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Hala M. Alshamlan

Also published under: Hala Alshamlan, Hala AlShamlan

Publications

Citations

199

Publications by Year

20182025

Co-Authors:

Areej Al SahowKhawlah AlBabtainRand AlMahmoudSara AlTuwaijriReham Alabduljabbar

Show All Co-Authors (12)

Hala M. Alshamlan

Also published under: Hala Alshamlan, Hala AlShamlan

Affiliation

Department of Information Technology

College of Computer and Information Sciences

King Saud University, Riyadh, Saudi Arabia

Publication Topics

Cancer Classification,
Cancer Datasets,
Classification Accuracy,
Feature Selection Methods,
Gene Selection,
Learning Algorithms,
Support Vector Machine,
Ant Colony Optimization,
Artificial Neural Network,
Autoencoder,
Bat Algorithm,
Bio-inspired Algorithm

Biography

Hala Alshamlan received the Ph.D. degree in computer science from King Saud University, in 2015. From 2016 to 2017, she was a Research Fellow with the Kamm Lab, Mechanical Engineering Department, Massachusetts Institute of Technology (MIT), Cambridge, USA. In 2018, she was leading of Data Science for Global Health track at MIT Hacking Medicine, Riyadh, Saudi Arabia.,She is currently an Assistant Professor with the Information Technology Department, College of Computer and Information Sciences, King Saud University (KSU). She is interested in data science and big data analytics. She developed many novel algorithms that discover the cancer biomarker from genomic data. All these algorithms have been published on high impact journals. Her resea...

Publications

Citations

199

Publications by Year

20182025

Co-Authors:

Areej Al Sahow
Khawlah AlBabtain
Rand AlMahmoud
Sara AlTuwaijri
Reham Alabduljabbar

Show All Co-Authors (12)

Author's Published Works

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Showing 1-9 of 9 results

Journals (5)

Conferences (4)

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Hala Alshamlan(5)
Nada Almugren(3)
Hala M. Alshamlan(2)
Hala AlShamlan(1)
Hala M Alshamlan(1)
Department of Information Technology, King Saud University, Riyadh, Saudi Arabia(2)
Information Technology Department, King Saud University, Riyadh, Saudi Arabia(2)
College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia(1)
College of Computer and Information Sciences, Information Technology Department, King Saud University, KSA, Ryiadh(1)
Information Technology Department, King Saud Universty Riyadh, Saudi Arabia(1)
IEEE Access(5)
2018 21st Saudi Computer Society National Computer Conference (NCC)(1)
2019 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)(1)
2020 11th International Conference on Information and Communication Systems (ICICS)(1)
2023 Intelligent Methods, Systems, and Applications (IMSA)(1)
IEEE(9)
Giza, Egypt(1)
Irbid, Jordan(1)
Riyadh, Saudi Arabia(1)
Siena, Italy(1)
Gene Selection(7)
Support Vector Machine(7)
Classification Accuracy(6)
Feature Selection Methods(6)
Support Vector Machine Classifier(6)

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Results

Performance Evaluation of Hybrid Bio-Inspired and Deep Learning Algorithms in Gene Selection and Cancer Classification

Shahad S. Alkamli;Hala M. Alshamlan

IEEE Access

Year: 2025 | Volume: 13 | Journal Article |

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Cancer classification based on gene expression data is a critical challenge in modern bioinformatics, requiring efficient and accurate feature selection methods. This study explores the performance of hybrid bio-inspired algorithms and deep learning techniques for gene selection and cancer classification. Hybrid bio-inspired methods, inspired by natural optimization processes, have demonstrated si...Show More

Performance Evaluation of Hybrid Bio-Inspired and Deep Learning Algorithms in Gene Selection and Cancer Classification

Shahad S. Alkamli;Hala M. Alshamlan

IEEE Access

Year: 2025 | Volume: 13 | Journal Article |

Personalized Car Recommendations Using Knowledge-Based Methods

Reham Alabduljabbar;Maha Alghamdi;Hala Alshamlan

2023 Intelligent Methods, Systems, and Applications (IMSA)

Year: 2023 | Conference Paper |

Cited by: Papers (2)

