Deep learning in cancer diagnosis, prognosis and treatment selection
Deep learning is a subdiscipline of artificial intelligence that uses a machine learning
technique called artificial neural networks to extract patterns and make predictions from …
technique called artificial neural networks to extract patterns and make predictions from …
Portrait of a cancer: mutational signature analyses for cancer diagnostics
Background In the past decade, systematic and comprehensive analyses of cancer
genomes have identified cancer driver genes and revealed unprecedented insight into the …
genomes have identified cancer driver genes and revealed unprecedented insight into the …
A deep learning system accurately classifies primary and metastatic cancers using passenger mutation patterns
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 …
determinants of its clinical behaviour, but in 3% of cases a patient presents with a metastatic …
Evaluating DNA methylation, gene expression, somatic mutation, and their combinations in inferring tumor tissue-of-origin
H Liu, C Qiu, B Wang, P Bing, G Tian… - Frontiers in cell and …, 2021 - frontiersin.org
Carcinoma of unknown primary (CUP) is a type of metastatic cancer, the primary tumor site
of which cannot be identified. CUP occupies approximately 5% of cancer incidences in the …
of which cannot be identified. CUP occupies approximately 5% of cancer incidences in the …
Machine learning-based tissue of origin classification for cancer of unknown primary diagnostics using genome-wide mutation features
Cancers of unknown primary (CUP) origin account for∼ 3% of all cancer diagnoses,
whereby the tumor tissue of origin (TOO) cannot be determined. Using a uniformly …
whereby the tumor tissue of origin (TOO) cannot be determined. Using a uniformly …
TOOme: a novel computational framework to infer cancer tissue-of-origin by integrating both gene mutation and expression
Metastatic cancers require further diagnosis to determine their primary tumor sites. However,
the tissue-of-origin for around 5% tumors could not be identified by routine medical …
the tissue-of-origin for around 5% tumors could not be identified by routine medical …
[HTML][HTML] A machine learning framework to trace tumor tissue-of-origin of 13 types of cancer based on DNA somatic mutation
B He, C Dai, J Lang, P Bing, G Tian, B Wang… - Biochimica et Biophysica …, 2020 - Elsevier
Carcinoma of unknown primary (CUP), defined as metastatic cancers with unknown cancer
origin, occurs in 3‐5 per 100 cancer patients in the United States. Heterogeneity and …
origin, occurs in 3‐5 per 100 cancer patients in the United States. Heterogeneity and …
Applications of topological data analysis in oncology
The emergence of the information age in the last few decades brought with it an explosion of
biomedical data. But with great power comes great responsibility: there is now a pressing …
biomedical data. But with great power comes great responsibility: there is now a pressing …
Development of genome-derived tumor type prediction to inform clinical cancer care
A Penson, N Camacho, Y Zheng, AM Varghese… - JAMA …, 2020 - jamanetwork.com
Importance Diagnosing the site of origin for cancer is a pillar of disease classification that
has directed clinical care for more than a century. Even in an era of precision oncologic …
has directed clinical care for more than a century. Even in an era of precision oncologic …
[PDF][PDF] Microarray bioinformatics in cancer-a review
Z Tao, A Shi, R Li, Y Wang, X Wang, J Zhao - J buon, 2017 - jbuon.com
Bioinformatics is one of the newest fields of biological research, and should be viewed
broadly as the use of mathematical, statistical, and computational methods for the …
broadly as the use of mathematical, statistical, and computational methods for the …