TransFair: Transferring fairness from ocular disease classification to progression prediction [0.03%]
基于眼科疾病分类的眼科疾病进展预测的公平性迁移方法
Min Shi,Leila Gheisi,Chee-Hung Henry Chu et al.
Min Shi et al.
The use of artificial intelligence (AI) in automated disease classification significantly reduces healthcare costs and improves the accessibility of services. However, this transformation has given rise to concerns about the fairness of AI,...
Leveraging artificial intelligence in advance care planning: A scoping review [0.03%]
利用人工智能进行护理规划的现状与前景：综述研究
Minghui Tan,Siyuan Tang,Zhao Ni et al.
Minghui Tan et al.
Background: Advance care planning (ACP) is a process that enables individuals to discuss future health care decisions before they become seriously ill or unable to communicate. Artificial intelligence (AI) has demonstrate...
ProtoRadNet: Prototypical patches of Convolutional Features for Radiology Image Classification Network [0.03%]
原型图块的卷积特征医学影像分类网络
Prateek Sarangi,Riya Agarwal,Tanmay Basu
Prateek Sarangi
Convolutional Neural Networks (CNNs) have achieved significant success in classifying radiology images; however, their implementation often resembles a "black box," limiting medical practitioners' ability to comprehend and trust the decisio...
Development and validation of deep continual learning model to sequentially learn multiple clinical prediction tasks for ICU patients [0.03%]
深度连续学习模型的发展与验证，该模型可依次对重症监护室患者的多个临床预测任务进行学习
Zhixuan Zeng,Yang Liu,Shuo Yao et al.
Zhixuan Zeng et al.
Background: ICU patients often suffer from critical and complex condition, and multiple potential risks should be monitored to provide them comprehensive care. However, no study proposes continual learning (CL) model that...
QENNA: A quantum-enhanced neural network for early Alzheimer's detection using magnetic resonance imaging [0.03%]
QENNA：一种量子增强神经网络使用磁共振成像进行早期阿尔茨海默病检测
Chutchai Kaewta,Rapeepan Pitakaso,Surajet Khonjun et al.
Chutchai Kaewta et al.
Early detection of Alzheimer's disease (AD) is essential for effective clinical intervention and disease management. However, conventional Deep Learning (DL) methods face limitations in analyzing complex brain magnetic resonance imaging (MR...
Artificial intelligence use and performance in detecting and predicting healthcare-associated infections: A systematic review [0.03%]
人工智能在检测和预测与医疗相关的感染中的应用和性能：系统性综述
Chiara Barbati,Luca Viviani,Riccardo Vecchio et al.
Chiara Barbati et al.
Objectives: The increasing digitisation of healthcare data and the rapid development of Artificial Intelligence (AI) pave the way for innovative strategies for infectious disease management. This study aimed to systematic...
Artificial intelligence in depression diagnostics: A systematic review of methodologies and clinical applications [0.03%]
抑郁症诊断中人工智能的应用：方法与临床应用系统综述
Mahdi Ghorbankhani,Maryam Safara
Mahdi Ghorbankhani
The integration of artificial intelligence (AI) into the field of mental health diagnosis has garnered increasing scholarly and clinical attention, particularly in relation to the early detection and classification of depression. This study...
Data Augmentation for Few-Shot Biomedical NER Using ChatGPT [0.03%]
基于ChatGPT的few-shot生物医学命名实体识别数据增强方法
Wenxuan Mu,Di Zhao,Jiana Meng et al.
Wenxuan Mu et al.
Data Augmentation (DA) aims to create a new dataset to address the lack of data in various domains. Particularly in few-shot scenarios of the biomedical Named Entity Recognition (NER) domain, an effective DA method can enhance data diversit...
Geometric deep learning for local growth prediction on abdominal aortic aneurysm surfaces [0.03%]
基于几何深度学习的腹主动脉瘤壁局部生长预测模型
Dieuwertje Alblas,Patryk Rygiel,Julian Suk et al.
Dieuwertje Alblas et al.
Abdominal aortic aneurysms (AAAs) are progressive focal dilatations of the abdominal aorta. AAAs may rupture, with fatal consequences in >80% of cases. Current clinical guidelines recommend elective surgical repair when the maximum AAA diam...
Deep learning for autism detection using clinical notes: A comparison of transfer learning for a transparent and black-box approach [0.03%]
基于临床记录的自闭症深度检测：透明方法与黑盒方法的迁移学习比较研究
Gondy Leroy,Prakash Bisht,Sai Madhuri Kandula et al.
Gondy Leroy et al.
Autism spectrum disorder (ASD) is a complex neurodevelopmental condition whose rising prevalence places increasing demands on a lengthy diagnostic process. Machine learning (ML) has shown promise in automating ASD diagnosis, but most existi...