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Can speech reveal the progression of a neurodegenerative disease? In this episode of In Conversation With…, Evgenia Koutsouki, Senior Editor at The Lancet Digital Health, speaks with Professor Anne-Catherine Bachoud-Lévi about her team's latest research on NDSNet, a deep learning model that uses speech recordings to estimate clinical status in people with Huntington's disease.

They discuss the growing role of speech-based digital biomarkers in neurology, how AI can help monitor disease progression, and why subtle changes in speech may provide valuable insights into underlying brain changes before they become apparent on conventional clinical assessments. The conversation also explores the challenges of validating AI tools in real-world settings and the future of remote, scalable monitoring for Huntington's disease and other neurodegenerative disorders. Tune in to listen to Professor Bachoud-Lévi’s insights on how speech, digital health technologies, and machine learning are reshaping the way we assess and monitor neurological disease.

Click here to read the full article:

https://www.thelancet.com/journals/landig/article/PIIS2589-7500(26)00048-8/fulltext

Ruben Hemelings and Leo Schmetterer from the Singapore Eye Research Institute join Lucy Dunbar to discuss G-PROG, a deep learning tool that predicts glaucoma progression from fundus photographs.

Click here to read the full article:

https://www.thelancet.com/journals/landig/article/PIIS2589-7500(26)00055-5/fulltext

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

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

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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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.

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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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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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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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