Deep learning for drug response prediction in cancer
Predicting the sensitivity of tumors to specific anti-cancer treatments is a challenge of
paramount importance for precision medicine. Machine learning (ML) algorithms can be …
paramount importance for precision medicine. Machine learning (ML) algorithms can be …
An overview of machine learning methods for monotherapy drug response prediction
F Firoozbakht, B Yousefi… - Briefings in …, 2022 - academic.oup.com
For an increasing number of preclinical samples, both detailed molecular profiles and their
responses to various drugs are becoming available. Efforts to understand, and predict, drug …
responses to various drugs are becoming available. Efforts to understand, and predict, drug …
Representation of features as images with neighborhood dependencies for compatibility with convolutional neural networks
Abstract Deep learning with Convolutional Neural Networks has shown great promise in
image-based classification and enhancement but is often unsuitable for predictive modeling …
image-based classification and enhancement but is often unsuitable for predictive modeling …
Optimizing ensemble weights and hyperparameters of machine learning models for regression problems
Aggregating multiple learners through an ensemble of models aim to make better
predictions by capturing the underlying distribution of the data more accurately. Different …
predictions by capturing the underlying distribution of the data more accurately. Different …
Graph convolutional networks for drug response prediction
Background: Drug response prediction is an important problem in computational
personalized medicine. Many machine-learning-based methods, especially deep learning …
personalized medicine. Many machine-learning-based methods, especially deep learning …
A systematic review of applications of machine learning in cancer prediction and diagnosis
Advancement in genome sequencing technology has empowered researchers to think
beyond their imagination. Researchers are trying their hard to fight against various genetic …
beyond their imagination. Researchers are trying their hard to fight against various genetic …
Deep learning of pharmacogenomics resources: moving towards precision oncology
The recent accumulation of cancer genomic data provides an opportunity to understand how
a tumor's genomic characteristics can affect its responses to drugs. This field, called …
a tumor's genomic characteristics can affect its responses to drugs. This field, called …
Anticancer drug response prediction in cell lines using weighted graph regularized matrix factorization
Precision medicine has become a novel and rising concept, which depends much on the
identification of individual genomic signatures for different patients. The cancer cell lines …
identification of individual genomic signatures for different patients. The cancer cell lines …
Tomato disease and pest diagnosis method based on the Stacking of prescription data
C Xu, J Ding, Y Qiao, L Zhang - Computers and Electronics in Agriculture, 2022 - Elsevier
Crop prescription data contains an extensive amount of information on crops, environment
and pests, and has notable diagnostic capabilities. At present, there is lack of feasible …
and pests, and has notable diagnostic capabilities. At present, there is lack of feasible …
An ensemble model for prediction of vancomycin trough concentrations in pediatric patients
X Huang, Z Yu, S Bu, Z Lin, X Hao, W He… - Drug design …, 2021 - Taylor & Francis
Purpose This study aimed to establish an optimal model to predict vancomycin trough
concentrations by using machine learning. Patients and Methods We enrolled 407 pediatric …
concentrations by using machine learning. Patients and Methods We enrolled 407 pediatric …