AIMC Topic: Neoplasms

Clear Filters Showing 2241 to 2250 of 2356 articles

Representation transfer for differentially private drug sensitivity prediction.

Bioinformatics (Oxford, England)
MOTIVATION: Human genomic datasets often contain sensitive information that limits use and sharing of the data. In particular, simple anonymization strategies fail to provide sufficient level of protection for genomic data, because the data are inher...

Deep learning with multimodal representation for pancancer prognosis prediction.

Bioinformatics (Oxford, England)
MOTIVATION: Estimating the future course of patients with cancer lesions is invaluable to physicians; however, current clinical methods fail to effectively use the vast amount of multimodal data that is available for cancer patients. To tackle this p...

A deep learning model based on sparse auto-encoder for prioritizing cancer-related genes and drug target combinations.

Carcinogenesis
Prioritization of cancer-related genes from gene expression profiles and proteomic data is vital to improve the targeted therapies research. Although computational approaches have been complementing high-throughput biological experiments on the under...

Advances in Auto-Segmentation.

Seminars in radiation oncology
Manual image segmentation is a time-consuming task routinely performed in radiotherapy to identify each patient's targets and anatomical structures. The efficacy and safety of the radiotherapy plan requires accurate segmentations as these regions of ...

DriverML: a machine learning algorithm for identifying driver genes in cancer sequencing studies.

Nucleic acids research
Although rapid progress has been made in computational approaches for prioritizing cancer driver genes, research is far from achieving the ultimate goal of discovering a complete catalog of genes truly associated with cancer. Driver gene lists predic...

Differentiating post-cancer from healthy tongue muscle coordination patterns during speech using deep learning.

The Journal of the Acoustical Society of America
The ability to differentiate post-cancer from healthy tongue muscle coordination patterns is necessary for the advancement of speech motor control theories and for the development of therapeutic and rehabilitative strategies. A deep learning approach...

Big data and machine learning algorithms for health-care delivery.

The Lancet. Oncology
Analysis of big data by machine learning offers considerable advantages for assimilation and evaluation of large amounts of complex health-care data. However, to effectively use machine learning tools in health care, several limitations must be addre...

Digital pathology and artificial intelligence.

The Lancet. Oncology
In modern clinical practice, digital pathology has a crucial role and is increasingly a technological requirement in the scientific laboratory environment. The advent of whole-slide imaging, availability of faster networks, and cheaper storage soluti...