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Saba Bashir
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2020 – today
- 2024
- [j21]Saba Bashir, Farwa Maqbool Hussain, Farhan Hassan Khan, Asif Sohail Abid:
Hybrid machine learning model for malware analysis in android apps. Pervasive Mob. Comput. 97: 101859 (2024) - 2023
- [j20]Abdulwahab Ali Almazroi, Eman Aldhahri, Saba Bashir, Sufyan Ashfaq:
A Clinical Decision Support System for Heart Disease Prediction Using Deep Learning. IEEE Access 11: 61646-61659 (2023) - 2022
- [j19]Saba Bashir, Irfan Ullah Khattak, Aihab Khan, Farhan Hassan Khan, Abdullah Gani, Muhammad Shiraz:
A Novel Feature Selection Method for Classification of Medical Data Using Filters, Wrappers, and Embedded Approaches. Complex. 2022: 8190814:1-8190814:12 (2022) - [j18]Syed Fakhar Bilal, Abdulwahab Ali Almazroi, Saba Bashir, Farhan Hassan Khan, Abdulaleem Ali Almazroi:
An ensemble based approach using a combination of clustering and classification algorithms to enhance customer churn prediction in telecom industry. PeerJ Comput. Sci. 8: e854 (2022) - [c8]Kinza Rohail, Saba Bashir, Hazrat Ali, Tanvir Alam, Sheheryar Khan, Jia Wu, Pingjun Chen, Rizwan Qureshi:
Understanding Tumor Micro Environment Using Graph Theory. ACCV (Workshops) 2022: 90-101 - 2021
- [j17]Saba Bashir, Abdulwahab Ali Almazroi, Sufyan Ashfaq, Abdulaleem Ali Almazroi, Farhan Hassan Khan:
A Knowledge-Based Clinical Decision Support System Utilizing an Intelligent Ensemble Voting Scheme for Improved Cardiovascular Disease Prediction. IEEE Access 9: 130805-130822 (2021) - [j16]Saman Ebadi, Saba Bashir:
An exploration into EFL learners' writing skills via mobile-based dynamic assessment. Educ. Inf. Technol. 26(2): 1995-2016 (2021)
2010 – 2019
- 2019
- [j15]Farhan Hassan Khan, Usman Qamar, Saba Bashir:
Enhanced cross-domain sentiment classification utilizing a multi-source transfer learning approach. Soft Comput. 23(14): 5431-5442 (2019) - [c7]Muhammad Asad, Younas Khan, Usman Qamar, Saba Bashir:
Blood Glucose Level Prediction Using Optimized Neural Network for Virtual Patients. IntelliSys (2) 2019: 671-683 - 2018
- [j14]Saba Bashir, Usman Qamar, Farhan Hassan Khan:
WebMAC: A web based clinical expert system. Inf. Syst. Frontiers 20(5): 1135-1151 (2018) - [c6]Fawad Ali, Farhan Hassan Khan, Saba Bashir, Uzair Ahmad:
Counter Terrorism on Online Social Networks Using Web Mining Techniques. INTAP 2018: 240-250 - [c5]Haroon Ur Rasheed, Farhan Hassan Khan, Saba Bashir, Irsa Fatima:
Detecting Suspicious Discussion on Online Forums Using Data Mining. INTAP 2018: 262-273 - [c4]Syed Fakhar Bilal, Saba Bashir, Farhan Hassan Khan, Haroon Rasheed:
Malwares Detection for Android and Windows System by Using Machine Learning and Data Mining. INTAP 2018: 485-495 - [c3]Madeha Arif, Usman Qamar, Farhan Hassan Khan, Saba Bashir:
A Survey of Customer Review Helpfulness Prediction Techniques. IntelliSys (1) 2018: 215-226 - 2017
- [j13]Farhan Hassan Khan, Usman Qamar, Saba Bashir:
Lexicon based semantic detection of sentiments using expected likelihood estimate smoothed odds ratio. Artif. Intell. Rev. 48(1): 113-138 (2017) - [j12]Farhan Hassan Khan, Usman Qamar, Saba Bashir:
