The Lancet Digital Health in conversation with
Rupa Sarkar, Editor-in-Chief, Diana Samuel, Deputy Editor, Lucy Dunbar, Senior Editor, and Gustavo Monnerat, 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.
Episodes
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.
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https://www.thelancet.com/journals/landig/article/PIIS2589-7500(23)00249-2/fulltext?dgcid=buzzsprout_icw_podcast_generic_landig
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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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Dr Mamatha Bhat joins Dr Lucy Dunbar to discuss the development of deep learning algorithms in predicting risk of significant fibrosis after liver transplantation.
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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 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 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.
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Prediction of hospital-onset COVID-19 infections using dynamic networks of patient contact
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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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Dr Caroline Figueroa and Dr Rupa Sarkar talk about the social and economic fallout from COVID-19 which has further exacerbated gender inequities and the need for a feminist outlook in digital health.
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https://www.thelancet.com/journals/landig/article/PIIS2589-7500(21)00118-7/fulltext
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Mihaela van der Schaar and Vincent J Gnanapragasam join Diana Samuel to discuss a new machine learning-based prognostic model for prediction of 10-year mortality from non-metastatic prostate cancer.
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https://www.thelancet.com/journals/landig/article/PIIS2589-7500(20)30314-9/fulltext
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Vence Bonham joins Diana Samuel to discuss the impact of genomics and precision medicine on health disparities, and the need for greater diversity in genomic research studies.
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Deepti Gurdasani joins Rupa Sarkar to discuss bias and inequalities in health data and artificial intelligence and the impact of COVID-19.
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Maimuna S Majumder joins Diana Samuel to discuss how misinformation on COVID-19 can influence the public’s online search interests, and the potential impact this can have on their health.
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Sara Gerke and Timo Minssen join Diana Samuel to discuss the European Commission’s white paper on artificial intelligence (published in February 2020), and the challenges of implementing the outlined approach in healthcare.
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Virginia Newcombe and Miguel Monteiro join Rupa Sarkar to discuss their work on a deep learning algorithm to quantify and distinguish between brain lesion types in head CT images of patients with traumatic brain injury.
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To celebrate the journal’s anniversary, the Editors and International Advisory Board members of The Lancet Digital Health reflect on the major digital advances transforming medicine and healthcare in the past year and the role of digital health in mitigating the COVID-19 pandemic.
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Dr. Louis Dron and Dr Samuel talk about an online dashboard that collates all clinical trials investigating treatments for COVID-19, and discuss the broader implications of its use.
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Prof Perry Pickhardt and Diana Samuel talk about the prognostic abilities of a panel of automated CT-based biomarkers for predicting future risk of serious adverse events.
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Prof Anant Madabhushi and Dr Samuel talk about the utility of a radiomic risk score applied to CT scans of patients with early stage non-small cell lung carcinoma.
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Dr Jennifer Radin and Dr Rupa Sarkar talk about using heart rate and sleep data from Fitbit devices to predict influenza-like illness activity in the US.
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Professor Helen Christensen and Dr Rupa Sarkar talk about evidence for effective digital interventions to support people at risk of suicide.
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A machine learning model for early identification of individuals with familial hypercholesterolaemia
Katherine Wilemon and Kelly Myers join Christina Wayman from The Lancet Digital Health to discuss the potential of precision screening of individuals with familial hypercholesterolaemia.
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