Muhammad E. H. Chowdhury

qatar university

H指数:51

被引数:1.2万

个人简介

暂无内容

教育背景

暂无内容

工作经历

暂无内容

荣誉奖项

暂无内容

Remodeling of Oncogene-Related Molecular Networks Following Bariatric Surgery: a Multi-Omics Study

癌基因相关分子网络在减肥手术后的重塑：一项多组学研究

Obesity Surgery

IF3.1

2026-10-050

OAAI

Atherosclerosis diagnosis from magnetic resonance images: an empirical approach to automate carotid vessel wall segmentation and feature-based prediction

基于磁共振图像的动脉粥样硬化诊断：一种自动颈动脉血管壁分割和基于特征预测的经验性方法

Railway Engineering Science

IF5.4

2026-09-280

PRE

Longitudinal Transcriptomic Remodeling of Adipose Tissue After Bariatric Surgery Revealed by Differential Expression and Explainable Machine Learning

通过差异表达和可解释机器学习揭示的减重手术后脂肪组织的纵向转录组重塑

Genes

IF2.8

2026-09-010

A novel detection-guided approach for multimodal brain tumor segmentation

一种基于检测引导的多模态脑肿瘤分割新方法

Biomedical Signal Processing and Control

IF4.9

2026-08-250

OAAI

Accurate Diabetic Foot Ulcer Segmentation: A Human-Machine Collaborative Approach with EfficientNet and Self-ONN FPN

基于EfficientNet和自ONN FPN的人机协作方法实现准确的糖尿病足溃疡分割

Cognitive Computation

IF4.3

2026-07-290

A comprehensive review of U-Net architectures for medical image segmentation: emerging trends and federated learning perspectives

医疗图像分割中U-Net架构的全面综述：新兴趋势和联邦学习视角

Neural Computing and Applications

IF4.5

2026-06-150

OAAI

ED-Net: A hybrid deep learning framework for precise polyp segmentation integrating EfficientNetB0 with Double U-Net architecture and Atrous Spatial Pyramid Pooling with test-time augmentation

ED-Net：一种结合EfficientNetB0与Double U-Net架构及空洞空间金字塔池化并采用测试时增强的混合深度学习框架，用于精确息肉分割

Biomedical Signal Processing and Control

IF4.9

2026-05-120

PRE

Spectral–spatial integration of hyperspectral imaging for glioblastoma classification with cross-modal attention and swin transformer

基于跨模态注意力与Swin Transformer的高光谱成像光谱-空间信息融合用于胶质母细胞瘤分类

Engineering Applications of Artificial Intelligence

IF8

2026-04-280

PRE

Machine Learning-Based Classification of Gliomas and Tumor Grades with SHAP-Guided Feature Interpretation

基于机器学习的胶质瘤和肿瘤分级分类及SHAP引导的特征解释

Genes

IF2.8

2026-04-270

OAAI

Can deep learning-based segmentation and classification improve the detection of renal cortical abnormalities?

基于深度学习的分割和分类能改善肾皮质异常的检测吗？

Neural Computing and Applications

IF4.5

2026-04-220

FootSegONN: an ensemble of Self-ONN-based models for diabetic foot ulcer segmentation

FootSegONN：基于Self-ONN模型的集成方法用于糖尿病足溃疡分割

Neural Computing and Applications

IF4.5

2026-03-050

OAAI

A comprehensive review of convolutional neural networks: foundations, enhancements and applications

卷积神经网络的综合综述：基础、改进与应用

Neural Computing and Applications

IF4.5

2026-02-180

OAAI

Correction: Senceroglu et al. Constructing an Intelligent Model Based on Support Vector Regression to Simulate the Solubility of Drugs in Polymeric Media. Pharmaceuticals 2022, 15, 1405

更正：Senceroglu等人基于支持向量回归构建智能模型，以模拟药物在聚合物介质中的溶解度。Pharmaceuticals 2022, 15, 1405

Pharmaceuticals

IF4.8

2026-01-150

OAAI

Sepsis mortality prediction using machine learning and deep learning - a systematic review

利用机器学习和深度学习进行脓毒症死亡预测——一项系统综述

BMC Medical Informatics and Decision Making

IF3.8

2025-12-100

OAAI

Privacy-preserving energy optimization via multi-stage federated learning for micro-moment recommendations

通过多阶段联邦学习实现隐私保护的微时刻推荐能耗优化

Sustainable Energy, Grids and Networks

IF0

2025-12-090

OAAI

Hybrid Neural Networks for Precise Hydronephrosis Classification Using Deep Learning

基于深度学习的混合神经网络用于精确的肾积水分类

Urology

IF2

2025-12-010

Bariatric metabolic surgery and cancer risk: Target trial emulation using iterative time distribution matching

减重代谢手术与癌症风险：基于迭代时间分布匹配的靶向试验模拟

Biomolecules and Biomedicine

IF2.2

2025-11-010

OAAI

Diffuse glioma classification with deep learning and explainability: addressing challenges in histopathology image analysis

基于深度学习和可解释性的弥漫性胶质瘤分类：解决组织病理学图像分析中的挑战

Soft Computing

IF2.5

2025-10-310

PRE

A Hybrid 3D CNN-LSTM Model with Soft Spatial Attention Mechanism for Accurate Hyperspectral Image Classification

一种带有软空间注意力机制的混合3D CNN-LSTM模型，用于精确的高光谱图像分类

Remote Sensing Applications: Society and Environment

IF0

2025-10-280

PRE

Real-time jute leaf disease classification using an explainable lightweight CNN via a supervised and semi-supervised self-training approach

基于监督和半监督自训练方法的可解释轻量级CNN的实时黄麻叶病害分类

Frontiers in Plant Science

IF4.8

2025-10-240

OAAI

Muhammad E. H. Chowdhury

个人简介

教育背景

工作经历

荣誉奖项

研究方向