
基于自适应注意力机制的轻量级网络的虚拟现实(VR)范式不可知型运动想象解码方法
Rongrong Fu,Yang Liu,Zeyi Wang et al.
Rongrong Fu et al.
Motor imagery (MI) is widely used in brain-computer interfaces (BCIs) due to its simplicity and reproducibility, enabling individuals with motor impairments to perform non-muscular limb training for the rehabilitation of motor-related neuro...
Weihao Cheng,Enjian Liu,Zekai Yu
Weihao Cheng