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The process of selecting a new car can be a complex and challenging task due to the wide range of cars available in the market. To address this issue, this paper proposes a car recommendation system that employs a knowledge-based recommender approach. The system utilizes a variety of car features, including brand, color, year, gear type, number of seats, and price, to provide personalized recommen...Show More

Personalized Car Recommendations Using Knowledge-Based Methods

Reham Alabduljabbar;Maha Alghamdi;Hala Alshamlan

2023 Intelligent Methods, Systems, and Applications (IMSA)

Year: 2023 | Conference Paper |

A Comprehensive Survey of Recent Hybrid Feature Selection Methods in Cancer Microarray Gene Expression Data

Halah Almazrua;Hala Alshamlan

IEEE Access

Year: 2022 | Volume: 10 | Journal Article |

Cited by: Papers (9)

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In the diagnosis and treatment of cancer, cancer classification is a vital issue. Gene selection is much needed to solve the high dimensionality issue in microarray data, small sample size, and noisy. The best way to classify cancer is to select those genes that hold the most informative ones, and this process contributes significantly to the classification performance of microarrays. In this surv...Show More

A Comprehensive Survey of Recent Hybrid Feature Selection Methods in Cancer Microarray Gene Expression Data

Halah Almazrua;Hala Alshamlan

IEEE Access

Year: 2022 | Volume: 10 | Journal Article |

An Effective Filter Method Towards the Performance Improvement of FF-SVM Algorithm

Hala M Alshamlan

IEEE Access

Year: 2021 | Volume: 9 | Journal Article |

Cited by: Papers (4)

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Fining effective and informative biomarker genes form microarray is very challenging. In order to develop an hybrid gene selection algorithm, numerous filter feature selection algorithms have been previously reported. This research paper aims to identify the filter method that will improve the performance of our previously proposed FF-SVM algorithm to find the minimum number of accurate genes that...Show More

An Effective Filter Method Towards the Performance Improvement of FF-SVM Algorithm

Hala M Alshamlan

IEEE Access

Year: 2021 | Volume: 9 | Journal Article |

A Gene Prediction Function for Type 2 Diabetes Mellitus using Logistic Regression

Hala Alshamlan;Hind Bin Taleb;Areej Al Sahow

2020 11th International Conference on Information and Communication Systems (ICICS)

Year: 2020 | Conference Paper |

Cited by: Papers (8)

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Type 2 diabetes mellitus (T2D), is a complex diabetes disease that is caused by high blood sugar, insulin resistance, and a relative lack of insulin. Many studies are trying to predict variant genes that causes this disease by using a sample disease model. In this paper we predict diabetic and normal persons by using fisher score feature selection, chi-2 feature selection and Logistic Regression s...Show More

A Gene Prediction Function for Type 2 Diabetes Mellitus using Logistic Regression

Hala Alshamlan;Hind Bin Taleb;Areej Al Sahow

2020 11th International Conference on Information and Communication Systems (ICICS)

Year: 2020 | Conference Paper |

New Bio-Marker Gene Discovery Algorithms for Cancer Gene Expression Profile

Nada Almugren;Hala M. Alshamlan

IEEE Access

Year: 2019 | Volume: 7 | Journal Article |

Cited by: Papers (16)

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Several hybrid gene selection algorithms for cancer classification that employ bio-inspired evolutionary wrapper algorithm have been proposed in the literature and show good classification accuracy. In our recent previous work, we proposed a new wrapper gene selection method based-on firefly algorithm named FF-SVM. In this work, we will improve the classification performance of FF-SVM algorithm by...Show More

New Bio-Marker Gene Discovery Algorithms for Cancer Gene Expression Profile

Nada Almugren;Hala M. Alshamlan

IEEE Access

Year: 2019 | Volume: 7 | Journal Article |

FF-SVM: New FireFly-based Gene Selection Algorithm for Microarray Cancer Classification

