Using unsupervised machine learning to quantify physical activity from accelerometry in a diverse and rapidly changing population [0.03%]
利用无监督机器学习量化多民族和人口快速变化人群的加速计测得的体格活动水平
Christopher B Thornton,Niina Kolehmainen,Kianoush Nazarpour
Christopher B Thornton
Accelerometers are widely used to measure physical activity behaviour, including in children. The traditional method for processing acceleration data uses cut points to define physical activity intensity, relying on calibration studies that...
Modelling and classifying joint trajectories of self-reported mood and pain in a large cohort study [0.03%]
在一个大型队列研究中对自我报告的 mood 和 pain 的关节轨迹进行建模和分类
Rajenki Das,Mark Muldoon,Mark Lunt et al.
Rajenki Das et al.
It is well-known that mood and pain interact with each other, however individual-level variability in this relationship has been less well quantified than overall associations between low mood and pain. Here, we leverage the possibilities p...
Exploring how informed mental health app selection may impact user engagement and satisfaction [0.03%]
探索知情的精神健康应用程序选择可能如何影响用户参与度和满意度
Marvin Kopka,Erica Camacho,Sam Kwon et al.
Marvin Kopka et al.
The prevalence of mental health app use by people suffering from mental health disorders is rapidly growing. The integration of mental health apps shows promise in increasing the accessibility and quality of treatment. However, a lack of co...
Developing better digital health measures of Parkinson's disease using free living data and a crowdsourced data analysis challenge [0.03%]
利用日常活动数据和众包数据分析竞赛开发更好的数字健康帕金森病检测方法
Solveig K Sieberts,Henryk Borzymowski,Yuanfang Guan et al.
Solveig K Sieberts et al.
One of the promising opportunities of digital health is its potential to lead to more holistic understandings of diseases by interacting with the daily life of patients and through the collection of large amounts of real-world data. Validat...
Capturing children food exposure using wearable cameras and deep learning [0.03%]
基于可穿戴相机和深度学习的儿童食品接触行为记录方法研究
Shady Elbassuoni,Hala Ghattas,Jalila El Ati et al.
Shady Elbassuoni et al.
Children's dietary habits are influenced by complex factors within their home, school and neighborhood environments. Identifying such influencers and assessing their effects is traditionally based on self-reported data which can be prone to...
Moving beyond algorithmic accuracy to improving user interaction with clinical AI [0.03%]
从改进临床AI用户交互的角度超越算法准确性
Shlomo Berkovsky,Enrico Coiera
Shlomo Berkovsky
3D facial analysis for rare disease diagnosis and treatment monitoring: Proof-Of-Concept plan for hereditary angioedema [0.03%]
用于遗传性血管水肿罕见病诊断和治疗监测的三维面部分析：概念验证方案
Saumya Jamuar,Richard Palmer,Hugh Dawkins et al.
Saumya Jamuar et al.
Rare diseases pose a diagnostic conundrum to even the most experienced clinicians around the world. The technology could play an assistive role in hastening the diagnosis process. Data-driven methodologies can identify distinctive disease f...
Explainable AI identifies diagnostic cells of genetic AML subtypes [0.03%]
解释性人工智能识别遗传性急性髓系白血病亚型的诊断细胞
Matthias Hehr,Ario Sadafi,Christian Matek et al.
Matthias Hehr et al.
Explainable AI is deemed essential for clinical applications as it allows rationalizing model predictions, helping to build trust between clinicians and automated decision support tools. We developed an inherently explainable AI model for t...
Data heterogeneity in federated learning with Electronic Health Records: Case studies of risk prediction for acute kidney injury and sepsis diseases in critical care [0.03%]
基于电子健康档案的联邦学习中的数据异质性：重症监护中急性肾损伤和脓毒症病例研究
Suraj Rajendran,Zhenxing Xu,Weishen Pan et al.
Suraj Rajendran et al.
With the wider availability of healthcare data such as Electronic Health Records (EHR), more and more data-driven based approaches have been proposed to improve the quality-of-care delivery. Predictive modeling, which aims at building compu...
Varied performance of picture description task as a screening tool across MCI subtypes [0.03%]
跨MCI亚型的图片描述任务作为筛查工具的表现力不同
Joel A Mefford,Zilong Zhao,Leah Heilier et al.
Joel A Mefford et al.
A picture description task is a component of Miro Health's platform for self-administration of neurobehavioral assessments. Picture description has been used as a screening tool for identification of individuals with Alzheimer's disease and...