Wearable full-body motion tracking of activities of daily living predicts disease trajectory in Duchenne muscular dystrophy V Ricotti, B Kadirvelu, V Selby, R Festenstein, E Mercuri, T Voit, AA Faisal Nature medicine 29 (1), 95-103, 2023 | 45 | 2023 |
Accuracy and acceptability of wearable motion tracking for inpatient monitoring using smartwatches C Auepanwiriyakul, S Waibel, J Songa, P Bentley, AA Faisal Sensors 20 (24), 7313, 2020 | 45 | 2020 |
A wearable motion capture suit and machine learning predict disease progression in Friedreich’s ataxia B Kadirvelu, C Gavriel, S Nageshwaran, JPK Chan, S Nethisinghe, ... Nature medicine 29 (1), 86-94, 2023 | 36 | 2023 |
Variation in global COVID-19 symptoms by geography and by chronic disease: A global survey using the COVID-19 Symptom Mapper B Kadirvelu, G Burcea, JK Quint, CE Costelloe, AA Faisal EClinicalMedicine 45, 2022 | 28 | 2022 |
Inferring structural connectivity using Ising couplings in models of neuronal networks B Kadirvelu, Y Hayashi, SJ Nasuto Scientific reports 7 (1), 8156, 2017 | 27 | 2017 |
Accuracy and acceptability of wearable motion tracking smartwatches for inpatient monitoring C Auepanwiriyakul, S Waibel, J Songa, P Bentley, AA A. Faisal medRxiv, 2020.07. 24.20160663, 2020 | 4 | 2020 |
Mindcraft, a Mobile Mental Health Monitoring Platform for Children and Young People: Development and Acceptability Pilot Study B Kadirvelu, T Bellido Bel, X Wu, V Burmester, S Ananth, ... JMIR Formative Research 7, e44877, 2023 | 3 | 2023 |
Covid-19 does not look like what you are looking for: clustering symptoms by nation and multi-morbidities reveal substantial differences to the classical symptom triad B Kadirvelu, G Burcea, JK Quint, CE Costelloe, AA Faisal medRxiv, 2021.04. 02.21254818, 2021 | 2 | 2021 |
Clustering of patient comorbidities within electronic medical records enables high-precision COVID-19 mortality prediction EL Lannou, B Post, S Haar, SJ Brett, B Kadirvelu, AA Faisal medRxiv, 2021.03. 29.21254579, 2021 | 2 | 2021 |
P. 203Towards high-resolution clinical digital biomarkers for Duchenne muscular dystrophy V Ricotti, B Kadirvelu, V Selby, T Voit, A Faisal Neuromuscular Disorders 29, S108, 2019 | 2 | 2019 |
Data-derived wearable digital biomarkers predict Frataxin gene expression levels and longitudinal disease progression in Friedreich’s Ataxia A Faisal, B Kadirvelu, C Gavriel, S Nageshwaran, PKJ Chan, ... | 1 | 2021 |
P. 204Full-body behaviour analytics reveals DMD disease state within the first few steps of the 6-minute-walk test V Ricotti, B Kadirvelu, S Rabinowicz, V Selby, T Voit, A Faisal Neuromuscular Disorders 29, S108-S109, 2019 | 1 | 2019 |
P. 205Daily life digital biomarkers for longitudinal monitoring of Duchenne muscular dystrophy with wearable sensors V Ricotti, B Kadirvelu, C Auepanwiriyakul, S Zeng, V Selby, T Voit, ... Neuromuscular Disorders 29, S109, 2019 | 1 | 2019 |
Speaker-Independent Dysarthria Severity Classification using Self-Supervised Transformers and Multi-Task Learning L Stumpf, B Kadirvelu, S Waibel, AA Faisal arXiv preprint arXiv:2403.00854, 2024 | | 2024 |
Research briefing AA Faisal, B Kadirvelu Nature Medicine 29, 37-38, 2023 | | 2023 |
Wearables and AI better predict the progression of muscular dystrophy AA Faisal, B Kadirvelu NATURE MEDICINE 29 (1), 37-38, 2023 | | 2023 |
Wearable full-body motion tracking of daily-life activities predicts disease trajectory in Duchenne Muscular Dystrophy V Ricotti, K Balasundaram, S Victoria, R Festenstein, M Eugenio, ... Nature Research, 2023 | | 2023 |
Clustering of patient comorbidities within electronic medical records enables high-precision COVID-19 mortality prediction A Faisal, E Le Lannou, B Post, S Haar, S Brett, B Kadirvelu | | 2021 |
Analytics Dashboard for Duchenne Muscular Dystrophy Clinical Trials T Bellingham, A Faisal, R Misener | | 2019 |
Inferring structural connectivity using Ising couplings in models of neuronal networks (vol 7, 2017) B Kadirvelu, Y Hayashi, SJ Nasuto SCIENTIFIC REPORTS 8, 2018 | | 2018 |