A semi-supervised approach to sentiment analysis using revised sentiment strength based on SentiWordNet. Knowl. Inf. Syst. 51(3): 851-872 (2017) - [c2]Adnan Ullah, Usman Qamar, Farhan Hassan Khan, Saba Bashir:
Dimensionality reduction approaches and evolving challenges in high dimensional data. IML 2017: 67:1-67:8 - 2016
- [j11]Farhan Hassan Khan, Usman Qamar, Saba Bashir:
SentiMI: Introducing point-wise mutual information with SentiWordNet to improve sentiment polarity detection. Appl. Soft Comput. 39: 140-153 (2016) - [j10]Usman Qamar, Rozina Nisa, Saba Bashir, Farhan Hassan Khan:
A Majority Vote Based Classifier Ensemble for Web Service Classification. Bus. Inf. Syst. Eng. 58(4): 249-259 (2016) - [j9]Saba Bashir, Usman Qamar, Farhan Hassan Khan:
A Multicriteria Weighted Vote-Based Classifier Ensemble for Heart Disease Prediction. Comput. Intell. 32(4): 615-645 (2016) - [j8]Farhan Hassan Khan, Usman Qamar, Saba Bashir:
Multi-Objective Model Selection (MOMS)-based Semi-Supervised Framework for Sentiment Analysis. Cogn. Comput. 8(4): 614-628 (2016) - [j7]Farhan Hassan Khan, Usman Qamar, Saba Bashir:
Senti-CS: Building a lexical resource for sentiment analysis using subjective feature selection and normalized Chi-Square-based feature weight generation. Expert Syst. J. Knowl. Eng. 33(5): 489-500 (2016) - [j6]Farhan Hassan Khan, Usman Qamar, Saba Bashir:
eSAP: A decision support framework for enhanced sentiment analysis and polarity classification. Inf. Sci. 367-368: 862-873 (2016) - [j5]Saba Bashir, Usman Qamar, Farhan Hassan Khan:
IntelliHealth: A medical decision support application using a novel weighted multi-layer classifier ensemble framework. J. Biomed. Informatics 59: 185-200 (2016) - [j4]Saba Bashir, Usman Qamar, Farhan Hassan Khan, Lubna Naseem:
HMV: A medical decision support framework using multi-layer classifiers for disease prediction. J. Comput. Sci. 13: 10-25 (2016) - [j3]Farhan Hassan Khan, Usman Qamar, Saba Bashir:
SWIMS: Semi-supervised subjective feature weighting and intelligent model selection for sentiment analysis. Knowl. Based Syst. 100: 97-111 (2016) - 2015
- [j2]Farhan Hassan Khan, Usman Qamar, Saba Bashir:
Building Normalized SentiMI to enhance semi-supervised sentiment analysis. J. Intell. Fuzzy Syst. 29(5): 1805-1816 (2015) - 2014
- [j1]Farhan Hassan Khan, Saba Bashir, Usman Qamar:
TOM: Twitter opinion mining framework using hybrid classification scheme. Decis. Support Syst. 57: 245-257 (2014) - [c1]Saba Bashir, Usman Qamar, Farhan Hassan Khan, M. Younus Javed:
An Efficient Rule-Based Classification of Diabetes Using ID3, C4.5, & CART Ensembles. FIT 2014: 226-231 - 2010
- [i2]Farhan Hassan Khan, Saba Bashir, M. Younus Javed, Aihab Khan, Malik Sikandar Hayat Khiyal:
QoS Based Dynamic Web Services Composition & Execution. CoRR abs/1003.1502 (2010) - [i1]Saba Bashir, Farhan Hassan Khan, M. Younus Javed, Aihab Khan, Malik Sikandar Hayat Khiyal:
Indexer Based Dynamic Web Services Discovery. CoRR abs/1003.1504 (2010)
Coauthor Index
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last updated on 2024-08-03 21:18 CEST by the dblp team
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