Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation

Search Page

Filters

My NCBI Filters

Results by year

Table representation of search results timeline featuring number of search results per year.

Year Number of Results
2000 1
2004 2
2005 4
2006 1
2007 3
2008 1
2009 2
2010 3
2011 1
2012 3
2013 8
2014 11
2015 9
2016 17
2017 14
2018 35
2019 54
2020 60
2021 87
2022 96
2023 128
2024 60

Text availability

Article attribute

Article type

Publication date

Search Results

548 results

Results by year

Filters applied: . Clear all
Page 1
Did you mean ovarian cancer vaccine learning (6 results)?
Multimodal data integration using machine learning improves risk stratification of high-grade serous ovarian cancer.
Boehm KM, Aherne EA, Ellenson L, Nikolovski I, Alghamdi M, Vázquez-García I, Zamarin D, Long Roche K, Liu Y, Patel D, Aukerman A, Pasha A, Rose D, Selenica P, Causa Andrieu PI, Fong C, Capanu M, Reis-Filho JS, Vanguri R, Veeraraghavan H, Gangai N, Sosa R, Leung S, McPherson A, Gao J; MSK MIND Consortium; Lakhman Y, Shah SP. Boehm KM, et al. Nat Cancer. 2022 Jun;3(6):723-733. doi: 10.1038/s43018-022-00388-9. Epub 2022 Jun 28. Nat Cancer. 2022. PMID: 35764743 Free PMC article.
Patients with high-grade serous ovarian cancer suffer poor prognosis and variable response to treatment. ...We found that these features contributed complementary prognostic information relative to one another and clinicogenomic features. By fusing histopathological …
Patients with high-grade serous ovarian cancer suffer poor prognosis and variable response to treatment. ...We found that thes …
Proteogenomic analysis of chemo-refractory high-grade serous ovarian cancer.
Chowdhury S, Kennedy JJ, Ivey RG, Murillo OD, Hosseini N, Song X, Petralia F, Calinawan A, Savage SR, Berry AB, Reva B, Ozbek U, Krek A, Ma W, da Veiga Leprevost F, Ji J, Yoo S, Lin C, Voytovich UJ, Huang Y, Lee SH, Bergan L, Lorentzen TD, Mesri M, Rodriguez H, Hoofnagle AN, Herbert ZT, Nesvizhskii AI, Zhang B, Whiteaker JR, Fenyo D, McKerrow W, Wang J, Schürer SC, Stathias V, Chen XS, Barcellos-Hoff MH, Starr TK, Winterhoff BJ, Nelson AC, Mok SC, Kaufmann SH, Drescher C, Cieslik M, Wang P, Birrer MJ, Paulovich AG. Chowdhury S, et al. Cell. 2023 Aug 3;186(16):3476-3498.e35. doi: 10.1016/j.cell.2023.07.004. Cell. 2023. PMID: 37541199 Free PMC article.
To improve the understanding of chemo-refractory high-grade serous ovarian cancers (HGSOCs), we characterized the proteogenomic landscape of 242 (refractory and sensitive) HGSOCs, representing one discovery and two validation cohorts across two biospecimen types (formalin- …
To improve the understanding of chemo-refractory high-grade serous ovarian cancers (HGSOCs), we characterized the proteogenomic lands …
Machine Learning for Early Lung Cancer Identification Using Routine Clinical and Laboratory Data.
Gould MK, Huang BZ, Tammemagi MC, Kinar Y, Shiff R. Gould MK, et al. Am J Respir Crit Care Med. 2021 Aug 15;204(4):445-453. doi: 10.1164/rccm.202007-2791OC. Am J Respir Crit Care Med. 2021. PMID: 33823116
Objectives: To develop a model to predict a future diagnosis of lung cancer on the basis of routine clinical and laboratory data by using machine learning. Methods: We assembled data from 6,505 case patients with non-small cell lung cancer (NSCLC) and …
Objectives: To develop a model to predict a future diagnosis of lung cancer on the basis of routine clinical and laboratory data by u …
Predicting breast cancer risk using personal health data and machine learning models.
Stark GF, Hart GR, Nartowt BJ, Deng J. Stark GF, et al. PLoS One. 2019 Dec 27;14(12):e0226765. doi: 10.1371/journal.pone.0226765. eCollection 2019. PLoS One. 2019. PMID: 31881042 Free PMC article.
By contrast, we developed machine learning models that used highly accessible personal health data to predict five-year breast cancer risk. ...For both sets of inputs, six machine learning models were trained and evaluated on the Prostate, Lung, …
By contrast, we developed machine learning models that used highly accessible personal health data to predict five-year breast …
Using machine learning to predict ovarian cancer.
Lu M, Fan Z, Xu B, Chen L, Zheng X, Li J, Znati T, Mi Q, Jiang J. Lu M, et al. Int J Med Inform. 2020 Sep;141:104195. doi: 10.1016/j.ijmedinf.2020.104195. Epub 2020 May 23. Int J Med Inform. 2020. PMID: 32485554
