Recognition of autism in subcortical brain volumetric images using autoencoding-based region selection method and Siamese Convolutional Neural Network [0.03%]
基于自编码区域选择方法和暹罗卷积神经网络的亚皮质脑体积图像自闭症识别技术
Anas Abu-Doleh,Isam F Abu-Qasmieh,Hiam H Al-Quran et al.
Anas Abu-Doleh et al.
Background: Autism Spectrum Disorder (ASD) is a neurodevelopmental condition that affects social interactions and behavior. Accurate and early diagnosis of ASD is still challenging even with the improvements in neuroimagi...
Electronic health records and data exchange in the WHO European region: A subregional analysis of achievements, challenges, and prospects [0.03%]
欧洲区域电子健康记录和数据交换的次区域分析：成就、挑战与前景
Roberto Tornero Costa,Keyrellous Adib,Nagui Salama et al.
Roberto Tornero Costa et al.
Electronic health record (EHR) systems are powerful tools that enhance healthcare quality. They improve efficiency, enable data exchange, and ensure authorized access to patient information. In 2022, the World Health Organization Regional O...
Usefulness of self-guided digital services among mental health patients: The role of health confidence and sociodemographic characteristics [0.03%]
精神疾病患者使用自助数字服务的情况：健康自信度和人口统计学特征的作用
Iiris Hörhammer,Johanna Suvanto,Maarit Kinnunen et al.
Iiris Hörhammer et al.
Background: Remote services provided via telephone or the internet have become an essential part of mental health provision. Alongside services involving healthcare personnel (HCP), self-guided digital services hold great...
A machine-learning-based algorithm for bone marrow cell differential counting [0.03%]
基于机器学习的骨髓细胞分类计数算法
Ta-Chuan Yu,Cheng-Kun Yang,Wei-Han Hsu et al.
Ta-Chuan Yu et al.
Background: Differential counting (DC) of different cell types in bone marrow (BM) aspiration smears is crucial for diagnosing hematological diseases. However, a clinically applicable method for automatic DC has yet to be...
Supporting the care to breast cancer patients with unique needs: Evidence from online community members' responses [0.03%]
具有特殊需要的乳腺癌患者的护理支持：来自在线社区成员回复的证据
Anqi Xu,Yuanyuan Gao
Anqi Xu
Background: Breast cancer is the most common cancer diagnosed in women globally. Online cancer communities (OCCs) provide platforms for breast cancer patients to connect, share experiences, and support each other. These c...
Predicting Fear of Breast Cancer Recurrence in women five years after diagnosis using Machine Learning and healthcare reimbursement data from the French nationwide VICAN survey [0.03%]
基于法国全国VICAN调查的机器学习和医疗保健报销数据预测确诊五年后女性乳腺癌复发的恐惧
Mamoudou Koume,Lorène Seguin,Julien Mancini et al.
Mamoudou Koume et al.
Objective: A major concern for cancer survivors after treatment is the Fear of Cancer Recurrence (FCR), which is the fear that cancer will reappear or progress. This fear can be exacerbated by medical uncertainty about th...
Machine learning adjusted sequential CUSUM-analyses are superior to cross-sectional analysis of excess mortality after surgery [0.03%]
机器学习校正的序贯CUSUM分析优于手术后超额死亡的横断面分析
Florian Bösch,Stina Schild-Suhren,Elif Yilmaz et al.
Florian Bösch et al.
Background: The assessment of clinical outcome quality, particularly in surgery, is crucial for healthcare improvement. Traditional cross-sectional analyses often fall short in timely and systematic identification of clin...
Balancing accuracy and Interpretability: An R package assessing complex relationships beyond the Cox model and applications to clinical prediction [0.03%]
超越Cox模型的复杂关系的R语言评估包及临床预测应用研究
Diana Shamsutdinova,Daniel Stamate,Daniel Stahl
Diana Shamsutdinova
Background: Accurate and interpretable models are essential for clinical decision-making, where predictions can directly impact patient care. Machine learning (ML) survival methods can handle complex multidimensional data...
Deep learning-driven ultrasound equipment quality assessment with ATS-539 phantom data [0.03%]
基于ATS-539模体数据的深度学习驱动超声设备质量评估方法
Dong Hoon Jang,Ji Won Heo,Kyu Hong Lee et al.
Dong Hoon Jang et al.
Introduction: Ultrasound equipment provides real-time visualization of internal organs, essential for early disease detection and diagnosis. However, poor-quality ultrasound images can compromise diagnostic accuracy and i...
Healthy nutrition and weight management for a positive pregnancy experience in the antenatal period: Comparison of responses from artificial intelligence models on nutrition during pregnancy [0.03%]
产前健康营养和体重管理以获得积极的妊娠体验：人工智能模型对孕期营养反应的比较
Emine Karacan
Emine Karacan
Background: As artificial intelligence AI-supported applications become integral to web-based information-seeking, assessing their impact on healthy nutrition and weight management during the antenatal period is crucial. ...