AIMC Topic: Neoplasms

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Collective effects of long-range DNA methylations predict gene expressions and estimate phenotypes in cancer.

Scientific reports
DNA methylation of various genomic regions has been found to be associated with gene expression in diverse biological contexts. However, most genome-wide studies have focused on the effect of (1) methylation in cis, not in trans and (2) a single CpG,...

Tabu Search and Machine-Learning Classification of Benign and Malignant Proliferative Breast Lesions.

BioMed research international
Breast cancer is the most diagnosed cancer among women around the world. The development of computer-aided diagnosis tools is essential to help pathologists to accurately interpret and discriminate between malignant and benign tumors. This paper prop...

Comparing an Artificial Neural Network to Logistic Regression for Predicting ED Visit Risk Among Patients With Cancer: A Population-Based Cohort Study.

Journal of pain and symptom management
CONTEXT: Prior work using symptom burden to predict emergency department (ED) visits among patients with cancer has used traditional statistical methods such as logistic regression (LR). Machine learning approaches for prediction, such as artificial ...

iLoF: An intelligent Lab on Fiber Approach for Human Cancer Single-Cell Type Identification.

Scientific reports
With the advent of personalized medicine, there is a movement to develop "smaller" and "smarter" microdevices that are able to distinguish similar cancer subtypes. Tumor cells display major differences when compared to their natural counterparts, due...

Hyper-Graph Regularized Constrained NMF for Selecting Differentially Expressed Genes and Tumor Classification.

IEEE journal of biomedical and health informatics
Non-negative Matrix Factorization (NMF) is a dimensionality reduction approach for learning a parts-based and linear representation of non-negative data. It has attracted more attention because of that. In practice, NMF not only neglects the manifold...

Performance assessment of a new optimization system for robotic SBRT MLC-based plans.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
PURPOSE: To assess the performance of a new optimization system, VOLO, for CyberKnife MLC-based SBRT plans in comparison with the existing Sequential optimizer.

Machine Learning and Bioinformatics Models to Identify Pathways that Mediate Influences of Welding Fumes on Cancer Progression.

Scientific reports
Welding generates and releases fumes that are hazardous to human health. Welding fumes (WFs) are a complex mix of metallic oxides, fluorides and silicates that can cause or exacerbate health problems in exposed individuals. In particular, WF inhalati...

RefDNN: a reference drug based neural network for more accurate prediction of anticancer drug resistance.

Scientific reports
Cancer is one of the most difficult diseases to treat owing to the drug resistance of tumour cells. Recent studies have revealed that drug responses are closely associated with genomic alterations in cancer cells. Numerous state-of-the-art machine le...

A deep learning system accurately classifies primary and metastatic cancers using passenger mutation patterns.

Nature communications
In cancer, the primary tumour's organ of origin and histopathology are the strongest determinants of its clinical behaviour, but in 3% of cases a patient presents with a metastatic tumour and no obvious primary. Here, as part of the ICGC/TCGA Pan-Can...

A deep learning approach to radiation dose estimation.

Physics in medicine and biology
Currently methods for predicting absorbed dose after administering a radiopharmaceutical are rather crude in daily clinical practice. Most importantly, individual tissue density distributions as well as local variations of the concentration of the ra...