Louis J Vaickus
Overview
Explore the profile of Louis J Vaickus including associated specialties, affiliations and a list of published articles.
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47
Citations
522
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Recent Articles
1.
Fatemi M, Lu Y, Diallo A, Srinivasan G, Azher Z, Christensen B, et al.
Brief Bioinform
. 2024 Oct;
25(6).
PMID: 39367648
The application of deep learning to spatial transcriptomics (ST) can reveal relationships between gene expression and tissue architecture. Prior work has demonstrated that inferring gene expression from tissue histomorphology can...
2.
Vaickus L, Kerr D, Velez Torres J, Levy J
Surg Pathol Clin
. 2024 Aug;
17(3):521-531.
PMID: 39129146
The practice of cytopathology has been significantly refined in recent years, largely through the creation of consensus rule sets for the diagnosis of particular specimens (Bethesda, Milan, Paris, and so...
3.
Velez Torres J, Vaickus L, Kerr D
Surg Pathol Clin
. 2024 Aug;
17(3):371-381.
PMID: 39129137
Thyroid cytology is a rapidly evolving field that has seen significant advances in recent years. Its main goal is to accurately diagnose thyroid nodules, differentiate between benign and malignant lesions,...
4.
Levy J, Davis M, Chacko R, Davis M, Fu L, Goel T, et al.
NPJ Precis Oncol
. 2024 Jan;
8(1):2.
PMID: 38172524
Successful treatment of solid cancers relies on complete surgical excision of the tumor either for definitive treatment or before adjuvant therapy. Intraoperative and postoperative radial sectioning, the most common form...
5.
Belikoff B, Vaickus L, Sitkovsky M, Remick D
J Immunol
. 2024 Jan;
212(4):748.
PMID: 38169328
No abstract available.
6.
Srinivasan G, Davis M, LeBoeuf M, Fatemi M, Azher Z, Lu Y, et al.
Pac Symp Biocomput
. 2023 Dec;
29:477-491.
PMID: 38160301
The advent of spatial transcriptomics technologies has heralded a renaissance in research to advance our understanding of the spatial cellular and transcriptional heterogeneity within tissues. Spatial transcriptomics allows investigation of...
7.
Azher Z, Fatemi M, Lu Y, Srinivasan G, Diallo A, Christensen B, et al.
Pac Symp Biocomput
. 2023 Dec;
29:464-476.
PMID: 38160300
Graph-based deep learning has shown great promise in cancer histopathology image analysis by contextualizing complex morphology and structure across whole slide images to make high quality downstream outcome predictions (ex:...
8.
Fatemi M, Lu Y, Diallo A, Srinivasan G, Azher Z, Christensen B, et al.
medRxiv
. 2023 Oct;
PMID: 37873287
The application of deep learning methods to spatial transcriptomics has shown promise in unraveling the complex relationships between gene expression patterns and tissue architecture as they pertain to various pathological...
9.
Fatemi M, Lu Y, Sharma C, Feng E, Azher Z, Diallo A, et al.
medRxiv
. 2023 Oct;
PMID: 37873186
Background: Spatial transcriptomics involves studying the spatial organization of gene expression within tissues, offering insights into the molecular diversity of tumors. While spatial gene expression is commonly amalgamated from 1-10...
10.
Davis M, Srinivasan G, Chacko R, Chen S, Suvarna A, Vaickus L, et al.
Exp Dermatol
. 2023 Oct;
33(1):e14949.
PMID: 37864429
Intraoperative margin analysis is crucial for the successful removal of cutaneous squamous cell carcinomas (cSCC). Artificial intelligence technologies (AI) have previously demonstrated potential for facilitating rapid and complete tumour removal...