3 citations · 11 across the 20 of their papers we have counts for
22 papers
Tensor-based Fusion of Multi-modal Data for Predicting Cancer Risk Levels
Ali Anaissi, Yuanzhe Jia, Qishun Peng +3
Cancer diagnosis and treatment increasingly rely on multi-modal diagnostic technologies that generate high-dimensional datasets. Although these datasets are rich in pathological in…
CUNO: Curriculum and Preference Optimization for Stable Graph Unlearning under Mass Deletion
Chenhan Zhang, Ali Braytee, Madhushi Bandara +4
Graph unlearning removes the influence of designated training data from a trained graph model without retraining from scratch. However, existing methods suffer a sharp drop in mode…
Towards Automated Differential Diagnosis of Skin Diseases Using Deep Learning and Imbalance-Aware Strategies
Ali Anaissi, Ali Braytee, Weidong Huang +3
As dermatological conditions become increasingly common and the availability of dermatologists remains limited, there is a growing need for intelligent tools to support both patien…
Benchmarking Preprocessing and Integration Methods in Single-Cell Genomics
Ali Anaissi, Seid Miad Zandavi, Weidong Huang +4
Single-cell data analysis has the potential to revolutionize personalized medicine by characterizing disease-associated molecular changes at the single-cell level. Advanced single-…
RSVLM-QA: A Benchmark Dataset for Remote Sensing Vision Language Model-based Question Answering
Xing Zi, Jinghao Xiao, Yunxiao Shi +4
Visual Question Answering (VQA) in remote sensing (RS) is pivotal for interpreting Earth observation data. However, existing RS VQA datasets are constrained by limitations in annot…
Simplified Swarm Learning Framework for Robust and Scalable Diagnostic Services in Cancer Histopathology
Yanjie Wu, Yuhao Ji, Saiho Lee +3
The complexities of healthcare data, including privacy concerns, imbalanced datasets, and interoperability issues, necessitate innovative machine learning solutions. Swarm Learning…
Detecting and Understanding Hateful Contents in Memes Through Captioning and Visual Question-Answering
Ali Anaissi, Junaid Akram, Kunal Chaturvedi +1
Memes are widely used for humor and cultural commentary, but they are increasingly exploited to spread hateful content. Due to their multimodal nature, hateful memes often evade tr…
DualPrompt-MedCap: A Dual-Prompt Enhanced Approach for Medical Image Captioning
Yining Zhao, Ali Braytee, Mukesh Prasad
Medical image captioning via vision-language models has shown promising potential for clinical diagnosis assistance. However, generating contextually relevant descriptions with acc…
AeroLite: Tag-Guided Lightweight Generation of Aerial Image Captions
Xing Zi, Tengjun Ni, Xianjing Fan +4
Accurate and automated captioning of aerial imagery is crucial for applications like environmental monitoring, urban planning, and disaster management. However, this task remains c…
Vision Transformers with Autoencoders and Explainable AI for Cancer Patient Risk Stratification Using Whole Slide Imaging
Ahmad Hussein, Mukesh Prasad, Ali Anaissi +1
Cancer remains one of the leading causes of mortality worldwide, necessitating accurate diagnosis and prognosis. Whole Slide Imaging (WSI) has become an integral part of clinical w…
FedSAF: A Federated Learning Framework for Enhanced Gastric Cancer Detection and Privacy Preservation
Yuxin Miao, Xinyuan Yang, Hongda Fan +6
Gastric cancer is one of the most commonly diagnosed cancers and has a high mortality rate. Due to limited medical resources, developing machine learning models for gastric cancer…
Enhancing Sentiment Analysis through Multimodal Fusion: A BERT-DINOv2 Approach
Taoxu Zhao, Meisi Li, Kehao Chen +6
Multimodal sentiment analysis enhances conventional sentiment analysis, which traditionally relies solely on text, by incorporating information from different modalities such as im…
Visual and Text Prompt Segmentation: A Novel Multi-Model Framework for Remote Sensing
Xing Zi, Kairui Jin, Xian Tao +4
Pixel-level segmentation is essential in remote sensing, where foundational vision models like CLIP and Segment Anything Model(SAM) have demonstrated significant capabilities in ze…
Fine-Tuning LLMs for Reliable Medical Question-Answering Services
Ali Anaissi, Ali Braytee, Junaid Akram
We present an advanced approach to medical question-answering (QA) services, using fine-tuned Large Language Models (LLMs) to improve the accuracy and reliability of healthcare inf…
Explainable AI Methods for Multi-Omics Analysis: A Survey
Ahmad Hussein, Mukesh Prasad, Ali Braytee
Advancements in high-throughput technologies have led to a shift from traditional hypothesis-driven methodologies to data-driven approaches. Multi-omics refers to the integrative a…
Optimized Biomedical Question-Answering Services with LLM and Multi-BERT Integration
Cheng Qian, Xianglong Shi, Shanshan Yao +6
We present a refined approach to biomedical question-answering (QA) services by integrating large language models (LLMs) with Multi-BERT configurations. By enhancing the ability to…
Integration of Self-Supervised BYOL in Semi-Supervised Medical Image Recognition
Hao Feng, Yuanzhe Jia, Ruijia Xu +3
Image recognition techniques heavily rely on abundant labeled data, particularly in medical contexts. Addressing the challenges associated with obtaining labeled data has led to th…
Damage GAN: A Generative Model for Imbalanced Data
Ali Anaissi, Yuanzhe Jia, Ali Braytee +2
This study delves into the application of Generative Adversarial Networks (GANs) within the context of imbalanced datasets. Our primary aim is to enhance the performance and stabil…
SS-CPGAN: Self-Supervised Cut-and-Pasting Generative Adversarial Network for Object Segmentation
Kunal Chaturvedi, Ali Braytee, Jun Li +1
This paper proposes a novel self-supervised based Cut-and-Paste GAN to perform foreground object segmentation and generate realistic composite images without manual annotations. We…
Conditional Variational Autoencoder with Balanced Pre-training for Generative Adversarial Networks
Yuchong Yao, Xiaohui Wangr, Yuanbang Ma +5
Class imbalance occurs in many real-world applications, including image classification, where the number of images in each class differs significantly. With imbalanced data, the ge…
Learning Discriminative Features using Multi-label Dual Space
Ali Braytee, Wei Liu
Multi-label learning handles instances associated with multiple class labels. The original label space is a logical matrix with entries from the Boolean domain $\in \left \{ 0,1 \r…
Multi-Objective Variational Autoencoder: an Application for Smart Infrastructure Maintenance
Ali Anaissi, Seid Miad Zandavi
Multi-way data analysis has become an essential tool for capturing underlying structures in higher-order data sets where standard two-way analysis techniques often fail to discover…