OXFORD, England & TORONTO--(BUSINESS WIRE)--Oxford Cancer Analytics (OXcan), the medtech company developing blood tests for early cancer detection using advanced proteomics and AI, today announced it ...
A new study published in JCO Clinical Cancer Informatics demonstrates that machine learning models incorporating patient-reported outcomes and wearable sensor data can predict which patients with ...
Cancer diagnoses traditionally require invasive or labor-intensive procedures such as tissue biopsies. Researchers at the Ludwig-Maximilians-Universität München (LMU) have now reported on a method ...
Survival outcomes in non-small cell lung cancer: Real-world analysis of immunotherapy era vs pre-immunotherapy era, with insights into treatment settings, racial disparities, and socioeconomic impacts ...
As patients with lung cancer live longer, the risk of long-term cardiac side effects of radiation therapy has been increasing, despite advances that reduce the radiation dose to the heart. New ...
Three hundred and ninety-eight patients with ctDNA data (206 in training and 192 in validation) were analyzed. Our models outperformed existing workflow using conventional temporal ctDNA features, ...
A groundbreaking study led by USC Assistant Professor of Computer Science Ruishan Liu has uncovered how specific genetic mutations influence cancer treatment outcomes-insights that could help doctors ...
Please provide your email address to receive an email when new articles are posted on . Machine learning models can predict which patients receiving lung cancer therapy may need urgent care visits.
BEIJING, 4 February (BelTA - China Daily) - A Chinese research team has developed the world's first blood-based diagnostic kit that can tell whether lung nodules are benign or cancerous, including ...
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