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J

James M. Dolezal

geisinger cancer institute, danville, pa, usa
H指数:20
被引数:1,651

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Virtual multiplex immunofluorescence identifies lymphocyte subsets predictive of response to neoadjuvant therapy

虚拟多重免疫荧光识别预测新辅助治疗反应的淋巴细胞亚群

2025-10-180
OA
Corrigendum to “Analysis of AI foundation model features decodes the histopathologic landscape of HPV-positive head and neck squamous cell carcinomas”. [Oral Oncol. 163 (2025) 107207]

勘误:“Analysis of AI foundation model features decodes the histopathologic landscape of HPV-positive head and neck squamous cell carcinomas” [Oral Oncol. 163 (2025) 107207]

2025-07-280
PRE
Analysis of AI foundation model features decodes the histopathologic landscape of HPV-positive head and neck squamous cell carcinomas

AI基础模型特征的分析解码了HPV阳性头颈部鳞状细胞癌的组织病理学景观

2025-03-011
PRE
Generative adversarial networks accurately reconstruct pan-cancer histology from pathologic, genomic, and radiographic latent features

生成对抗网络从病理,基因组和影像学潜在特征准确地重建了泛癌症组织学

2024-11-150
OAAI
Artificial intelligence-based morphologic classification and molecular characterization of neuroblastic tumors from digital histopathology
2024-11-080
OAAI
Artificial intelligence for predictive biomarker discovery in immuno-oncology: a systematic review

免疫肿瘤学中预测生物标志物发现的人工智能: 系统综述

2024-01-0138
OAAI
The EU-funded I3LUNG Project: Integrative Science, Intelligent Data Platform for Individualized LUNG Cancer Care With Immunotherapy
2023-06-017
PRE
Deep learning generates synthetic cancer histology for explainability and education

深度学习为可解释性和教育生成合成癌症组织学

2023-05-2916
OAAI
Integration of clinical features and deep learning on pathology for the prediction of breast cancer recurrence assays and risk of recurrence

临床特征与病理学深度学习相结合预测乳腺癌复发检测及复发风险

2023-04-1418
OA
Uncertainty-informed deep learning models enable high-confidence predictions for digital histopathology

基于不确定性的深度学习模型可实现数字组织病理学的高置信度预测

2022-11-0244
OAAI