8 citations · 15 across the 13 of their papers we have counts for
13 papers
EDUE: Expert Disagreement-Guided One-Pass Uncertainty Estimation for Medical Image Segmentation
Kudaibergen Abutalip, Numan Saeed, Ikboljon Sobirov +3
Deploying deep learning (DL) models in medical applications relies on predictive performance and other critical factors, such as conveying trustworthy predictive uncertainty. Uncer…
Advanced Tumor Segmentation in Medical Imaging: An Ensemble Approach for BraTS 2023 Adult Glioma and Pediatric Tumor Tasks
Fadillah Maani, Anees Ur Rehman Hashmi, Mariam Aljuboory +3
Automated segmentation proves to be a valuable tool in precisely detecting tumors within medical images. The accurate identification and segmentation of tumor types hold paramount…
HuLP: Human-in-the-Loop for Prognosis
Muhammad Ridzuan, Mai Kassem, Numan Saeed +2
This paper introduces HuLP, a Human-in-the-Loop for Prognosis model designed to enhance the reliability and interpretability of prognostic models in clinical contexts, especially w…
Reinforcement Learning for Solving Stochastic Vehicle Routing Problem with Time Windows
Zangir Iklassov, Ikboljon Sobirov, Ruben Solozabal +1
This paper introduces a reinforcement learning approach to optimize the Stochastic Vehicle Routing Problem with Time Windows (SVRP), focusing on reducing travel costs in goods deli…
Reinforcement Learning for Solving Stochastic Vehicle Routing Problem
Zangir Iklassov, Ikboljon Sobirov, Ruben Solozabal +1
This study addresses a gap in the utilization of Reinforcement Learning (RL) and Machine Learning (ML) techniques in solving the Stochastic Vehicle Routing Problem (SVRP) that invo…
Structurally Different Neural Network Blocks for the Segmentation of Atrial and Aortic Perivascular Adipose Tissue in Multi-centre CT Angiography Scans
Ikboljon Sobirov, Cheng Xie, Muhammad Siddique +26
Since the emergence of convolutional neural networks (CNNs) and, later, vision transformers (ViTs), deep learning architectures have predominantly relied on identical block types w…
Diagnosis and Prognosis of Head and Neck Cancer Patients using Artificial Intelligence
Ikboljon Sobirov
Cancer is one of the most life-threatening diseases worldwide, and head and neck (H&N) cancer is a prevalent type with hundreds of thousands of new cases recorded each year. Clinic…
MGMT promoter methylation status prediction using MRI scans? An extensive experimental evaluation of deep learning models
Numan Saeed, Muhammad Ridzuan, Hussain Alasmawi +2
The number of studies on deep learning for medical diagnosis is expanding, and these systems are often claimed to outperform clinicians. However, only a few systems have shown medi…
TMSS: An End-to-End Transformer-based Multimodal Network for Segmentation and Survival Prediction
Numan Saeed, Ikboljon Sobirov, Roba Al Majzoub +1
When oncologists estimate cancer patient survival, they rely on multimodal data. Even though some multimodal deep learning methods have been proposed in the literature, the majorit…
Super Images -- A New 2D Perspective on 3D Medical Imaging Analysis
Ikboljon Sobirov, Numan Saeed, Mohammad Yaqub
In medical imaging analysis, deep learning has shown promising results. We frequently rely on volumetric data to segment medical images, necessitating the use of 3D architectures,…
An Ensemble Approach for Patient Prognosis of Head and Neck Tumor Using Multimodal Data
Numan Saeed, Roba Al Majzoub, Ikboljon Sobirov +1
Accurate prognosis of a tumor can help doctors provide a proper course of treatment and, therefore, save the lives of many. Traditional machine learning algorithms have been eminen…
Object Detection in Aerial Images: What Improves the Accuracy?
Hashmat Shadab Malik, Ikboljon Sobirov, Abdelrahman Mohamed
Object detection is a challenging and popular computer vision problem. The problem is even more challenging in aerial images due to significant variation in scale and viewpoint in…
Automatic Segmentation of Head and Neck Tumor: How Powerful Transformers Are?
Ikboljon Sobirov, Otabek Nazarov, Hussain Alasmawi +1
Cancer is one of the leading causes of death worldwide, and head and neck (H&N) cancer is amongst the most prevalent types. Positron emission tomography and computed tomography are…