45 citations · 85 across the 7 of their papers we have counts for
7 papers
Disease Insight through Digital Biomarkers Developed by Remotely Collected Wearables and Smartphone Data
Zulqarnain Rashid, Amos A Folarin, Yatharth Ranjan +7
Digital Biomarkers and remote patient monitoring can provide valuable and timely insights into how a patient is coping with their condition (disease progression, treatment response…
Foresight -- Generative Pretrained Transformer (GPT) for Modelling of Patient Timelines using EHRs
Zeljko Kraljevic, Dan Bean, Anthony Shek +9
Background: Electronic Health Records hold detailed longitudinal information about each patient's health status and general clinical history, a large portion of which is stored wit…
Challenges in Using mHealth Data From Smartphones and Wearable Devices to Predict Depression Symptom Severity: Retrospective Analysis
Shaoxiong Sun, Amos A. Folarin, Yuezhou Zhang +28
A number of challenges exist for the analysis of mHealth data: maintaining participant engagement over extended time periods and therefore understanding what constitutes an accepta…
Predicting Clinical Intent from Free Text Electronic Health Records
Kawsar Noor, Katherine Smith, Julia Bennett +9
After a patient consultation, a clinician determines the steps in the management of the patient. A clinician may for example request to see the patient again or refer them to a spe…
Associations between depression symptom severity and daily-life gait characteristics derived from long-term acceleration signals in real-world settings
Yuezhou Zhang, Amos A Folarin, Shaoxiong Sun +27
Gait is an essential manifestation of depression. Laboratory gait characteristics have been found to be closely associated with depression. However, the gait characteristics of dai…
The utility of wearable devices in assessing ambulatory impairments of people with multiple sclerosis in free-living conditions
Shaoxiong Sun, Amos A Folarin, Yuezhou Zhang +25
Multiple sclerosis (MS) is a progressive inflammatory and neurodegenerative disease of the central nervous system affecting over 2.5 million people globally. In-clinic six-minute w…
Fitbeat: COVID-19 Estimation based on Wristband Heart Rate
Shuo Liu, Jing Han, Estela Laporta Puyal +26
This study investigates the potential of deep learning methods to identify individuals with suspected COVID-19 infection using remotely collected heart-rate data. The study utilise…