This predictive model built on readily acquired clinical data provides encouraging results for the detection of residual disease. External validation and prospective studies implementing the model in ...

Nearly 50 new cancer therapies are approved every year. This is good news. "But for patients and their treating physicians, ...

A 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 ...

We retrospectively identified 111 lesions, divided into training and test sets (n = 78 v 33) with equal class distribution. 3D Slicer was used to segment lesions with a short axis of >10 mm from the ...

AI is rapidly transforming oncology, but many clinicians lack practical tools to evaluate its real-world reliability.

Understanding machine learning modifies cold atmospheric plasma medicine delivery in cancer treatments without being trained on detailed plasma parameters.

With the rapidly evolving world, having digital skills has become one of the most important requirements for both professionals in any field and students. From learning basic computer operations to ...

From using AI to detect diseases to building human-like conversational platforms, the world’s third-largest startup ecosystem is at the very front of this revolution Last year, the Centre launched the ...

An artificial intelligence (AI) deep learning tool that estimates the malignancy risk of lung nodules achieved high cancer detection rates while significantly reducing false-positive results.