AIMC Topic: Fluorouracil
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Comparing Scientific Machine Learning With Population Pharmacokinetic and Classical Machine Learning Approaches for Prediction of Drug Concentrations.
CPT: pharmacometrics & systems pharmacology
Feb 7, 2025
A variety of classical machine learning (ML) approaches has been developed over the past decade aiming to individualize drug dosages based on measured plasma concentrations. However, the interpretability of these models is challenging as they do not ...
Determination of 5-fluorouracil anticancer drug solubility in supercritical COusing semi-empirical and machine learning models.
Scientific reports
Feb 7, 2025
In order to provide the facilities to design the supercritical fluid (SCF) processes for micro or nanosizing of solid solute compounds such as drugs, it is essential to obtain their solubility in green solvents like pressurized CO. This important rol...
Improving the prediction of patient survival with the aid of residual convolutional neural network (ResNet) in colorectal cancer with unresectable liver metastases treated with bevacizumab-based chemotherapy.
Cancer imaging : the official publication of the International Cancer Imaging Society
Dec 18, 2024
BACKGROUND: To verify overall survival predictions made with residual convolutional neural network-determined morphological response (ResNet-MR) in patients with unresectable synchronous liver-only metastatic colorectal cancer (mCRC) treated with bev...
Artificial intelligence-driven hydrogel microneedle patches integrating 5-fluorouracil inclusion complex-loaded flexible pegylated liposomes for enhanced non-melanoma skin cancer treatment.
International journal of pharmaceutics
Dec 13, 2024
The current study focused on the development of crosslinked hydrogel microneedle patches (cHMNs) incorporating 5-FU-hydroxypropyl beta-cyclodextrin inclusion complex-loaded flexible PEGylated liposomes (5-FU-HPβCD-loaded FP-LPs) to enhance treatment ...
SNPs and blood inflammatory marker featured machine learning for predicting the efficacy of fluorouracil-based chemotherapy in colorectal cancer.
Scientific reports
Nov 12, 2024
Fluorouracil-based chemotherapy responses in colorectal cancer (CRC) patients vary widely, highlighting the role of pharmacogenomics in developing better predictive models. We analyzed 379 CRC patients receiving fluorouracil-based chemotherapy, colle...
Predictive biomarkers for embryotoxicity: a machine learning approach to mitigating multicollinearity in RNA-Seq.
Archives of toxicology
Sep 6, 2024
Multicollinearity, characterized by significant co-expression patterns among genes, often occurs in high-throughput expression data, potentially impacting the predictive model's reliability. This study examined multicollinearity among closely related...
Predicting response to neoadjuvant chemotherapy for colorectal liver metastasis using deep learning on prechemotherapy cross-sectional imaging.
Journal of surgical oncology
May 7, 2024
BACKGROUND AND OBJECTIVES: Deep learning models (DLMs) are applied across domains of health sciences to generate meaningful predictions. DLMs make use of neural networks to generate predictions from discrete data inputs. This study employs DLM on pre...
Modeling 5-FU-Induced Chemotherapy Selection of a Drug-Resistant Cancer Stem Cell Subpopulation.
Current oncology (Toronto, Ont.)
Feb 25, 2024
(1) Background: Cancer stem cells (CSCs) are a subpopulation of cells in a tumor that can self-regenerate and produce different types of cells with the ability to initiate tumor growth and dissemination. Chemotherapy resistance, caused by numerous me...
Machine Learning Predicts Oxaliplatin Benefit in Early Colon Cancer.
Journal of clinical oncology : official journal of the American Society of Clinical Oncology
Feb 5, 2024
PURPOSE: A combination of fluorouracil, leucovorin, and oxaliplatin (FOLFOX) is the standard for adjuvant therapy of resected early-stage colon cancer (CC). Oxaliplatin leads to lasting and disabling neurotoxicity. Reserving the regimen for patients ...
Noninvasive Computed Tomography-Based Deep Learning Model Predicts In Vitro Chemosensitivity Assay Results in Pancreatic Cancer.
Pancreas
Nov 24, 2023
OBJECTIVES: We aimed to predict in vitro chemosensitivity assay results from computed tomography (CT) images by applying deep learning (DL) to optimize chemotherapy for pancreatic ductal adenocarcinoma (PDAC).
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