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Based on findings from:
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Plasma signals of lung tumor promotion for molecular cancer prevention
Tej Pandya et al.. Cell, 2026.
DOI: 10.1016/j.cell.2026.05.005
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GE HealthCare receives FDA 510(k) clearance for MIM Contour ProtégéAI+ 2.0, advancing AI-enabled radiation therapy planning with expanded clinical capabilities
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plasmaCHORD: A Machine Learning Approach to Distinguish Clonal Hematopoiesis–Derived Variants in Liquid Biopsies from Patients with Solid Tumors
Jenna Canzoniero, et al.. Clinical Cancer Research, 2026.
DOI: 10.1158/1078-0432.CCR-25-0976
Weekly News Brief: June 15–19, 2026
To catch up on all of the news from this past week, listen to our weekly news brief for the week of June 15–19, 2026.
This week’s brief covers a blood protein signature that predicts lung cancer risk in advance of diagnosis, an FDA clearance for AI-powered auto-contouring software, and a machine learning model that determines the origin of variants found in liquid biopsies.
To learn more about machine learning–driven proteomics for lung cancer prevention, read "Machine Learning–Derived Plasma Protein Signature May Enable Lung Cancer Prediction Years Before Diagnosis," or see the source report in Cell.
For more information on GE HealthCare's MIM Contour ProtégéAI+ 2.0, read "Auto-Contouring Software for Radiation Oncology Receives FDA 510(k) Clearance," or see the press release.
To learn more about plasmaCHORD, read "Machine Learning Model Reduces Misinterpretation of Variants By Liquid Biopsies," or see the source report in Clinical Cancer Research.
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.