Early Detection of Breast Cancer with AI enhanced workflows
Principal Investigator
Name
Dr. Tariq Mahmood
Degrees
Ph.D., Master's in Computer Science
Institution
Institute of Business Administration
Position Title
Professor
Email
About this CDAS Project
Study
PLCO
(Learn more about this study)
Project ID
PLCO-1496
Initial CDAS Request Approval
Mar 13, 2024
Title
Early Detection of Breast Cancer with AI enhanced workflows
Summary
The thesis "Early Detection of Breast Cancer with AI-enhanced workflows" aims to revolutionize breast cancer diagnosis through the integration of artificial intelligence (AI) technologies. Leveraging advanced machine learning algorithms and image processing techniques, the research focuses on improving the accuracy, efficiency, and timeliness of breast cancer detection, ultimately contributing to enhanced patient outcomes.
Aims
1. Enhanced Accuracy: Employing AI algorithms to analyze medical data, the research seeks to achieve acceptable levels of accuracy in identifying early signs of breast cancer.
2. Efficient Screening: Developing an intelligent and automated screening process to streamline the identification of potential malignancies, reducing the workload on healthcare professionals and enabling swift decision-making.
3. Integration with Clinical Practice: Ensuring the seamless integration of AI tools into existing clinical workflows, with a focus on interoperability to facilitate widespread adoption by healthcare practitioners.
Collaborators
None