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Thomas E. Yankeelov

the university of texas at austin

H指数:61

被引数:1.3万

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An MRI-informed poromechanical model for organ-scale prediction of glioma growth

基于MRI信息的孔弹力模型用于器官尺度的胶质瘤生长预测

Computer Methods in Applied Mechanics and Engineering

IF7.3

2026-08-250

OAAI

TumorTwin: a Python framework for patient-specific digital twins in oncology

TumorTwin：一个用于肿瘤学中患者特异性数字孪生的Python框架

BMC Medical Informatics and Decision Making

IF3.8

2026-05-110

OAAI

Predicting head and neck cancer response to radiotherapy using mathematical modeling of MRI-based habitats

基于MRI栖息地数学建模预测头颈癌对放射治疗反应

npj Precision Oncology

IF8

2026-04-160

OA

Predictive Digital Twins with Quantified Uncertainty for Patient-Specific Decision Making in Oncology

具有量化不确定性的预测数字孪生，用于肿瘤学中的患者特异性决策制定

Journal of Computational Physics

IF3.8

2026-04-120

PRE

Modeling tumor dynamics and predicting response to therapies in a murine pancreatic cancer model

建模肿瘤动力学并预测对疗法反应的小鼠胰腺癌模型

npj Systems Biology and Applications

IF3.5

2025-11-040

OAAI

Investigating the Limits of Predictability of Magnetic Resonance Imaging-Based Mathematical Models of Tumor Growth

探究基于磁共振成像的肿瘤生长数学模型的可预测性极限

Cancers 2025, Vol. 17, Page 3361

IF0

2025-10-180

OAAI

Employing nullclines to balance treatment efficacy and neurotoxicity for sustained tumor control

采用零等斜线平衡治疗效果和神经毒性以实现持续肿瘤控制

MATHEMATICAL BIOSCIENCES

IF1.8

2025-09-010

PRE

Personalizing neoadjuvant chemotherapy regimens for triple-negative breast cancer using a biology-based digital twin

基于生物学模型的数字孪生技术个性化三阴性乳腺癌新辅助化疗方案

NPJ SYSTEMS BIOLOGY AND APPLICATIONS

IF3.5

2025-05-230

OA

Identifiability and model selection frameworks for models of high-grade glioma response to chemoradiation

PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES

IF3.7

2025-04-020

OA

Patient-Specific, Mechanistic Models of Tumor Growth Incorporating Artificial Intelligence and Big Data

结合人工智能和大数据的肿瘤生长的患者特异性机械模型

ANNUAL REVIEW OF BIOMEDICAL ENGINEERING

IF9.6

2024-07-032

OA

Optimizing therapeutic regimens via digital twins to improve triple negative breast cancer response to neoadjuvant therapy

CANCER RESEARCH

IF16.6

2024-05-020

PRE

Integrating mechanism-based and data-driven modeling to predict the response of triple negative breast cancer to therapy

CANCER RESEARCH

IF16.6

2024-05-020

PRE

Personalized MRI-informed forecasting of prostate cancer progression during active surveillance

CANCER RESEARCH

IF16.6

2024-03-220

PRE

Toward mechanistic medical digital twins: some use cases in immunology

走向机械医学数字双胞胎: 免疫学中的一些用例

FRONTIERS IN DIGITAL HEALTH

IF3.8

2024-03-078

OAAI

A mathematical model for predicting the spatiotemporal response of breast cancer cells treated with doxorubicin

CANCER BIOLOGY & THERAPY

IF4.6

2024-02-272

OAAI

Forum on immune digital twins: a meeting report

NPJ SYSTEMS BIOLOGY AND APPLICATIONS

IF3.5

2024-02-164

OAAI

Breast Multiparametric MRI for Prediction of Neoadjuvant Chemotherapy Response in Breast Cancer: The BMMR2 Challenge

乳腺多参数MRI预测乳腺癌新辅助化疗反应: BMMR2挑战

RADIOLOGY-IMAGING CANCER

IF6.3

2024-01-017

OA

Li, Wen; Partridge, Savannah C.; Newitt, David C.; Steingrimsson, Jon; Marques, Helga S.; Bolan, Patrick J.; Hirano, Michael; Bearce, Benjamin Aaron; Kalpathy-Cramer, Jayashree; Boss, Michael A.; Teng, Xinzhi; Zhang, Jiang; Cai, Jing; Kontos, Despina; Cohen, Eric A.; Mankowski, Walter C.; Liu, Michael; Ha, Richard; Pellicer-Valero, Oscar J.; Maier-Hein, Klaus; Rabinovici-Cohen, Simona; Tlusty, Tal; Ozery-Flato, Michal; Parekh, Vishwa S.; Jacobs, Michael A.; Yan, Ran; Sung, Kyunghyun; Kazerouni, Anum S.; Dicarlo, Julie C.; Yankeelov, Thomas E.; Chenevert, Thomas L.; Hylton, Nola M.

Predictive digital twin for optimizing patient-specific radiotherapy regimens under uncertainty in high-grade gliomas

预测性数字双胞胎可在不确定的情况下优化高级别神经胶质瘤的患者特异性放疗方案

FRONTIERS IN ARTIFICIAL INTELLIGENCE

IF4.7

2023-10-1120

OAAI

Bayesian Inference of Tissue Heterogeneity for Individualized Prediction of Glioma Growth

IEEE TRANSACTIONS ON MEDICAL IMAGING

IF9.8

2023-10-012

OA

A global sensitivity analysis of a mechanistic model of neoadjuvant chemotherapy for triple negative breast cancer constrained by in vitro and in vivo imaging data

ENGINEERING WITH COMPUTERS

IF4.9

2023-08-071

OAAI