Stress prediction using micro-EMA and machine learning during COVID-19 social isolation [0.03%]
基于微观体验取样和机器学习的新冠疫情隔离期间压力预测研究
Huining Li,Enhao Zheng,Zijian Zhong et al.
Huining Li et al.
Accurately predicting users' perceived stress is beneficial to aid early intervention and prevent both mental illness and physical disease during the COVID-19 pandemic. However, the existing perceived stress predicting system needs to colle...
Sabrina Sicari,Alessandra Rizzardi,Alberto Coen-Porisini
Sabrina Sicari
Patients' remote monitoring becomes even more crucial due to the spreading of the COVID-19 disease. Hospitals cannot accommodate all the patients who need to be taken care. Hence, tele-medicine or, as also named, tele-health, remains the on...
Predicting Progression Patterns of Type 2 Diabetes using Multi-sensor Measurements [0.03%]
使用多传感器测量预测二型糖尿病的进展模式
Ramin Ramazi,Christine Perndorfer,Emily C Soriano et al.
Ramin Ramazi et al.
Type 2 diabetes - a prevalent chronic disease worldwide - increases risk for serious health consequences including heart and kidney disease. Forecasting diabetes progression can inform disease management strategies, thereby potentially redu...
Impact of COVID-19 on city-scale transportation and safety: An early experience from Detroit [0.03%]
COVID-19对城市规模的交通运输和安全的影响：底特律的早期经验
Yongtao Yao,Tony G Geara,Weisong Shi
Yongtao Yao
The COVID-19 pandemic brought unprecedented levels of disruption to the local and regional transportation networks throughout the United States, especially the Motor City---Detroit. That was mainly a result of swift restrictive measures suc...
Predicting mortality risk in patients with COVID-19 using machine learning to help medical decision-making [0.03%]
利用机器学习预测COVID-19患者的死亡风险以助力医疗决策
Mohammad Pourhomayoun,Mahdi Shakibi
Mohammad Pourhomayoun
In the wake of COVID-19 disease, caused by the SARS-CoV-2 virus, we designed and developed a predictive model based on Artificial Intelligence (AI) and Machine Learning algorithms to determine the health risk and predict the mortality risk ...
iWash: A smartwatch handwashing quality assessment and reminder system with real-time feedback in the context of infectious disease [0.03%]
基于传染病背景下具有实时反馈的智能手表洗手质量评估和提醒系统
Sirat Samyoun,Sudipta Saha Shubha,Md Abu Sayeed Mondol et al.
Sirat Samyoun et al.
Washing hands properly and frequently is the simplest and most cost-effective interventions to prevent the spread of infectious diseases. People are often ignorant about proper handwashing in different situations and do not know if they was...
Elishiah Miller,Nilanjan Banerjee,Ting Zhu
Elishiah Miller
Coughing, sneezing, and face touching activities are three primary ways of spreading disease. With the onset of COVID-19 it is paramount to monitor these activities at home and practice good hygiene. To help stop the spread of disease, we h...
MaskedFace-Net - A dataset of correctly/incorrectly masked face images in the context of COVID-19 [0.03%]
MaskedFace-Net：一个关于正确/错误佩戴口罩面部的图像数据集（在COVID-19背景下）
Adnane Cabani,Karim Hammoudi,Halim Benhabiles et al.
Adnane Cabani et al.
Wearing face masks appears as a solution for limiting the spread of COVID-19. In this context, efficient recognition systems are expected for checking that people faces are masked in regulated areas. Hence, a large dataset of masked faces i...
Topic modeling for systematic review of visual analytics in incomplete longitudinal behavioral trial data [0.03%]
纵向行为试验数据的可视化分析系统回顾的主题模型研究
Joshua Rumbut,Hua Fang,Honggong Wang
Joshua Rumbut
Longitudinal observational and randomized controlled trials (RCT) are widely applied in biomedical behavioral studies and increasingly implemented in smart health systems. These trials frequently produce data that are high-dimensional, corr...
Golnoush Asaeikheybari,Monica Webb Hooper,Ming-Chun Huang
Golnoush Asaeikheybari
Cigarette smoking is the primary preventable cause of death and disease worldwide. Studies reveal that smoking is associated with psychiatric symptoms, sociodemographic characteristics, social stressors, and lack of social support. In gener...