Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Explainable Machine Learning Model to Predict Overall Survival in Patients Treated With Palliative Radiotherapy for Bone Metastases
3
Zitationen
10
Autoren
2024
Jahr
Abstract
An explainable ML approach can provide a reliable prediction of 1-year survival after RT in patients with advanced cancer. The implementation of SHAP analysis provides an intelligible explanation of individualized risk prediction, enabling oncologists to identify the best strategy for patient stratification and treatment selection.
Ähnliche Arbeiten
Early Palliative Care for Patients with Metastatic Non–Small-Cell Lung Cancer
2010 · 7.345 Zit.
Tolerance of normal tissue to therapeutic irradiation
1991 · 4.457 Zit.
Stereotactic Body Radiation Therapy for Inoperable Early Stage Lung Cancer
2010 · 2.501 Zit.
Clinical Features of Metastatic Bone Disease and Risk of Skeletal Morbidity
2006 · 2.452 Zit.
Whole brain radiation therapy with or without stereotactic radiosurgery boost for patients with one to three brain metastases: phase III results of the RTOG 9508 randomised trial
2004 · 2.419 Zit.