SOTONWA ADEBOLA KEHINDE

Computer Science

At the Computer Science department office

Appointment on Visitation important

Topic: Research Interest

Description:

Artificial Intelligence, Machine Learning, Healthcare Informatics, Software Engineering, Software Complexity Analysis

#	Certificate	School	Year
1.	Ph.D (Computer Science)	Computer Engineering/ Ladoke Akintola University of Technology, Ogbomoso, Oyo State	2020

Development of deep learning model in breast cancer using digital pathology

There s a surge of interest in using deep learning, a type of artificial intelligence, to analyze digital pathology images for breast cancer detection and diagnosis. This fascination stems from the potential of deep learning models to: -Improve accuracy and efficiency: Deep learning can automatically identify patterns in complex images that may be missed by the human eye, potentially leading to earlier and more precise diagnoses. -Assist pathologists: Models can act as a second opinion for pathologists, highlighting suspicious areas and reducing workload. Develop personalized medicine: By analyzing tumor characteristics, deep learning could aid in predicting a cancer s aggressiveness and guide personalized treatment plans. Researchers are actively developing deep learning models for various breast cancer tasks. Some areas of focus include: -Distinguishing between benign and malignant tumors. -Assessing the severity of cancer based on factors like cell growth. -Identifying specific breast cancer subtypes for targeted therapies. Overall, deep learning in digital pathology holds promise for revolutionizing breast cancer diagnosis and treatment. However, challenges like data privacy and ensuring model fairness require ongoing research.

SOTONWA KEHINDE is a Lecturer I at the Department of Computer Science

SOTONWA has a Ph.D in Computer Science from Computer Engineering/ Ladoke Akintola University of Technology, Ogbomoso, Oyo State