Big Data Analytics &
Clinical AI
Led by Dr. Yash Patel, we bridge the gap between Computer Vision, NLP, and Generative AI. Our research spans wound care, neuroimaging, and corporate analytics to drive data-informed decision making.
Core Research Areas
We bridge the gap between computer vision theory, data analytics, and clinical application.
Biomedical Image Analysis
Developing U-Net and Transformer architectures for precise tissue delineation in wounds, tumors, and X-rays.
Generative AI & NLP
Leveraging LLMs, VLMs, and LSTM networks for clinical reporting, corporate culture analysis, and strategy evaluation.
Predictive Analytics
Applied data science for disease prediction, early detection of Alzheimer’s, and business intelligence.
Active Projects
Our graduate and undergraduate students work on real-world datasets with clinical and industrial impact.
Multi-Class Wound Classification
Developing deep learning models to automatically classify different types of wounds from images, streamlining diagnosis and treatment planning.
Breast Mass Segmentation
Binary segmentation of masses in mammograms to precisely isolate regions of interest, aiding radiologists in early cancer detection.
Corporate Culture Analytics (LSTM)
Utilizing Long Short-Term Memory (LSTM) networks to analyze organizational text data and objectively measure corporate culture metrics.
SOAR Framework Analysis with LLMs
Leveraging Large Language Models to automatically evaluate organizational strategies against the SOAR (Strengths, Opportunities, Aspirations, Results) framework.
Foot Bone X-Ray Segmentation
Automated segmentation of bone structures in foot X-rays to assist clinicians in diagnosing fractures and structural deformities.
Early Detection of Alzheimer’s
Building AI models to detect subtle, early-stage biomarkers of Alzheimer’s disease from neuroimaging data for timely intervention.
Wound Tissue Segmentation
Precise segmentation of necrotic, slough, and granulation tissue within wounds to objectively monitor healing progress over time.
X-Ray Report Generation using VLMs
Exploring Vision-Language Models (VLMs) to generate automated, descriptive clinical reports directly from medical imaging.
Lab Members
Dr. Yash Patel
Dr. Patel leads the Big Data Analytics Lab at Lawrence Technological University. He serves as an editor for Scientific Reports (Nature Portfolio) and specializes in applying deep learning to complex medical imaging challenges.
Interested in our research?
We are always looking for motivated students and collaborators to join our team.
Dr. Yash Patel
Lab Director
Please reach out via email for research opportunities, collaborations, or general inquiries.
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