Observational analysis improves clinical outcomes through ensemble learning in minimally invasive cancer therapy, suggesting enhanced treatment precision.
Combining FEM simulations with supervised learning provides a scalable, data-driven framework for precision MWA. This approach improves predictive reliability, accelerates treatment planning, and enables adaptive, optimized thermal therapies, offering potential for enhanced clinical outcomes in minimally invasive oncological interventions.
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Qiao et al. (2025) studied this question.
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