A5040777498- Colorectal Cancer Screening and Detection
- Gastrointestinal Bleeding Diagnosis and Treatment
- AI in cancer detection
- Radiomics and Machine Learning in Medical Imaging
- Image Retrieval and Classification Techniques
- Natural Language Processing Techniques
- Gastric Cancer Management and Outcomes
- Topic Modeling
- Speech and dialogue systems
- Advanced Steganography and Watermarking Techniques
- Generative Adversarial Networks and Image Synthesis
- Machine Learning and Data Classification
- Retinal Imaging and Analysis
- Evolutionary Algorithms and Applications
- Explainable Artificial Intelligence (XAI)
- Machine Learning in Healthcare
- COVID-19 diagnosis using AI
- Metaheuristic Optimization Algorithms Research
- Rhetoric and Communication Studies
- Artificial Intelligence in Healthcare and Education
- Advanced Data Compression Techniques
University of Virginia
2019-2023
Flint Institute Of Arts
2021
Weatherford College
2021
Deep convolutional neural networks (CNNs) have been successful for a wide range of computer vision tasks including image classification. A specific area application lies in digital pathology pattern recognition tissue-based diagnosis gastrointestinal (GI) diseases. This domain can utilize CNNs to translate histopathological images into precise diagnostics. is challenging since these complex biopsies are heterogeneous and require multiple levels assessment. mainly due structural similarities...
With the decreasing cost of data collection, space variables or features that can be used to characterize a particular predictor interest continues grow exponentially. Therefore, identifying most characterizing minimizes variance without jeopardizing bias our models is critical successfully training machine learning model. In addition, such for interpretability, prediction accuracy and optimal computation cost. While statistical methods as subset selection, shrinkage, dimensionality...
Effective and rapid detection of lesions in the Gastrointestinal tract is critical to gastroenterologist's response some life-threatening diseases. Wireless Capsule Endoscopy (WCE) has revolutionized traditional endoscopy procedure by allowing gastroenterologists visualize entire GI non-invasively. Once tiny capsule swallowed, it sequentially capture images at about 2 6 frames per second (fps). A single video can last up 8 hours producing between 30,000 100,000 images. Automating containing...
In this paper, we propose a distributed Generative Adversarial Networks (discGANs) to generate synthetic tabular data specific the healthcare domain. While using GANs images has been well studied, little no attention given generation of data. Modeling distributions discrete and continuous is non-trivial task with high utility. We applied discGAN model non-Gaussian multi-modal generated 249,000 records from original 2,027 eICU dataset. evaluated performance machine learning efficacy,...
In political discourse and geopolitical analysis, national leaders words hold profound significance, often serving as harbingers of pivotal historical moments. From impassioned rallying cries to calls for caution, presidential speeches preceding major conflicts encapsulate the multifaceted dynamics decision-making at apex governance. This project aims use deep learning techniques decode subtle nuances underlying patterns US rhetoric that may signal involvement in wars. While accurate...
Most past research in the area of serious games for simulation has focused on with constrained multiple-choice based dialogue systems. Recent advancements natural language processing make free-input text classification-based systems more feasible, but an effective framework collecting training data such not yet been developed. This paper presents methods and generating a system. Various crowdsourcing prompt types are presented. A binary category system, which increases fidelity labeling to...
Existing simulations designed for cultural and interpersonal skill training rely on pre-defined responses with a menu option selection interface. Using multiple-choice interface restricting trainees' may limit the ability to apply lessons in real life situations. This systems also uses simplistic evaluation model, where selected options are marked as either correct or incorrect. model not capture sufficient information that could drive an adaptive feedback mechanism improve awareness. paper...
Introduction: Technical burdens and time-intensive review processes limit the practical utility of video capsule endoscopy (VCE). Artificial intelligence (AI) is poised to address these limitations, but intersection AI VCE reveals challenges that must first be overcome. We identified five address. Challenge #1: data are stochastic contains significant artifact. #2: interpretation cost-intensive. #3: inherently imbalanced. #4: Existing AIMLT computationally cumbersome. #5: Clinicians hesitant...
Physicians use Capsule Endoscopy (CE) as a non-invasive and non-surgical procedure to examine the entire gastrointestinal (GI) tract for diseases abnormalities. A single CE examination could last between 8 11 hours generating up 80,000 frames which is compiled video. have review analyze video identify abnormalities or before making diagnosis. This task can be very tedious, time consuming prone error. While only little frame may capture useful content that relevant physicians' final...
Temporal abnormality localization in long Wireless Capsule Endoscopy (WCE) videos is an important problem. The cost of obtaining frame level label for WCE prohibitive. In this paper, we propose end-to-end temporal using only weak video labels. Physicians use (CE) as a non-surgical and non-invasive method to examine the entire digestive tract order diagnose diseases or abnormalities. While CE has revolutionized traditional endoscopy procedures, single examination could last up 8 hours...
Deep convolutional neural networks(CNNs) have been successful for a wide range of computer vision tasks, including image classification. A specific area the application lies in digital pathology pattern recognition tissue-based diagnosis gastrointestinal(GI) diseases. This domain can utilize CNNs to translate histopathological images into precise diagnostics. is challenging since these complex biopsies are heterogeneous and require multiple levels assessment. mainly due structural...
Temporal activity localization in long videos is an important problem. The cost of obtaining frame level label for Wireless Capsule Endoscopy (WCE) prohibitive. In this paper, we propose end-to-end temporal abnormality WCE using only weak video labels. Physicians use (CE) as a non-surgical and non-invasive method to examine the entire digestive tract order diagnose diseases or abnormalities. While CE has revolutionized traditional endoscopy procedures, single examination could last up 8...