Concise summaries of everything published in the latest weekly issue of the New England Journal of Medicine (NEJM). NEJM publishes new medical research findings, review articles, and editorial opinion on topics of importance to biomedical science and clinical practice.
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Artificial Intelligence Tool Predicts Postoperative Radiotherapy Lymphedema
Manage episode 412750793 series 1021077
Indhold leveret af Oncology Times. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af Oncology Times eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.
Artificial intelligence is being harnessed by a team of researchers at Leicester University in the United Kingdom to predict the risk of lymphedema (and potentially other toxicities) from the use of postoperative radiation therapy for breast cancer.
The 2024 European Breast Cancer Conference heard the latest news on an artificial intelligence tool that promises to help cancer clinicians individualize radiotherapy regimens after surgery to minimize toxicity.
Tim Rattay, MBChB, PhD, Associate Professor in Breast Surgery in the Leicester Cancer Research Centre at the University of Leicester and Consultant Breast Surgeon at the University Hospitals of Leicester in the UK, told the conference about his group’s machine-learning algorithm, PRE-ACT (Prediction of Radiotherapy side Effects using explainable AI for patient Communication and Treatment modification), that predicts post-operative lymphedema.
After reporting his research in Milan, Rattay called into the OncTimesTalk studio to give Peter Goodwin the details.
…
continue reading
The 2024 European Breast Cancer Conference heard the latest news on an artificial intelligence tool that promises to help cancer clinicians individualize radiotherapy regimens after surgery to minimize toxicity.
Tim Rattay, MBChB, PhD, Associate Professor in Breast Surgery in the Leicester Cancer Research Centre at the University of Leicester and Consultant Breast Surgeon at the University Hospitals of Leicester in the UK, told the conference about his group’s machine-learning algorithm, PRE-ACT (Prediction of Radiotherapy side Effects using explainable AI for patient Communication and Treatment modification), that predicts post-operative lymphedema.
After reporting his research in Milan, Rattay called into the OncTimesTalk studio to give Peter Goodwin the details.
188 episoder
Manage episode 412750793 series 1021077
Indhold leveret af Oncology Times. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af Oncology Times eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.
Artificial intelligence is being harnessed by a team of researchers at Leicester University in the United Kingdom to predict the risk of lymphedema (and potentially other toxicities) from the use of postoperative radiation therapy for breast cancer.
The 2024 European Breast Cancer Conference heard the latest news on an artificial intelligence tool that promises to help cancer clinicians individualize radiotherapy regimens after surgery to minimize toxicity.
Tim Rattay, MBChB, PhD, Associate Professor in Breast Surgery in the Leicester Cancer Research Centre at the University of Leicester and Consultant Breast Surgeon at the University Hospitals of Leicester in the UK, told the conference about his group’s machine-learning algorithm, PRE-ACT (Prediction of Radiotherapy side Effects using explainable AI for patient Communication and Treatment modification), that predicts post-operative lymphedema.
After reporting his research in Milan, Rattay called into the OncTimesTalk studio to give Peter Goodwin the details.
…
continue reading
The 2024 European Breast Cancer Conference heard the latest news on an artificial intelligence tool that promises to help cancer clinicians individualize radiotherapy regimens after surgery to minimize toxicity.
Tim Rattay, MBChB, PhD, Associate Professor in Breast Surgery in the Leicester Cancer Research Centre at the University of Leicester and Consultant Breast Surgeon at the University Hospitals of Leicester in the UK, told the conference about his group’s machine-learning algorithm, PRE-ACT (Prediction of Radiotherapy side Effects using explainable AI for patient Communication and Treatment modification), that predicts post-operative lymphedema.
After reporting his research in Milan, Rattay called into the OncTimesTalk studio to give Peter Goodwin the details.
188 episoder
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