[HTML][HTML] Integrating omics data and AI for cancer diagnosis and prognosis

Y Ozaki, P Broughton, H Abdollahi, H Valafar… - Cancers, 2024 - mdpi.com
Simple Summary Cancer remains one of the leading causes of death worldwide, which
emphasizes the need for its early and accurate diagnosis and prognosis. Our review …

Avoiding C-hacking when evaluating survival distribution predictions with discrimination measures

R Sonabend, A Bender, S Vollmer - Bioinformatics, 2022 - academic.oup.com
Motivation In this article, we consider how to evaluate survival distribution predictions with
measures of discrimination. This is non-trivial as discrimination measures are the most …

Unsupervised machine learning improves risk stratification in newly diagnosed multiple myeloma: an analysis of the Spanish Myeloma Group

A Mosquera Orgueira, MS González Pérez… - Blood cancer …, 2022 - nature.com
Abstract The International Staging System (ISS) and the Revised International Staging
System (R-ISS) are commonly used prognostic scores in multiple myeloma (MM). These …

Genetic and transcriptomic analyses of diffuse large B-cell lymphoma patients with poor outcomes within two years of diagnosis

W Ren, H Wan, SA Own, M Berglund, X Wang, M Yang… - Leukemia, 2024 - nature.com
Despite the improvements in clinical outcomes for DLBCL, a significant proportion of
patients still face challenges with refractory/relapsed (R/R) disease after receiving first-line R …

Clinical approaches for integrating machine learning for patients with lymphoma: Current strategies and future perspectives

D Chihara, LJ Nastoupil… - British Journal of …, 2023 - Wiley Online Library
Machine learning (ML) approaches have been applied in the diagnosis and prediction of
haematological malignancies. The consideration of ML algorithms to complement or replace …

[HTML][HTML] Prognostic stratification of diffuse large B-cell lymphoma using clinico-genomic models: validation and improvement of the LymForest-25 model

AM Orgueira, JÁD Arías, MC López, AP Raíndo… - …, 2022 - journals.lww.com
Diffuse large B-cell lymphoma (DLBCL) is the most common type of non-Hodgkin
lymphoma. Despite notable therapeutic advances in the last decades, 30%–40% of affected …

Incorporation of emergent symptoms and genetic covariates improves prediction of aromatase inhibitor therapy discontinuation

I Rattsev, V Stearns, AL Blackford, DL Hertz… - JAMIA …, 2024 - academic.oup.com
Objectives Early discontinuation is common among breast cancer patients taking aromatase
inhibitors (AIs). Although several predictors have been identified, it is unclear how to …

Personally tailored survival prediction of patients with follicular lymphoma using machine learning transcriptome-based models

A Mosquera Orgueira, M Cid López… - Frontiers in …, 2022 - frontiersin.org
Follicular Lymphoma (FL) has a 10-year mortality rate of 20%, and this is mostly related to
lymphoma progression and transformation to higher grades. In the era of personalized …

A prognostic model based on gene expression parameters predicts a better response to bortezomib-containing immunochemotherapy in diffuse large B-cell …

A Mosquera Orgueira, JÁ Díaz Arías… - Frontiers in …, 2023 - frontiersin.org
Diffuse Large B-cell Lymphoma (DLBCL) is the most common type of aggressive lymphoma.
Approximately 60% of fit patients achieve curation with immunochemotherapy, but the …

[HTML][HTML] An interpretable survival model for diffuse large B-cell lymphoma patients using a biologically informed visible neural network

J Tan, J Xie, J Huang, W Deng, H Chai… - Computational and …, 2024 - Elsevier
Diffuse large B-cell lymphoma (DLBCL) is the most common subtype of non-Hodgkin
lymphoma (NHL) and is characterized by high heterogeneity. Assessment of its prognosis …