29 episodes
The Lancet Digital Health in conversation with The Lancet Group
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- Health & Fitness
Rupa Sarkar, Editor-in-Chief, Diana Samuel, Deputy Editor, and Lucy Dunbar, Senior Editor at The Lancet Digital Health, in conversation with the journal’s authors, explore their latest research and its impact on people’s health, healthcare, and health policy.
A monthly audio companion to this open access journal, this podcast covers a broad range of topics, from using machine learning to predict mortality in prostate cancer and the need for feminist intersectionality in digital health, to how algorithms can predict a patient's race from medical data, and more.
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Judith Bonnes on detecting cardiac arrest using wearable technology
Developing and validating an algorithm for automated circulatory arrest detection with wrist-derived photoplethysmography with Judith Bonnes from the Department of Cardiology of the Radboud University Medical Center - Netherlands.
Read the full article:
https://www.thelancet.com/journals/landig/article/PIIS2589-7500(23)00249-2/fulltext?dgcid=buzzsprout_icw_podcast_generic_landig
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Andrew Soltan on federated learning systems
Dr Andrew Soltan joins Dr Lucy Dunbar to discuss the development, testing and deployment of a federated learning system across four UK hospital groups.
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Mamatha Bhat on deep learning for predicting liver graft fibrosis
Dr Mamatha Bhat joins Dr Lucy Dunbar to discuss the development of deep learning algorithms in predicting risk of significant fibrosis after liver transplantation.
Read the full article:
https://www.thelancet.com/journals/landig/article/PIIS2589-7500(23)00068-7/fulltext?dgcid=buzzsprout_icw_podcast_general_landig
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Xiao Liu on AI-based clinical research studies
Xiao Liu joins Diana Samuel to discuss how to improve the reporting of artificial intelligence-based clinical research studies and the representativeness of health datasets.
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Ashleigh Myall on predicting hospital-onset COVID-19 infections
Ashleigh Myall joins Diana Samuel to discuss a new machine-learning framework that integrates dynamic patient-contact networks with patient clinical variables and contextual hospital variables to predict hospital-onset COVID-19 infections.
Read the full article:
Prediction of hospital-onset COVID-19 infections using dynamic networks of patient contact
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Reading race
Judy Gichoya, Leo Celi and Laleh Seyyed-Kalantari join Rupa Sarkar to discuss how algorithms can predict a patient's race from medical data.
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