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
14 episodes
Hugo Aerts and Ray Mak on FaceAge
Hugo Aerts and Ray Mak from Mass General Brigham join Lucy Dunbar to discuss FaceAge, a deep learning tool that estimates biological age from simple face photographs, and its implications in aiding clinicians in predicting prognoses for people ...
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22:30
Mohamed Omar on pathology and generative AI
Mohamed Omar joins The Lancet Digital Health to discuss pathology and generative AI from a Digital Health Perspective. We explore expert journeys, AI applications in diagnostics, GPT-4's role, integration challenges, ethical considerat...
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18:24
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 t...
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17:22
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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14:18
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:
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20:16
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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21:41
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.<...
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18:40
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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31:41
Caroline Figueroa on the need for feminist intersectionality in digital health
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. Read the full article:https...
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13:16
Mihaela van der Schaar and Vincent J Gnanapragasam on predicting mortality in prostate cancer
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.Read full article:https://www.thel...
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20:44
Vence Bonham on diversity and impact in genomic research
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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8:08
Deepti Gurdasani on health data, AI, and COVID-19
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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24:28