The Lancet Digital Health in conversation with
Ein Podcast von The Lancet Group
31 Folgen
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Hugo Aerts and Ray Mak on FaceAge
Vom: 8.5.2025 -
Mohamed Omar on pathology and generative AI
Vom: 27.8.2024 -
Judith Bonnes on detecting cardiac arrest using wearable technology
Vom: 7.3.2024 -
Andrew Soltan on federated learning systems
Vom: 24.1.2024 -
Mamatha Bhat on deep learning for predicting liver graft fibrosis
Vom: 23.5.2023 -
Xiao Liu on AI-based clinical research studies
Vom: 21.3.2023 -
Ashleigh Myall on predicting hospital-onset COVID-19 infections
Vom: 19.7.2022 -
Reading race
Vom: 11.5.2022 -
Caroline Figueroa on the need for feminist intersectionality in digital health
Vom: 26.7.2021 -
Mihaela van der Schaar and Vincent J Gnanapragasam on predicting mortality in prostate cancer
Vom: 15.2.2021 -
Deepti Gurdasani on health data, AI, and COVID-19
Vom: 2.12.2020 -
Vence Bonham on diversity and impact in genomic research
Vom: 2.12.2020 -
Maimuna S Majumder on COVID-19 misinformation online
Vom: 26.10.2020 -
Sara Gerke and Timo Minssen on AI in healthcare
Vom: 23.6.2020 -
Identifying and measuring brain lesions in patients with traumatic brain injury
Vom: 14.5.2020 -
The Lancet Digital Health turns one
Vom: 29.4.2020 -
A real-time dashboard of clinical trials for COVID-19
Vom: 24.4.2020 -
Opportunistic value of fully automated CT-based biomarkers
Vom: 4.3.2020 -
Predicting the added benefit of adjuvant chemotherapy
Vom: 19.2.2020 -
Using Fitbit data to predict flu outbreaks
Vom: 16.1.2020
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.
