Machine Learning and Radiomics of Bone Scintigraphy: Their Role in Predicting Recurrence of Localized or Locally Advanced Prostate Cancer.
Yu-De WangChi-Ping HuangYou-Rong YangHsi-Chin WuYu-Ju HsuYi-Chun YehPei-Chun YehKuo-Chen WuChia-Hung KaoPublished in: Diagnostics (Basel, Switzerland) (2023)
The study showed that ML based on clinical features and radiomics features of BS improves the prediction of PCa recurrence after initial treatment. These findings highlight the added value of ML techniques for risk classification in PCa based on clinical features and radiomics features of BS.
Keyphrases
- machine learning
- prostate cancer
- lymph node metastasis
- locally advanced
- contrast enhanced
- squamous cell carcinoma
- deep learning
- radical prostatectomy
- neoadjuvant chemotherapy
- artificial intelligence
- rectal cancer
- big data
- computed tomography
- pet ct
- magnetic resonance
- free survival
- body composition
- combination therapy
- postmenopausal women