James M Dolezal
Overview
Explore the profile of James M Dolezal including associated specialties, affiliations and a list of published articles.
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Articles
18
Citations
271
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0
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Recent Articles
1.
Hieromnimon H, Trzcinska A, Wen F, Howard F, Dolezal J, Dyer E, et al.
Oral Oncol
. 2025 Mar;
163:107207.
PMID: 40043423
Objectives: Human papillomavirus (HPV) influences the pathobiology of Head and Neck Squamous Cell Carcinomas (HSNCCs). While deep learning shows promise in detecting HPV from hematoxylin and eosin (H&E) stained slides,...
2.
Choudhury D, Dolezal J, Dyer E, Kochanny S, Ramesh S, Howard F, et al.
EBioMedicine
. 2024 Aug;
107:105276.
PMID: 39197222
Background: Deployment and access to state-of-the-art precision medicine technologies remains a fundamental challenge in providing equitable global cancer care in low-resource settings. The expansion of digital pathology in recent years...
3.
Dolezal J, Kochanny S, Dyer E, Ramesh S, Srisuwananukorn A, Sacco M, et al.
BMC Bioinformatics
. 2024 Mar;
25(1):134.
PMID: 38539070
Deep learning methods have emerged as powerful tools for analyzing histopathological images, but current methods are often specialized for specific domains and software environments, and few open-source options exist for...
4.
Hines J, Cameron R, Esposito A, Kim L, Porcu L, Nuccio A, et al.
J Thorac Oncol
. 2024 Mar;
19(7):1108-1116.
PMID: 38461929
Introduction: Controversy remains as to whether pathologic complete response (pCR) and major pathologic response (MPR) represent surrogate end points for event-free survival (EFS) and overall survival (OS) in neoadjuvant trials...
5.
Cameron R, Hines J, Torri V, Porcu L, Donington J, Bestvina C, et al.
Ther Adv Med Oncol
. 2023 Sep;
15:17588359231198446.
PMID: 37720499
Numerous clinical trials investigating neoadjuvant immune checkpoint inhibitors (ICI) have been performed over the last 5 years. As the number of neoadjuvant trials increases, attention must be paid to identifying...
6.
Dolezal J, Wolk R, Hieromnimon H, Howard F, Srisuwananukorn A, Karpeyev D, et al.
NPJ Precis Oncol
. 2023 May;
7(1):49.
PMID: 37248379
Artificial intelligence methods including deep neural networks (DNN) can provide rapid molecular classification of tumors from routine histology with accuracy that matches or exceeds human pathologists. Discerning how neural networks...
7.
Partin A, Brettin T, Zhu Y, Dolezal J, Kochanny S, Pearson A, et al.
Front Med (Lausanne)
. 2023 Mar;
10:1058919.
PMID: 36960342
Patient-derived xenografts (PDXs) are an appealing platform for preclinical drug studies. A primary challenge in modeling drug response prediction (DRP) with PDXs and neural networks (NNs) is the limited number...
8.
Ramesh S, Dolezal J, Pearson A
Surg Pathol Clin
. 2023 Feb;
16(1):167-176.
PMID: 36739164
Machine learning methods have been growing in prominence across all areas of medicine. In pathology, recent advances in deep learning (DL) have enabled computational analysis of histological samples, aiding in...
9.
Dolezal J, Srisuwananukorn A, Karpeyev D, Ramesh S, Kochanny S, Cody B, et al.
Nat Commun
. 2022 Nov;
13(1):6572.
PMID: 36323656
A model's ability to express its own predictive uncertainty is an essential attribute for maintaining clinical user confidence as computational biomarkers are deployed into real-world medical settings. In the domain...
10.
Jackson L, Kulkarni S, Wang H, Lu J, Dolezal J, Bharathi S, et al.
Cancer Res
. 2022 Mar;
82(5):944.
PMID: 35247896
No abstract available.