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Predicting Current Glycated Hemoglobin Levels in Adults From Electronic Health Records: Validation of Multiple Logistic Regression Algorithm

Predicting Current Glycated Hemoglobin Levels in Adults From Electronic Health Records: Validation of Multiple Logistic Regression Algorithm

We employ comparative statistical models similar to the models used by Wells et al [2] and apply them to a larger electronic health record (EHR) dataset collected from King Abdullah International Medical Research Center (KAIMRC) [20,21] in Saudi Arabia.The

Zakhriya Alhassan, David Budgen, Riyad Alshammari, Noura Al Moubayed

JMIR Med Inform 2020;8(7):e18963


MERS-CoV Outbreak at Domat Al-Jandal Hospital

MERS-CoV Outbreak at Domat Al-Jandal Hospital

IPROCiprocIproceedings2369-6893JMIR PublicationsToronto, Canadav4i1e1060310.2196/10603AbstractAbstractMERS-CoV Outbreak at Domat Al-Jandal HospitalKhaderYousefAl-GuaimyAbdullahKamelSCorresponding Author: Abdullah Al-Guaimy doctorabduallah@gmail.comJan-Dec20182903201841e1060329320182932018

Abdullah Al-Guaimy, S Kamel

iproc 2018;4(1):e10603


Group-Personalized Regression Models for Predicting Mental Health Scores From Objective Mobile Phone Data Streams: Observational Study

Group-Personalized Regression Models for Predicting Mental Health Scores From Objective Mobile Phone Data Streams: Observational Study

For example, Lane et al [15] developed, and Abdullah et al [16] extended, an approach for finding groups of individuals based on the similarity of their demographics, lifestyle, and sensor data.

Niclas Palmius, Kate E A Saunders, Oliver Carr, John R Geddes, Guy M Goodwin, Maarten De Vos

J Med Internet Res 2018;20(10):e10194


Internet Mindfulness Meditation Intervention for the General Public: Pilot Randomized Controlled Trial

Internet Mindfulness Meditation Intervention for the General Public: Pilot Randomized Controlled Trial

The intervention was adapted from MBCT and MBSR to include shorter weekly sessions (1 hour vs 2.5 hours), less weekly sessions (6 vs 8), shorter meditations (30 minutes vs 45 minutes) and still included all the core mindfulness concepts (see Wahbeh, 2014 for

Helané Wahbeh, Barry S. Oken

JMIR Ment Health 2016;3(3):e37


Smartphones as Sleep Duration Sensors: Validation of the iSenseSleep Algorithm

Smartphones as Sleep Duration Sensors: Validation of the iSenseSleep Algorithm

In the related work section, we indicate the other smartphone or HCI-analysis methods with an error of 42 min (Chen et al [25]) or 45 min (Abdullah et al [26]) for sleep duration; these methods leveraged microphone and luminosity sensors besides, for example

Matteo Ciman, Katarzyna Wac

JMIR Mhealth Uhealth 2019;7(5):e11930


Barriers to Implementation of Perinatal Death Audit in Maternity and Pediatric Hospitals in Jordan: Cross-Sectional Study

Barriers to Implementation of Perinatal Death Audit in Maternity and Pediatric Hospitals in Jordan: Cross-Sectional Study

differ according to gender, profession, and years of experience.MethodsStudy DesignA cross-sectional study was conducted in 3 public hospitals and 1 teaching hospital, 3 hospitals from the north (Al-Mafraq Pediatrics Hospital, Princess Rahma Hospital, and King Abdullah

Yousef Khader, Mohammad Alyahya, Anwar Batieha

JMIR Public Health Surveill 2019;5(1):e11653