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Predicting Quality of Overnight Glycaemic Control in Type 1 Diabetes Using Binary Classifiers

IEEE journal of biomedical and health informatics, 2020-05, Vol.24 (5), p.1439-1446

2020

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Applying artificial intelligence and digital health technologies, Viet Nam

Bulletin of the World Health Organization, 2023-07, Vol.101 (7), p.487-492

2023

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Correction to: Informing antimicrobial management in the context of COVID-19: understanding the longitudinal dynamics of C-reactive protein and procalcitonin

BMC infectious diseases, 2021-09, Vol.21 (1), p.1-988, Article 988

2021

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vital_sqi: A Python package for physiological signal quality control

Frontiers in physiology, 2022-11, Vol.13, p.1020458-1020458

2022

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Supervised learning for infection risk inference using pathology data

BMC medical informatics and decision making, 2017-12, Vol.17 (1), p.168-168, Article 168

2017

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Mapping patient pathways and understanding clinical decision-making in dengue management to inform the development of digital health tools

BMC medical informatics and decision making, 2023-02, Vol.23 (1), p.24-9, Article 24

2023

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Machine learning and synthetic outcome estimation for individualised antimicrobial cessation

Frontiers in digital health, 2022-11, Vol.4, p.997219

2022

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Predicting deterioration in dengue using a low cost wearable for continuous clinical monitoring

NPJ digital medicine, 2024-11, Vol.7 (1), p.306-8, Article 306

2024

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Resistance Trend Estimation Using Regression Analysis to Enhance Antimicrobial Surveillance: A Multi-Centre Study in London 2009–2016

Antibiotics (Basel), 2021-10, Vol.10 (10), p.1267

2021

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The Diagnosis of Dengue in Patients Presenting With Acute Febrile Illness Using Supervised Machine Learning and Impact of Seasonality

Frontiers in digital health, 2022-03, Vol.4, p.849641

2022

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Learning meaningful latent space representations for patient risk stratification: Model development and validation for dengue and other acute febrile illness

Frontiers in digital health, 2023-02, Vol.5, p.1057467-1057467

2023

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Development of a patient-centred intervention to improve knowledge and understanding of antibiotic therapy in secondary care

Antimicrobial resistance & infection control, 2018-03, Vol.7 (1), p.43-43, Article 43

2018

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Applied machine learning for the risk-stratification and clinical decision support of hospitalised patients with dengue in Vietnam

PLOS digital health, 2022-01, Vol.1 (1), p.e0000005

2022

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A Real-world Evaluation of a Case-based Reasoning Algorithm to Support Antimicrobial Prescribing Decisions in Acute Care

Clinical infectious diseases, 2021-06, Vol.72 (12), p.2103-2111

2021

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Informing antimicrobial management in the context of COVID-19: understanding the longitudinal dynamics of C-reactive protein and procalcitonin

BMC infectious diseases, 2021-09, Vol.21 (1), p.1-932, Article 932

2021

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Applying artificial intelligence and digital health technologies, Viet Nam

Bulletin of the World Health Organization, 2023-07, Vol.101 (7), p.487-492

2023

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Mapping the decision pathways of acute infection management in secondary care among UK medical physicians: a qualitative study

BMC medicine, 2016-12, Vol.14 (1), p.208, Article 208

2016

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Clinical benefit of AI-assisted lung ultrasound in a resource-limited intensive care unit

Critical care (London, England), 2023-07, Vol.27 (1), p.257-257, Article 257

2023

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Computer-aided prognosis of tuberculous meningitis combining imaging and non-imaging data

Scientific reports, 2024-07, Vol.14 (1), p.17581-13, Article 17581

2024

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Clinical evaluation of AI-assisted muscle ultrasound for monitoring muscle wasting in ICU patients

Scientific reports, 2024-06, Vol.14 (1), p.14798-9, Article 14798

2024

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Digital Health Policy and Programs for Hospital Care in Vietnam: Scoping Review

Journal of medical Internet research, 2022-02, Vol.24 (2), p.e32392-e32392

2022

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Towards a machine-learning assisted non-invasive classification of dengue severity using wearable PPG data: a prospective clinical study

EBioMedicine, 2024-06, Vol.104, p.105164, Article 105164

2024

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Supervised machine learning to support the diagnosis of bacterial infection in the context of COVID-19

JAC-antimicrobial resistance, 2021-03, Vol.3 (1), p.dlab002-dlab002

2021

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Towards a machine-learning assisted non-invasive classification of dengue severity using wearable PPG data: a prospective clinical studyResearch in context

EBioMedicine, 2024-06, Vol.104, p.105164

2024

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Patient engagement with infection management in secondary care: a qualitative investigation of current experiences

BMJ open, 2016-10, Vol.6 (10), p.e011040-e011040

2016

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Predicting Quality of Overnight Glycaemic Control in Type 1 Diabetes Using Binary Classifiers

Applying artificial intelligence and digital health technologies, Viet Nam

Correction to: Informing antimicrobial management in the context of COVID-19: understanding the longitudinal dynamics of C-reactive protein and procalcitonin

vital_sqi: A Python package for physiological signal quality control

Supervised learning for infection risk inference using pathology data

Mapping patient pathways and understanding clinical decision-making in dengue management to inform the development of digital health tools

Machine learning and synthetic outcome estimation for individualised antimicrobial cessation

Predicting deterioration in dengue using a low cost wearable for continuous clinical monitoring

Resistance Trend Estimation Using Regression Analysis to Enhance Antimicrobial Surveillance: A Multi-Centre Study in London 2009–2016

The Diagnosis of Dengue in Patients Presenting With Acute Febrile Illness Using Supervised Machine Learning and Impact of Seasonality

Learning meaningful latent space representations for patient risk stratification: Model development and validation for dengue and other acute febrile illness

Development of a patient-centred intervention to improve knowledge and understanding of antibiotic therapy in secondary care

Applied machine learning for the risk-stratification and clinical decision support of hospitalised patients with dengue in Vietnam

A Real-world Evaluation of a Case-based Reasoning Algorithm to Support Antimicrobial Prescribing Decisions in Acute Care

Informing antimicrobial management in the context of COVID-19: understanding the longitudinal dynamics of C-reactive protein and procalcitonin

Applying artificial intelligence and digital health technologies, Viet Nam

Mapping the decision pathways of acute infection management in secondary care among UK medical physicians: a qualitative study

Clinical benefit of AI-assisted lung ultrasound in a resource-limited intensive care unit

Computer-aided prognosis of tuberculous meningitis combining imaging and non-imaging data

Clinical evaluation of AI-assisted muscle ultrasound for monitoring muscle wasting in ICU patients

Digital Health Policy and Programs for Hospital Care in Vietnam: Scoping Review

Towards a machine-learning assisted non-invasive classification of dengue severity using wearable PPG data: a prospective clinical study

Supervised machine learning to support the diagnosis of bacterial infection in the context of COVID-19

Towards a machine-learning assisted non-invasive classification of dengue severity using wearable PPG data: a prospective clinical studyResearch in context

Patient engagement with infection management in secondary care: a qualitative investigation of current experiences

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