OBJECTIVE: Ovarian cancer (OC) is one of the most common types of cancer in women. ...The model also yields better prediction result than ROMA. CONCLUSION: Machine learning approaches were able to accurately classify BOT and OC. ...
OBJECTIVE: Ovarian cancer (OC) is one of the most common types of cancer in women. ...The model also yields better pred …
Diagnostics of ovarian cancer via metabolite analysis and machine learning.
Yao JZ, Tsigelny IF, Kesari S, Kouznetsova VL. Yao JZ, et al. Integr Biol (Camb). 2023 Apr 11;15:zyad005. doi: 10.1093/intbio/zyad005. Integr Biol (Camb). 2023. PMID: 37032481
Ovarian cancer (OC) is the second most common cancer of the female reproductive system. ...Our results demonstrate the possibility of development of the machine-learning models for OC diagnostics using metabolomics data....
Ovarian cancer (OC) is the second most common cancer of the female reproductive system. ...Our results demonstrate the …
Integrative Analysis From Multicenter Studies Identifies a WGCNA-Derived Cancer-Associated Fibroblast Signature for Ovarian Cancer.
Feng S, Xu Y, Dai Z, Yin H, Zhang K, Shen Y. Feng S, et al. Front Immunol. 2022 Jul 8;13:951582. doi: 10.3389/fimmu.2022.951582. eCollection 2022. Front Immunol. 2022. PMID: 35874760 Free PMC article.
This study aimed to identify prognostic genes associated with CAFs that lead to high morbidity and mortality in ovarian cancer (OC) patients. We performed bioinformatics analysis in 16 multicenter studies (2,742 patients) and identified CAF-associated hub genes usin …
This study aimed to identify prognostic genes associated with CAFs that lead to high morbidity and mortality in ovarian cancer …
Deep learning-enabled pelvic ultrasound images for accurate diagnosis of ovarian cancer in China: a retrospective, multicentre, diagnostic study.
Gao Y, Zeng S, Xu X, Li H, Yao S, Song K, Li X, Chen L, Tang J, Xing H, Yu Z, Zhang Q, Zeng S, Yi C, Xie H, Xiong X, Cai G, Wang Z, Wu Y, Chi J, Jiao X, Qin Y, Mao X, Chen Y, Jin X, Mo Q, Chen P, Huang Y, Shi Y, Wang J, Zhou Y, Ding S, Zhu S, Liu X, Dong X, Cheng L, Zhu L, Cheng H, Cha L, Hao Y, Jin C, Zhang L, Zhou P, Sun M, Xu Q, Chen K, Gao Z, Zhang X, Ma Y, Liu Y, Xiao L, Xu L, Peng L, Hao Z, Yang M, Wang Y, Ou H, Jia Y, Tian L, Zhang W, Jin P, Tian X, Huang L, Wang Z, Liu J, Fang T, Yan D, Cao H, Ma J, Li X, Zheng X, Lou H, Song C, Li R, Wang S, Li W, Zheng X, Chen J, Li G, Chen R, Xu C, Yu R, Wang J, Xu S, Kong B, Xie X, Ma D, Gao Q. Gao Y, et al. Lancet Digit Health. 2022 Mar;4(3):e179-e187. doi: 10.1016/S2589-7500(21)00278-8. Lancet Digit Health. 2022. PMID: 35216752 Free article.
BACKGROUND: Ultrasound is a critical non-invasive test for preoperative diagnosis of ovarian cancer. Deep learning is making advances in image-recognition tasks; therefore, we aimed to develop a deep convolutional neural network (DCNN) model that automates ev …
BACKGROUND: Ultrasound is a critical non-invasive test for preoperative diagnosis of ovarian cancer. Deep learning is m …
Predictive Value of Machine Learning for Platinum Chemotherapy Responses in Ovarian Cancer: Systematic Review and Meta-Analysis.
Wang Q, Chang Z, Liu X, Wang Y, Feng C, Ping Y, Feng X. Wang Q, et al. J Med Internet Res. 2024 Jan 22;26:e48527. doi: 10.2196/48527. J Med Internet Res. 2024. PMID: 38252469 Free PMC article. Review.
BACKGROUND: Machine learning is a potentially effective method for predicting the response to platinum-based treatment for ovarian cancer. ...OBJECTIVE: This study aims to systematically review relevant literature on the predictive value of machine …
BACKGROUND: Machine learning is a potentially effective method for predicting the response to platinum-based treatment for …
Application of machine learning techniques for predicting survival in ovarian cancer.
Sorayaie Azar A, Babaei Rikan S, Naemi A, Bagherzadeh Mohasefi J, Pirnejad H, Bagherzadeh Mohasefi M, Wiil UK. Sorayaie Azar A, et al. BMC Med Inform Decis Mak. 2022 Dec 30;22(1):345. doi: 10.1186/s12911-022-02087-y. BMC Med Inform Decis Mak. 2022. PMID: 36585641 Free PMC article.
BACKGROUND: Ovarian cancer is the fifth leading cause of mortality among women in the United States. Ovarian cancer is also known as forgotten cancer or silent disease. ...
BACKGROUND: Ovarian cancer is the fifth leading cause of mortality among women in the United States. Ovarian cancer …
548 results