Nada Almugren;Hala Alshamlan

2019 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)

Year: 2019 | Conference Paper |

Cited by: Papers (16)

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Several bio-inspired evolutionary based feature selection algorithms for microarray data classification have been proposed in the literature and show a good performance. In this research we proposed a wrapper feature selection algorithm for classifying cancer microarray gene expression profile that uses FireFly algorithm along with SVM classifier named FF-SVM. Support vector machine SVM classifier...Show More

FF-SVM: New FireFly-based Gene Selection Algorithm for Microarray Cancer Classification

Nada Almugren;Hala Alshamlan

2019 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)

Year: 2019 | Conference Paper |

A Survey on Hybrid Feature Selection Methods in Microarray Gene Expression Data for Cancer Classification

Nada Almugren;Hala Alshamlan

IEEE Access

Year: 2019 | Volume: 7 | Journal Article |

Cited by: Papers (144)

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The emergence of DNA Microarray technology has enabled researchers to analyze the expression level of thousands of genes simultaneously. The Microarray data analysis is the process of finding the most informative genes as well as remove redundant and irrelevant genes. One of the most important applications of the Microarray data analysis is cancer classification. However, the curse of dimensionali...Show More

A Survey on Hybrid Feature Selection Methods in Microarray Gene Expression Data for Cancer Classification

Nada Almugren;Hala Alshamlan

IEEE Access

Year: 2019 | Volume: 7 | Journal Article |

Cancer Biomarker Rule Discovery

Hala AlShamlan;Lamia Almoajil;Khawlah AlBabtain;Manal BinShalaan;Rand AlMahmoud;Sara AlTuwaijri

2018 21st Saudi Computer Society National Computer Conference (NCC)

Year: 2018 | Conference Paper |

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This paper aims to obtain valuable knowledge from the biological dataset by providing a tool that applies normalization to the dataset and then reduce the high dimensionality by selecting only informative genes in order to extract rules. Each process supported by visualization representation.Show More

Cancer Biomarker Rule Discovery

Hala AlShamlan;Lamia Almoajil;Khawlah AlBabtain;Manal BinShalaan;Rand AlMahmoud;Sara AlTuwaijri

2018 21st Saudi Computer Society National Computer Conference (NCC)

Year: 2018 | Conference Paper |

Author details

Hala M. Alshamlan

Hala M. Alshamlan

Affiliation

Publication Topics

Biography

Showing 1-9 of 9 results

Show

Performance Evaluation of Hybrid Bio-Inspired and Deep Learning Algorithms in Gene Selection and Cancer Classification

Performance Evaluation of Hybrid Bio-Inspired and Deep Learning Algorithms in Gene Selection and Cancer Classification

Personalized Car Recommendations Using Knowledge-Based Methods

Personalized Car Recommendations Using Knowledge-Based Methods

A Comprehensive Survey of Recent Hybrid Feature Selection Methods in Cancer Microarray Gene Expression Data

A Comprehensive Survey of Recent Hybrid Feature Selection Methods in Cancer Microarray Gene Expression Data

An Effective Filter Method Towards the Performance Improvement of FF-SVM Algorithm

An Effective Filter Method Towards the Performance Improvement of FF-SVM Algorithm

A Gene Prediction Function for Type 2 Diabetes Mellitus using Logistic Regression

A Gene Prediction Function for Type 2 Diabetes Mellitus using Logistic Regression

New Bio-Marker Gene Discovery Algorithms for Cancer Gene Expression Profile

New Bio-Marker Gene Discovery Algorithms for Cancer Gene Expression Profile

FF-SVM: New FireFly-based Gene Selection Algorithm for Microarray Cancer Classification

FF-SVM: New FireFly-based Gene Selection Algorithm for Microarray Cancer Classification

A Survey on Hybrid Feature Selection Methods in Microarray Gene Expression Data for Cancer Classification

A Survey on Hybrid Feature Selection Methods in Microarray Gene Expression Data for Cancer Classification

Cancer Biomarker Rule Discovery

Cancer Biomarker Rule Discovery

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