A. S. M. Sanwar Hosen

Assistant Professor

Woosong University

South Korea

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A. S. M. Sanwar Hosen is an Assistant Professor at Woosong University, South Korea. His research areas include machine learning applications in healthcare, particularly in female infertility and brain tumor classification, as well as personalized education frameworks and real-time surveillance systems. He has contributed to multiple recent articles examining the intersection of artificial intelligence and clinical diagnostics, demonstrating a commitment to advancing technology in diverse fields.

A. S. M. Sanwar Hosen

Research Interests

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Articles (20)

Explainable Deep Ensemble Meta-Learning Framework for Brain Tumor Classification Using MRI Images

Temporal Trends and Machine Learning-Based Risk Prediction of Female Infertility: A Cross-Cohort Analysis Using NHANES Data (2015–2023)

Enhanced Brain Tumor Classification Using MobileNetV2: A Comprehensive Preprocessing and Fine-Tuning Approach

Multilayer stacking for polycystic ovary syndrome diagnosis

Personalized Course Recommendation System: A Multi-Model Machine Learning Framework for Academic Success

Advancing Personalized and Inclusive Education for Students with Disability Through Artificial Intelligence: Perspectives, Challenges, and Opportunities

Association of Polycystic Ovary Syndrome with Clinical, Physical, and Reproductive Factors: A Data-Driven Analysis

Real-Time Farm Surveillance Using IoT and YOLOv8 for Animal Intrusion Detection

A novel ensemble-based approach for Windows malware detection

A systematic analysis on machine learning classifiers with data pre-processing to detect anti-pattern from source code

An Advanced Job Scheduling Algorithmic Architecture to Reduce Energy Consumption and CO2 Emissions in Multi-Cloud

Digital Image Identification and Verification Using Maximum and Preliminary Score Approach with Watermarking for Security and Validation Enhancement

Machine learning and internet of things in industry 4.0: A review

Healthcare Internet of Things (H-IoT): Current Trends, Future Prospects, Applications, Challenges, and Security Issues

A New Unsupervised Technique to Analyze the Centroid and Frequency of Keyphrases from Academic Articles

SPTM-EC: A Security and Privacy-Preserving Task Management in Edge Computing for IIoT

Use of Machine Learning in Air Pollution Research: A Bibliographic Perspective

Energy Efficient Hybrid Relay-IRS-Aided Wireless IoT Network for 6G Communications

MSRM-IoT: A Reliable Resource Management for Cloud, Fog, and Mist-Assisted IoT Networks

Keyphrases Frequency Analysis From Research Articles: A Region-Based Unsupervised Novel Approach

Collaborators (6)

Yangwon LEE

In-Ho Ra

Divya Anand

Deepak Ghimire

Gi Hwan Cho

Md Abdus Samad

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