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Annarita Fanizzi

universita san raffaele
H指数:26
被引数:2,027

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Preoperative prediction model of lymphovascular space invasion in endometrial cancer using ultrasound indicators and foundation model-based features: a multicenter study

子宫内膜癌淋巴血管间隙浸润的术前预测模型:基于超声指标和基础模型特征的多中心研究

2026-09-150
OAAI
Nal-IRI (liposomal irinotecan) plus 5-fluorouracil and leucovorin versus 5-fluorouracil for metastatic pancreatic ductal adenocarcinoma following gemcitabine-based therapy. A systematic review and meta-analysis of randomized controlled trials

Nal-IRI(脂质体伊立替康)联合5-氟尿嘧啶和亚叶酸钙与5-氟尿嘧啶相比,用于在吉西他滨治疗后转移性胰腺导管腺癌的疗效:一项随机对照试验的系统评价和Meta分析

2026-03-310
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Machine and Deep Learning on Radiomic Features from Contrast-Enhanced Mammography and Dynamic Contrast-Enhanced Magnetic Resonance Imaging for Breast Cancer Characterization

机器和深度学习来自对比增强乳腺x线摄影和动态对比增强磁共振成像的影像组学特征,用于乳腺癌表征

2026-03-030
OAAI
Bone metastases in advanced urothelial carcinoma patients receiving enfortumab vedotin: A Real-World study from the ARON-2EV project

接受恩沃利单抗维多汀治疗的局部晚期或转移性尿路上皮癌患者的骨转移:ARON-2EV项目真实世界研究

2025-12-290
OAAI
Gender Medicine in Computed Tomography Radiomics Analysis to Predict Disease Progression in Liver Respectable Colorectal Cancer Patients

基于计算机断层扫描放射组学分析的性别医学在预测可切除结直肠癌患者疾病进展中的应用

2025-09-040
OAAI
Validation of machine learning-based models to predict and explain the risk of ovarian cancer: a multicentric study on BRCA-mutated patients undergoing risk-reducing salpingo-oophorectomy

基于机器学习模型的卵巢癌风险预测与解释验证:一项关于接受风险降低性输卵管卵巢切除术的BRCA突变患者的多中心研究

2025-04-150
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Explainable machine learning for predicting recurrence-free survival in endometrial carcinosarcoma patients

可解释的机器学习预测子宫内膜癌肉瘤患者的无复发生存率

2024-12-060
OAAI
Robust machine learning challenge: An AIFM multicentric competition to spread knowledge, identify common pitfalls and recommend best practice
2024-11-012
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Explainable prediction model for the human papillomavirus status in patients with oropharyngeal squamous cell carcinoma using CNN on CT images

在CT图像上使用CNN对口咽鳞状细胞癌患者的人乳头瘤病毒状态进行可解释的预测模型

2024-06-205
OAAI
A multicentric study of radiomics and artificial intelligence analysis on contrast-enhanced mammography to identify different histotypes of breast cancer

乳腺x线造影的影像组学和人工智能分析的多中心研究,以识别乳腺癌的不同组织类型

2024-05-172
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Radiomics and artificial intelligence analysis by T2-weighted imaging and dynamic contrast-enhanced magnetic resonance imaging to predict Breast Cancer Histological Outcome

通过T2-weighted成像和动态对比增强磁共振成像进行放射组学和人工智能分析,以预测乳腺癌的组织学结果

2023-10-0610
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