AIMC Topic: Antineoplastic Agents
Clear Filters Showing 231 to 240 of 491 articles
Leveraging TCGA gene expression data to build predictive models for cancer drug response.
BMC bioinformatics
Sep 30, 2020
BACKGROUND: Machine learning has been utilized to predict cancer drug response from multi-omics data generated from sensitivities of cancer cell lines to different therapeutic compounds. Here, we build machine learning models using gene expression da...
Cancer gene expression profiles associated with clinical outcomes to chemotherapy treatments.
BMC medical genomics
Sep 18, 2020
BACKGROUND: Machine learning (ML) methods still have limited applicability in personalized oncology due to low numbers of available clinically annotated molecular profiles. This doesn't allow sufficient training of ML classifiers that could be used f...
PeptiDesCalculator: Software for computation of peptide descriptors. Definition, implementation and case studies for 9 bioactivity endpoints.
Proteins
Sep 17, 2020
We present a novel Java-based program denominated PeptiDesCalculator for computing peptide descriptors. These descriptors include: redefinitions of known protein parameters to suite the peptide domain, generalization schemes for the global descriptio...
Molecular imaging and deep learning analysis of uMUC1 expression in response to chemotherapy in an orthotopic model of ovarian cancer.
Scientific reports
Sep 10, 2020
Artificial Intelligence (AI) algorithms including deep learning have recently demonstrated remarkable progress in image-recognition tasks. Here, we utilized AI for monitoring the expression of underglycosylated mucin 1 (uMUC1) tumor antigen, a biomar...
Representation of features as images with neighborhood dependencies for compatibility with convolutional neural networks.
Nature communications
Sep 1, 2020
Deep learning with Convolutional Neural Networks has shown great promise in image-based classification and enhancement but is often unsuitable for predictive modeling using features without spatial correlations. We present a feature representation ap...
Antineoplastic Agents
Gene Expression Profiling
Humans
Deep Learning
Image Processing, Computer-Assisted
Biomarkers, Tumor
High-Throughput Nucleotide Sequencing
Cell Line, Tumor
Cell Proliferation
Neoplasms
Datasets as Topic
Drug Screening Assays, Antitumor
Drug Resistance, Neoplasm
Bayes Theorem
Oligonucleotide Array Sequence Analysis
Robotic compounding versus manual compounding of chemotherapy: Comparing dosing accuracy and precision.
European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences
Aug 30, 2020
BACKGROUND: Cytostatic drugs are increasingly being prepared with a cytostatic robot, though it is not known whether the dose of the final product is more accurate after automated or manual preparation. This study is the first to compare accuracy and...
Machine learning for predicting pathological complete response in patients with locally advanced rectal cancer after neoadjuvant chemoradiotherapy.
Scientific reports
Jul 28, 2020
For patients with locally advanced rectal cancer (LARC), achieving a pathological complete response (pCR) after neoadjuvant chemoradiotherapy (CRT) provides them with the optimal prognosis. However, no reliable prediction model is presently available...
Strategies for Testing Intervention Matching Schemes in Cancer.
Clinical pharmacology and therapeutics
Jul 24, 2020
Personalized medicine, or the tailoring of health interventions to an individual's nuanced and often unique genetic, biochemical, physiological, behavioral, and/or exposure profile, is seen by many as a biological necessity given the great heterogene...
Concise Polygenic Models for Cancer-Specific Identification of Drug-Sensitive Tumors from Their Multi-Omics Profiles.
Biomolecules
Jun 26, 2020
In silico models to predict which tumors will respond to a given drug are necessary for Precision Oncology. However, predictive models are only available for a handful of cases (each case being a given drug acting on tumors of a specific cancer type)...
Artificial intelligence-based collaborative filtering method with ensemble learning for personalized lung cancer medicine without genetic sequencing.
Pharmacological research
Jun 23, 2020
In personalized medicine, many factors influence the choice of compounds. Hence, the selection of suitable medicine for patients with non-small-cell lung cancer (NSCLC) is expensive. To shorten the decision-making process for compounds, we propose a ...
Stay Ahead of Medical AI
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 31037
- Neural Networks, Computer 29719
- Algorithms 26832
- Deep Learning 26346
- Artificial Intelligence 24295
- Robotics 13311
- Image Processing, Computer-Assisted 9521
- Retrospective Studies 9111
- Magnetic Resonance Imaging 6181
- Reproducibility of Results 5592
- Tomography, X-Ray Computed 4771
- Support Vector Machine 4686
- Computational Biology 4237
- Brain 4050
- Computer Simulation 3881
Recent Journals
- Scientific reports 5949
- Sensors (Basel, Switzerland) 4794
- PloS one 4015
- Neural networks : the official journal of the International Neural Network Society 2930
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1859
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1278
- IEEE journal of biomedical and health informatics 1130
- Journal of chemical information and modeling 998
- Nature communications 944
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 861
- Briefings in bioinformatics 853
- IEEE transactions on neural networks and learning systems 826