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Year Number of Results
1975 1
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1994 4
1995 4
1996 3
1998 2
1999 1
2000 4
2001 11
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2003 30
2004 26
2005 36
2006 41
2007 54
2008 55
2009 66
2010 88
2011 150
2012 198
2013 234
2014 335
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2018 1322
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2020 3268
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2023 6030
2024 2309

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24,845 results

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Page 1
Machine and deep learning approaches for cancer drug repurposing.
Issa NT, Stathias V, Schürer S, Dakshanamurthy S. Issa NT, et al. Semin Cancer Biol. 2021 Jan;68:132-142. doi: 10.1016/j.semcancer.2019.12.011. Epub 2020 Jan 3. Semin Cancer Biol. 2021. PMID: 31904426 Free PMC article. Review.
Advanced "omics" coupled with machine learning and artificial intelligence (deep learning) methods have helped elucidate targets and pathways critical to those processes that may be amenable to pharmacologic modulation. ...Computational in-silico strategies h …
Advanced "omics" coupled with machine learning and artificial intelligence (deep learning) methods have helped elucidat …
From patterns to patients: Advances in clinical machine learning for cancer diagnosis, prognosis, and treatment.
Swanson K, Wu E, Zhang A, Alizadeh AA, Zou J. Swanson K, et al. Cell. 2023 Apr 13;186(8):1772-1791. doi: 10.1016/j.cell.2023.01.035. Epub 2023 Mar 10. Cell. 2023. PMID: 36905928 Review.
Machine learning (ML) is increasingly used in clinical oncology to diagnose cancers, predict patient outcomes, and inform treatment planning. ...Finally, we examine ML models approved for cancer-related patient usage by regulatory agencies and discuss …
Machine learning (ML) is increasingly used in clinical oncology to diagnose cancers, predict patient outcomes, and info …
Applications of Support Vector Machine (SVM) Learning in Cancer Genomics.
Huang S, Cai N, Pacheco PP, Narrandes S, Wang Y, Xu W. Huang S, et al. Cancer Genomics Proteomics. 2018 Jan-Feb;15(1):41-51. doi: 10.21873/cgp.20063. Cancer Genomics Proteomics. 2018. PMID: 29275361 Free PMC article. Review.
Machine learning with maximization (support) of separating margin (vector), called support vector machine (SVM) learning, is a powerful classification tool that has been used for cancer genomic classification or subtyping. ...Herein we reviewed …
Machine learning with maximization (support) of separating margin (vector), called support vector machine (SVM) lear …
Deep learning in cancer diagnosis, prognosis and treatment selection.
Tran KA, Kondrashova O, Bradley A, Williams ED, Pearson JV, Waddell N. Tran KA, et al. Genome Med. 2021 Sep 27;13(1):152. doi: 10.1186/s13073-021-00968-x. Genome Med. 2021. PMID: 34579788 Free PMC article. Review.
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 large data sets. The increasing adoption of deep learning across healthca …
Deep learning is a subdiscipline of artificial intelligence that uses a machine learning technique called artificial ne …
Machine learning on microbiome research in gastrointestinal cancer.
Cheung H, Yu J. Cheung H, et al. J Gastroenterol Hepatol. 2021 Apr;36(4):817-822. doi: 10.1111/jgh.15502. J Gastroenterol Hepatol. 2021. PMID: 33880761 Review.
Gastrointestinal cancer maintains the highest incidence and mortality rate among all cancers globally. ...Artificial intelligence is another rapidly developing field that has strong application potential in microbiome research. Deep learning and machine …
Gastrointestinal cancer maintains the highest incidence and mortality rate among all cancers globally. ...Artificial intellige …
Machine and deep learning methods for radiomics.
Avanzo M, Wei L, Stancanello J, Vallières M, Rao A, Morin O, Mattonen SA, El Naqa I. Avanzo M, et al. Med Phys. 2020 Jun;47(5):e185-e202. doi: 10.1002/mp.13678. Med Phys. 2020. PMID: 32418336 Free PMC article. Review.
Radiomics is an emerging area in quantitative image analysis that aims to relate large-scale extracted imaging information to clinical and biological endpoints. The development of quantitative imaging methods along with machine learning has enabled the opportunity t …
Radiomics is an emerging area in quantitative image analysis that aims to relate large-scale extracted imaging information to clinical and b …
Prediction of lung cancer patient survival via supervised machine learning classification techniques.
Lynch CM, Abdollahi B, Fuqua JD, de Carlo AR, Bartholomai JA, Balgemann RN, van Berkel VH, Frieboes HB. Lynch CM, et al. Int J Med Inform. 2017 Dec;108:1-8. doi: 10.1016/j.ijmedinf.2017.09.013. Epub 2017 Sep 25. Int J Med Inform. 2017. PMID: 29132615 Free PMC article.
Outcomes for cancer patients have been previously estimated by applying various machine learning techniques to large datasets such as the Surveillance, Epidemiology, and End Results (SEER) program database. ...In this study, a number of supervised learning …
Outcomes for cancer patients have been previously estimated by applying various machine learning techniques to large da …
Prediction of Cancer Treatment Using Advancements in Machine Learning.
Singh AK, Ling J, Malviya R. Singh AK, et al. Recent Pat Anticancer Drug Discov. 2023;18(3):364-378. doi: 10.2174/1574892818666221018091415. Recent Pat Anticancer Drug Discov. 2023. PMID: 36263487 Review.
Building therapeutically useful models is still difficult despite enormous increases in computer capacity due to the lack of adequate clinically important pharmacogenomics data. Machine learning is the most widely used branch of artificial intelligence. Here, we rev …
Building therapeutically useful models is still difficult despite enormous increases in computer capacity due to the lack of adequate clinic …
Current state of machine learning for non-melanoma skin cancer.
Sharma AN, Shwe S, Mesinkovska NA. Sharma AN, et al. Arch Dermatol Res. 2022 May;314(4):325-327. doi: 10.1007/s00403-021-02236-9. Epub 2021 May 15. Arch Dermatol Res. 2022. PMID: 33991230 Review.
BACKGROUND: Machine learning (ML) has been increasingly utilized for skin cancer screening, primarily of melanomas but also of non-melanoma skin cancers (NMSC). ...RESULTS: 52 articles were included for quantitative analysis, resulting in a mean sensit …
BACKGROUND: Machine learning (ML) has been increasingly utilized for skin cancer screening, primarily of melanomas but …
Machine Learning-Driven Multiobjective Optimization: An Opportunity of Microfluidic Platforms Applied in Cancer Research.
Liu Y, Li S, Liu Y. Liu Y, et al. Cells. 2022 Mar 5;11(5):905. doi: 10.3390/cells11050905. Cells. 2022. PMID: 35269527 Free PMC article. Review.
Crosstalk and causality of different factors in pathogenesis are two important areas in need of further research. With the assistance of machine learning, microfluidic platforms can reach a higher level of detection and classification of cancer metastasis. Th …
Crosstalk and causality of different factors in pathogenesis are two important areas in need of further research. With the assistance of …
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