AIMC Topic: Neoplasm, Residual
Clear Filters Showing 21 to 30 of 30 articles
Re: Accurate Quantification of Residual Cancer Cells in Pelvic Washing Reveals Association with Cancer Recurrence following Robot-Assisted Radical Cystectomy.
The Journal of urology
Aug 8, 2019
Automated Flow Cytometric MRD Assessment in Childhood Acute B- Lymphoblastic Leukemia Using Supervised Machine Learning.
Cytometry. Part A : the journal of the International Society for Analytical Cytology
Jul 7, 2019
Minimal residual disease (MRD) as measured by multiparameter flow cytometry (FCM) is an independent and strong prognostic factor in B-cell acute lymphoblastic leukemia (B-ALL). However, reliable flow cytometric detection of MRD strongly depends on op...
Clinically validated machine learning algorithm for detecting residual diseases with multicolor flow cytometry analysis in acute myeloid leukemia and myelodysplastic syndrome.
EBioMedicine
Oct 22, 2018
BACKGROUND: Multicolor flow cytometry (MFC) analysis is widely used to identify minimal residual disease (MRD) after treatment for acute myeloid leukemia (AML) and myelodysplastic syndrome (MDS). However, current manual interpretation suffers from dr...
Artificial intelligence weights the importance of factors predicting complete cytoreduction at secondary cytoreductive surgery for recurrent ovarian cancer.
Journal of gynecologic oncology
Apr 23, 2018
OBJECTIVE: Accumulating evidence support that complete cytoreduction (CC) at the time of secondary cytoreductive surgery (SCS) improves survival in patients affected by recurrent ovarian cancer (ROC). Here, we aimed to determine whether artificial in...
Sensitive detection of rare disease-associated cell subsets via representation learning.
Nature communications
Apr 6, 2017
Rare cell populations play a pivotal role in the initiation and progression of diseases such as cancer. However, the identification of such subpopulations remains a difficult task. This work describes CellCnn, a representation learning approach to de...
Monocytes
Signal Transduction
Acquired Immunodeficiency Syndrome
Survival Analysis
Killer Cells, Natural
Cytomegalovirus Infections
Supervised Machine Learning
Neural Networks, Computer
Cytokines
Prognosis
Single-Cell Analysis
Leukemia
Humans
Immunologic Memory
T-Lymphocyte Subsets
Rare Diseases
Neoplasm, Residual
[Value of the deep learning automated quantification of tumor-stroma ratio in predicting efficacy and prognosis of neoadjuvant therapy for breast cancer based on residual cancer burden grading].
Zhonghua bing li xue za zhi = Chinese journal of pathology
Jan 8, 2025
To investigate the prognostic value of deep learning-based automated quantification of tumor-stroma ratio (TSR) in patients undergoing neoadjuvant therapy (NAT) for breast cancer. Specimens were collected from 209 breast cancer patients who receive...
Automated analysis of acute myeloid leukemia minimal residual disease using a support vector machine.
Oncotarget
Nov 1, 2016
We investigated the ability of support vector machines (SVM) to analyze minimal residual disease (MRD) in flow cytometry data from patients with acute myeloid leukemia (AML) automatically, objectively and standardly. The initial disease data and MRD ...
Impact of Positive Surgical Margins after Radical Prostatectomy on Disease Progression and Adjuvant Treatment in Pathologically Localized Prostate Cancer.
Collegium antropologicum
Sep 1, 2015
The aim of our study was to evaluate the impact of margin positivity in clinically and pathologically localized prostate cancer (pT2) after radical prostatectomy on biochemical recurrence and time to adjuvant treatment. We analyzed data from 371 pati...
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