PURPOSE: Recent advances in machine learning have enabled better understanding of large and complex visual data. Here, we aim to investigate patient outcome prediction with a machine learning method using only an image of tumour sample as an input.
Journal of cellular and molecular medicine
Apr 18, 2019
BACKGROUND: This study aimed to examine multi-dimensional MRI features' predictability on survival outcome and associations with differentially expressed Genes (RNA Sequencing) in groups of glioblastoma multiforme (GBM) patients.
Clinical cancer research : an official journal of the American Association for Cancer Research
Apr 16, 2019
PURPOSE: Radiation pneumonitis is an important adverse event in patients with non-small cell lung cancer (NSCLC) receiving thoracic radiotherapy. However, the risk of radiation pneumonitis grade ≥ 2 (RP2) has not been well predicted. This study hypot...
Clinical cancer research : an official journal of the American Association for Cancer Research
Apr 11, 2019
PURPOSE: We aimed to develop an ovarian cancer-specific predictive framework for clinical stage, histotype, residual tumor burden, and prognosis using machine learning methods based on multiple biomarkers.
IEEE/ACM transactions on computational biology and bioinformatics
Apr 9, 2019
Breast cancer is one of the most common cancers all over the world, which bring about more than 450,000 deaths each year. Although this malignancy has been extensively studied by a large number of researchers, its prognosis is still poor. Since thera...
IMPORTANCE: A molecular diagnostic method that incorporates information about the transcriptional status of all genes across multiple tissue types can strengthen confidence in cancer diagnosis.
Increasing evidence has indicated that microRNAs(miRNAs) play vital roles in various pathological processes and thus are closely related with many complex human diseases. The identification of potential disease-related miRNAs offers new opportunities...
Estimating over-amplification of human epidermal growth factor receptor 2 (HER2) on invasive breast cancer is regarded as a significant predictive and prognostic marker. We propose a novel deep reinforcement learning (DRL)-based model that treats imm...
BACKGROUND: Lung adenocarcinoma is the most common type of lung cancers. Whole-genome sequencing studies disclosed the genomic landscape of lung adenocarcinomas. however, it remains unclear if the genetic alternations could guide prognosis prediction...
IEEE/ACM transactions on computational biology and bioinformatics
Mar 18, 2019
As one of the most common malignancies in the world, lung adenocarcinoma (LUAD) is currently difficult to cure. However, the advent of precision medicine provides an opportunity to improve the treatment of lung cancer. Subtyping lung cancer plays an ...