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Analysis of Customer Churn Classification for Sinarmas Syariah Lhokseumawe Insurance Services Using Deep Learning Tabnet and Explainable AI

Syarifah Muliana, Taufiq Taufiq, Munirul Ula • Journal of Applied Informatics and Computing (2026)

Customer churn is a major challenge in the insurance industry because it directly affects customer retention, business sustainability, and company profitability. Early identification of customers at risk of churn is therefore essential for ...

DOAJ Open Access (DOAJ) DOI: 10.30871/jaic.v10i3.12864

Compilation of training datasets for use of convolutional neural networks supporting automatic inspection processes in industry 4.0 based electronic manufacturing

A. I. M. Schwebig, A. I. M. Schwebig, R. Tutsch • Journal of Sensors and Sensor Systems (2020)

Ensuring the highest quality standards at competitive prices is one of the greatest challenges in the manufacture of electronic products. The identification of flaws has the uppermost priority in the field of automotive electronics, particu...

DOAJ Open Access (DOAJ) DOI: 10.5194/jsss-9-167-2020

Multimodal artificial intelligence for subepithelial lesion classification and characterization: a multicenter comparative study (with video)

Jiao Li, Xiaojuan Jing, Qin Zhang, Xiaoxiang Wang et al. • BMC Medical Informatics and Decision Making (2025)

Abstract Background Subepithelial lesions (SELs) present significant diagnostic challenges in gastrointestinal endoscopy, particularly in differentiating malignant types, such as gastrointestinal stromal tumors (GISTs) and neuroendocrine tu...

DOAJ Open Access (DOAJ) DOI: 10.1186/s12911-025-03147-9

A review of deep learning in image recognition

Myeongsuk Pak, Sang-Hoon Kim • International Conference on Computer Applications and Information Processing Technology (CAIPT) (2017)

Deep learning has been the core topic in machine learning and convolutional neural network is one of the most prominent approaches. Convolutional neural network has won numerous competitions in recent years. It has outstanding results in im...

OPENALEX DOI: https://doi.org/10.1109/caipt.2017.8320684

Deep Learning for Spatio-Temporal Data Mining: A Survey

Senzhang Wang, Jiannong Cao, Philip S. Yu • IEEE Transactions on Knowledge and Data Engineering (2020)

With the fast development of various positioning techniques such as Global Position System (GPS), mobile devices and remote sensing, spatio-temporal data has become increasingly available nowadays. Mining valuable knowledge from spatio-temp...

OPENALEX Open Access DOI: https://doi.org/10.1109/tkde.2020.3025580

Greedy Broad Learning System

Weitong Ding, Yubo Tian, Shudan Han, Huining Yuan • IEEE Access (2021)

In order to overcome the extremely time-consuming drawback of deep learning (DL), broad learning system (BLS) was proposed as an alternative method. This model is simple, fast, and easy to update. To ensure the fitting and generalization ab...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2021.3084610

A System for the Detection of Polyphonic Sound on a University Campus Based on CapsNet-RNN

Liyan Luo, Liujun Zhang, Mei Wang, Zhenghong Liu et al. • IEEE Access (2021)

In recent decades, surveillance and home security systems based on video analysis have been proposed for the automatic detection of abnormal situations. Nevertheless, in several real applications, it may be easier to detect a given event fr...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2021.3123970

Automated deep bottleneck residual 82-layered architecture with Bayesian optimization for the classification of brain and common maternal fetal ultrasound planes

Fatima Rauf, Muhammad Attique Khan, Ali Kashif Bashir, Kiran Jabeen et al. • Frontiers in Medicine (2023)

Despite a worldwide decline in maternal mortality over the past two decades, a significant gap persists between low- and high-income countries, with 94% of maternal mortality concentrated in low and middle-income nations. Ultrasound serves ...

DOAJ Open Access (DOAJ) DOI: 10.3389/fmed.2023.1330218

HDLTex: Hierarchical Deep Learning for Text Classification

Kamran Kowsari, Donald E. Brown, Mojtaba Heidarysafa, Kiana Jafari Meimandi et al. • International Conference on Machine Learning and Applications (2017)

Increasingly large document collections require improved information processing methods for searching, retrieving, and organizing text. Central to these information processing methods is document classification, which has become an importan...

OPENALEX Open Access DOI: https://doi.org/10.1109/icmla.2017.0-134

Review: Deep Learning on 3D Point Clouds

Saifullahi Aminu Bello, Shangshu Yu, Cheng Wang, Jibril Muhammad Adam et al. • Remote Sensing (2020)

A point cloud is a set of points defined in a 3D metric space. Point clouds have become one of the most significant data formats for 3D representation and are gaining increased popularity as a result of the increased availability of acquisi...

OPENALEX cc-by DOI: https://doi.org/10.3390/rs12111729

Intelligent diagnosis with Chinese electronic medical records based on convolutional neural networks

Xiaozheng Li, Huazhen Wang, Huixin He, Jixiang Du et al. • BMC Bioinformatics (2019)

Abstract Background Benefiting from big data, powerful computation and new algorithmic techniques, we have been witnessing the renaissance of deep learning, particularly the combination of natural language processing (NLP) and deep neural n...

DOAJ Open Access (DOAJ) DOI: 10.1186/s12859-019-2617-8

Deep learning for cardiovascular medicine: a practical primer

Chayakrit Krittanawong, Kipp W. Johnson, Robert S. Rosenson, Zhen Wang et al. • European Heart Journal (2019)

Deep learning (DL) is a branch of machine learning (ML) showing increasing promise in medicine, to assist in data classification, novel disease phenotyping and complex decision making. Deep learning is a form of ML typically implemented via...

OPENALEX Open Access DOI: https://doi.org/10.1093/eurheartj/ehz056 PMC: 6600129

A Survey on Deep Learning for Software Engineering

Yanming Yang, Xin Xia, David Lo, John Grundy • ACM Computing Surveys (2021)

In 2006, Geoffrey Hinton proposed the concept of training “Deep Neural Networks (DNNs)” and an improved model training method to break the bottleneck of neural network development. More recently, the introduction of AlphaGo in 2016 demonstr...

OPENALEX Open Access DOI: https://doi.org/10.1145/3505243

Deep Learning for ECG Classification

Boris Pyakillya, Н. Я. Казаченко, N Mikhailovsky • Journal of Physics Conference Series (2017)

The importance of ECG classification is very high now due to many current medical applications where this problem can be stated. Currently, there are many machine learning (ML) solutions which can be used for analyzing and classifying ECG d...

OPENALEX cc-by DOI: https://doi.org/10.1088/1742-6596/913/1/012004

Integrative multiomics-histopathology analysis for breast cancer classification

Yasha Ektefaie, William Yuan, Deborah A. Dillon, Nancy U. Lin et al. • npj Breast Cancer (2021)

Abstract Histopathologic evaluation of biopsy slides is a critical step in diagnosing and subtyping breast cancers. However, the connections between histology and multi-omics status have never been systematically explored or interpreted. We...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41523-021-00357-y