AIMC Topic: Neoplasms

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DeepMILO: a deep learning approach to predict the impact of non-coding sequence variants on 3D chromatin structure.

Genome biology
Non-coding variants have been shown to be related to disease by alteration of 3D genome structures. We propose a deep learning method, DeepMILO, to predict the effects of variants on CTCF/cohesin-mediated insulator loops. Application of DeepMILO on v...

Artificial intelligence in oncology.

Cancer science
Artificial intelligence (AI) has contributed substantially to the resolution of a variety of biomedical problems, including cancer, over the past decade. Deep learning, a subfield of AI that is highly flexible and supports automatic feature extractio...

Real-time tumor localization with single x-ray projection at arbitrary gantry angles using a convolutional neural network (CNN).

Physics in medicine and biology
For tumor tracking therapy, precise knowledge of tumor position in real-time is very important. A technique using single x-ray projection based on a convolutional neural network (CNN) was recently developed which can achieve accurate tumor localizati...

MethylNet: an automated and modular deep learning approach for DNA methylation analysis.

BMC bioinformatics
BACKGROUND: DNA methylation (DNAm) is an epigenetic regulator of gene expression programs that can be altered by environmental exposures, aging, and in pathogenesis. Traditional analyses that associate DNAm alterations with phenotypes suffer from mul...

Deep-Learning Detection of Cancer Metastases to the Brain on MRI.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Approximately one-fourth of all cancer metastases are found in the brain. MRI is the primary technique for detection of brain metastasis, planning of radiotherapy, and the monitoring of treatment response. Progress in tumor treatment now ...

Editorial for "Deep-Learning Detection of Cancer Metastasis to the Brain on MRI".

Journal of magnetic resonance imaging : JMRI
5 TECHNICAL EFFICACY: Stage 1 J. Magn. Reson. Imaging 2020;52:1237-1238.

Identifying Cancer Patients at Risk for Heart Failure Using Machine Learning Methods.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Cardiotoxicity related to cancer therapies has become a serious issue, diminishing cancer treatment outcomes and quality of life. Early detection of cancer patients at risk for cardiotoxicity before cardiotoxic treatments and providing preventive mea...

Achievability to Extract Specific Date Information for Cancer Research.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Accurate identification of temporal information such as date is crucial for advancing cancer research which often requires precise date information associated with related cancer events. However, there is a gap for existing natural language processin...

Artificial intelligence as the next step towards precision pathology.

Journal of internal medicine
Pathology is the cornerstone of cancer care. The need for accuracy in histopathologic diagnosis of cancer is increasing as personalized cancer therapy requires accurate biomarker assessment. The appearance of digital image analysis holds promise to i...