The Lancet Digital Health editors, in conversation with the journal’s authors, explore their latest research and its impact on people’s health, health care, 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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16 recent
April 30, 2026Episode 322 min
Shaoxu Wu on panCAM (Mandarin Version)
Dr Shaoxu Wu from Sun Yat-sen Memorial Hospital joins Dr Shangrong Han to discuss PanCAM, an AI pathology model that detects lymph-node metastasis across diverse cancers with robust performance.
Click here to read the article: https://www.thelancet.com/journals/landig/article/PIIS2589-7500(25)00143-8/fulltext
April 17, 2026Episode 218 min
Shaoxu Wu on panCAM
Dr Shaoxu Wu from Sun Yat-sen Memorial Hospital joins Dr Shangrong Han to discuss PanCAM, an AI pathology model that detects lymph-node metastasis across diverse cancers with robust performance.
Click here to read the full article:
https://www.thelancet.com/journals/landig/article/PIIS2589-7500(25)00143-8/fulltext
May 8, 202522 min
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 with cancer.
Read the full article:
https://www.thelancet.com/journals/landig/article/PIIS2589-7500(25)00042-1/fulltext?dgcid=buzzsprout_icw_podcast_01-05-25_landig
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August 27, 202418 min
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 considerations, democratisation of knowledge, and future advancements in the field.
Read the full article:
https://www.thelancet.com/journals/landig/article/PIIS2589-7500(24)00114-6/fulltext?dgcid=buzzsprout_icw_podcast_generic_landig
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March 7, 202417 min
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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January 24, 202414 min
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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May 23, 202320 min
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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March 21, 202321 min
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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July 19, 202218 min
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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May 11, 202231 min
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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