This video is entirely AI generated and does not replicate any original material. It should not be considered a substitute for authentic sources. For complete context and techniques, viewers are encouraged to refer to the original content.
Based on findings from:
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A Bayesian framework for longitudinal EHR and genetic discovery
Sarah Urbut, et al.. Nature, 2026.
DOI: 10.1038/s41586-026-10780-5
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Jiro Personalizes ASCO Journals and Guideline Content for Every Oncologist
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Tumour cell density quantified by artificial intelligence is associated with differential benefit from irinotecan-based chemo-radiotherapy in locally advanced rectal cancer: a post-hoc study of the phase 3 ARISTOTLE trial
Zhuoyan Shen, et al.. eBioMedicine, 2026.
DOI: 10.1016/j.ebiom.2026.106397
Weekly News Brief: August 17–21, 2026
To catch up on all of the news from this past week, listen to our weekly news brief for the week of August 17–21, 2026.
This week’s brief covers a Bayesian machine learning model that predicts risk across 348 diseases from health records and genetics, ASCO evidence integrated into Jiro’s practice intelligence platform, and an AI-based tumor cell density measure that identifies which patients with rectal cancer are likely to benefit from intensified neoadjuvant chemoradiotherapy.
To learn more about ALADYNOULLI, read "Bayesian Framework Integrates Health Records and Genetics to Predict Risk for Multiple Diseases" or see the source report in Nature.
For more information on Jiro's platform, read "ASCO Clinical Evidence Incorporated Into Jiro’s Practice Intelligence Platform," or see the press release.
To learn more about AI-derived tumor cell density measures, read "Tumor Cell Density Model May Guide Intensified Neoadjuvant Chemoradiotherapy Use in Locally Advanced Rectal Cancer," or see the source report in eBioMedicine.
Disclaimer: This newscast was generated with the assistance of AI tools and avatars. All content is reviewed and approved by the editorial staff of ASCO AI in Oncology. Contact us with any questions.
The ideas and opinions expressed in ASCO AI in Oncology do not necessarily reflect those of Conexiant or ASCO. The mention of any company, product, service, or therapy should not be construed as an endorsement of any kind. Conexiant and ASCO assume no responsibility for any injury or damage to persons or property arising out of or related to any use of material contained in this publication or to any errors or omissions.