These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
4. Evading obscure communication from spam emails. Rafat KF; Xin Q; Javed AR; Jalil Z; Ahmad RZ Math Biosci Eng; 2022 Jan; 19(2):1926-1943. PubMed ID: 35135236 [TBL] [Abstract][Full Text] [Related]
5. An efficient incremental learning mechanism for tracking concept drift in spam filtering. Sheu JJ; Chu KT; Li NF; Lee CC PLoS One; 2017; 12(2):e0171518. PubMed ID: 28182691 [TBL] [Abstract][Full Text] [Related]
6. Application of interval type-2 fuzzy logic and type-1 fuzzy logic-based approaches to social networks for spam detection with combined feature capabilities. Atacak İ; Çıtlak O; Doğru İA PeerJ Comput Sci; 2023; 9():e1316. PubMed ID: 37346510 [TBL] [Abstract][Full Text] [Related]
7. Cloud-based email phishing attack using machine and deep learning algorithm. Butt UA; Amin R; Aldabbas H; Mohan S; Alouffi B; Ahmadian A Complex Intell Systems; 2023; 9(3):3043-3070. PubMed ID: 35668732 [TBL] [Abstract][Full Text] [Related]
8. Empirical Analysis of Weapons of Influence, Life Domains, and Demographic-Targeting in Modern Spam - An Age-Comparative Perspective. Oliveira DS; Lin T; Rocha H; Ellis D; Dommaraju S; Yang H; Weir D; Marin S; Ebner NC Crime Sci; 2019; 8():. PubMed ID: 31231604 [TBL] [Abstract][Full Text] [Related]
9. Data-driven modeling and prediction of blood glucose dynamics: Machine learning applications in type 1 diabetes. Woldaregay AZ; Årsand E; Walderhaug S; Albers D; Mamykina L; Botsis T; Hartvigsen G Artif Intell Med; 2019 Jul; 98():109-134. PubMed ID: 31383477 [TBL] [Abstract][Full Text] [Related]
10. Real-Time Twitter Spam Detection and Sentiment Analysis using Machine Learning and Deep Learning Techniques. Rodrigues AP; Fernandes R; A A; B A; Shetty A; K A; Lakshmanna K; Shafi RM Comput Intell Neurosci; 2022; 2022():5211949. PubMed ID: 35463239 [TBL] [Abstract][Full Text] [Related]
11. Deep convolutional forest: a dynamic deep ensemble approach for spam detection in text. Shaaban MA; Hassan YF; Guirguis SK Complex Intell Systems; 2022; 8(6):4897-4909. PubMed ID: 35496326 [TBL] [Abstract][Full Text] [Related]
12. A systematic literature review on spam content detection and classification. Kaddoura S; Chandrasekaran G; Elena Popescu D; Duraisamy JH PeerJ Comput Sci; 2022; 8():e830. PubMed ID: 35174265 [TBL] [Abstract][Full Text] [Related]
13. Machine Learning Approaches for Predicting Radiation Therapy Outcomes: A Clinician's Perspective. Kang J; Schwartz R; Flickinger J; Beriwal S Int J Radiat Oncol Biol Phys; 2015 Dec; 93(5):1127-35. PubMed ID: 26581149 [TBL] [Abstract][Full Text] [Related]
14. An Advanced Deep Attention Collaborative Mechanism for Secure Educational Email Services. Chen Y; Yang Y Comput Intell Neurosci; 2022; 2022():3150626. PubMed ID: 35515496 [TBL] [Abstract][Full Text] [Related]
15. The psychological interaction of spam email features. Williams SE; Sarno DM; Lewis JE; Shoss MK; Neider MB; Bohil CJ Ergonomics; 2019 Aug; 62(8):983-994. PubMed ID: 31056018 [TBL] [Abstract][Full Text] [Related]
16. A machine learning model with human cognitive biases capable of learning from small and biased datasets. Taniguchi H; Sato H; Shirakawa T Sci Rep; 2018 May; 8(1):7397. PubMed ID: 29743630 [TBL] [Abstract][Full Text] [Related]
17. A novel approach for Arabic business email classification based on deep learning machines. Masri A; Al-Jabi M PeerJ Comput Sci; 2023; 9():e1221. PubMed ID: 37346608 [TBL] [Abstract][Full Text] [Related]
18. [Spams in doctors' mailbox: their threat to health education, to patient information and to scientific research]. Felkai P; Lengyel I Orv Hetil; 2019 Oct; 160(43):1706-1710. PubMed ID: 31630551 [TBL] [Abstract][Full Text] [Related]
19. Rise of Deep Learning for Genomic, Proteomic, and Metabolomic Data Integration in Precision Medicine. Grapov D; Fahrmann J; Wanichthanarak K; Khoomrung S OMICS; 2018 Oct; 22(10):630-636. PubMed ID: 30124358 [TBL] [Abstract][Full Text] [Related]
20. SMS sentiment classification using an evolutionary optimization based fuzzy recurrent neural network. Srinivasarao U; Sharaff A Multimed Tools Appl; 2023 Apr; ():1-32. PubMed ID: 37362691 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]