Md. Shahin Ali
PhD Fellow
University of Iowa
BSc, Dept. of Biomedical Engineering, IU
Md Shahin Ali is currently pursuing a PhD in the Department of Biomedical Engineering at the University of Iowa, Iowa City, Iowa, USA. He holds a B.Sc. in Engineering from the Department of Biomedical Engineering at Islamic University, Bangladesh. From June 2020 to July 2024, he worked as a research assistant at the Bio-Imaging Research Lab at Islamic University. Since August 2024, he has been serving as a research assistant in the Laboratory of Quantitative and Dynamic Magnetic Resonance Imaging at the University of Iowa. His diverse research interests include Medical Image Processing, Medical Image Reconstruction, Inverse Problems, Machine Learning, and Deep Learning, reflecting his dedication to advancing the field of Biomedical Engineering.
Google Scholar Profile
Name: Md Shahin Ali
Citation Count: 1068
Published Papers:
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An enhanced technique of skin cancer classification using deep convolutional neural network with transfer learning models
Cited by: 402 | Year: 2021 -
Brain tumor detection in MR image using superpixels, principal component analysis and template based K-means clustering algorithm
Cited by: 171 | Year: 2021 -
Deep transfer learning approaches for Monkeypox disease diagnosis
Cited by: 91 | Year: 2023 -
Melanoma skin lesions classification using deep convolutional neural network with transfer learning
Cited by: 51 | Year: 2021 -
Automated Detection and Characterization of Colon Cancer with Deep Convolutional Neural Networks
Cited by: 47 | Year: 2022 -
Monkeypox diagnosis with interpretable deep learning
Cited by: 32 | Year: 2023 -
Alzheimer’s disease detection using m-random forest algorithm with optimum features extraction
Cited by: 29 | Year: 2021 -
A Novel Approach for Best Parameters Selection and Feature Engineering to Analyze and Detect Diabetes: Machine Learning Insights
Cited by: 27 | Year: 2023 -
Enhancing lung abnormalities detection and classification using a Deep Convolutional Neural Network and GRU with explainable AI: A promising approach for accurate diagnosis
Cited by: 25 | Year: 2023 -
Human brain tumor detection using k-means segmentation and improved support vector machine
Cited by: 23 | Year: 2020 -
Cardiovascular disease identification using a hybrid CNN-LSTM model with explainable AI
Cited by: 22 | Year: 2023 -
Unlocking the potential of XAI for improved alzheimer’s disease detection and classification using a ViT-GRU model
Cited by: 20 | Year: 2024 -
Transfer learning and local interpretable model agnostic based visual approach in monkeypox disease detection and classification: A deep learning insights
Cited by: 15 | Year: 2022 -
Enhancing monkeypox diagnosis and explanation through modified transfer learning, vision transformers, and federated learning
Cited by: 14 | Year: 2024 -
Efficient deep learning-based data-centric approach for autism spectrum disorder diagnosis from facial images using explainable AI
Cited by: 14 | Year: 2023 -
Enhancing and improving the performance of imbalanced class data using novel GBO and SSG: A comparative analysis
Cited by: 11 | Year: 2024 -
Enhancing Atrial Fibrillation detection accuracy: A wavelet transform filtered single lead ECG signal analysis with artificial neural networks and novel feature extraction
Cited by: 11 | Year: 2023 -
An ensemble classification approach for cervical cancer prediction using behavioral risk factors
Cited by: 10 | Year: 2024 -
Enhancing lung abnormalities diagnosis using hybrid DCNN-ViT-GRU model with explainable AI: A deep learning approach
Cited by: 10 | Year: 2024 -
Active learning on medical image
Cited by: 9 | Year: 2023