Manideep Reddy Pothula, a graduate student in the biomedical and health informatics (BHI) program at SUNY Oswego, is driven by a passion to revolutionize the way breast cancer is understood and treated.
His research focuses on leveraging machine learning and genetic data to help doctors make better decisions, improve patient outcomes and enhance treatment strategies. His journey into this critical area of study is a testament to the power of innovation and hands-on learning.
Machine learning and genetic data
Pothula's research centers around using machine learning algorithms to analyze genetic and clinical data associated with breast cancer. "Machine learning allows us to analyze the genetic and clinical data," Pothula explained. He chose to focus on breast cancer due to its widespread impact, particularly on women. His project aims to predict survival rates, identify high-risk patients and support doctors in making more informed decisions.
The use of machine learning in his research enables large-scale analysis of complex datasets that would be nearly impossible to manage manually. This technology not only speeds up the process but also increases the accuracy of predictions related to patient outcomes. Pothula emphasized how crucial this is for patient care: "It helps doctors because they will be making better decisions and will be curing the patients with better treatment."
Pothula’s work with large genetic datasets has not been without challenges. "One of the biggest complexities I've worked on is genetic data. It's a very complex material and also very long," he shared.
Working with real data took him days to run programs and interpret the outcomes. Despite the difficulties, Pothula credits his faculty mentor and program director of BHI, Isabelle Bichindaritz, for her invaluable guidance throughout the project. "She guided me every step of the way. She gave me advice and valuable feedback," he said, acknowledging her role in shaping his approach to problem-solving and critical thinking.
Hands-on research
Pothula is quick to credit SUNY Oswego for providing him with hands-on research opportunities that go beyond textbook learning.
"SUNY Oswego stood out to me because of its research environment," he remarked. The university’s unique course curriculum, which integrates machine learning with health data, gave him the tools and experiences needed to excel in his field. "It's different for me," he added, highlighting how real-world applications of machine learning have enhanced his understanding and passion for healthcare analytics.
His involvement in Oswego’s Three-Minute Thesis (3MT) Competition also honed his ability to communicate complex research in a clear and impactful way. "It was very critical to match all the things in three minutes... But I tried my best," Pothula said.
Capstone research presentation
Pothula recently took his research to the next level by presenting his capstone project, “Machine Learning Based Survival Analysis for Breast Cancer Using Clinical and Genetic Data,” at the SUNY Oswego Syracuse Campus Quest Poster Presentations on April 22. The project aimed to explore how machine learning can help predict survival outcomes in breast cancer patients by using both clinical and gene expression data from The Cancer Genome Atlas (TCGA).
"I integrated genetic features with clinical data to create a more complete risk profile," Pothula explained. He also evaluated model performance using C-index to measure predictive accuracy. His findings were groundbreaking: "Random Survival Forests outperformed traditional models by better handling non-linear relationships and missing data," he noted.
Additionally, certain genetic markers showed a strong correlation with survival risk, particularly when combined with clinical features like age and tumor stage. "The integrated model provided higher accuracy and robustness, demonstrating the importance of using both data types together," Pothula emphasized.
Pothula is quick to acknowledge the role of mentorship in his success. "I would like to sincerely thank professor Isabelle Bichindaritz for her guidance and mentorship throughout this research project. Her thoughts were invaluable to shaping the direction and depth of the project," he said. This experience, he noted, not only solidified his passion for healthcare analytics but also inspired him to continue exploring how AI can improve patient outcomes.
Looking toward the future
Pothula’s ambitions do not stop at graduation. He plans to continue his work in healthcare, focusing on the application of machine learning to improve patient outcomes. He believes the experiences and mentorship at SUNY Oswego have set him on the path to success.
"My future plans are to work as a healthcare professional, and SUNY Oswego helped me prepare for this. The BHI program is a top-five master's program in the country," Pothula shared.
His work exemplifies the innovative spirit and hands-on learning opportunities at SUNY Oswego, highlighting how research at the intersection of technology and healthcare can transform lives. As he continues his journey, Pothula remains dedicated to advancing the fight against breast cancer, one data point at a time.
If you're curious about the kind of research opportunities and mentorship that shaped Pothula's path, you can explore SUNY Oswego's biomedical and health informatics program and other graduate programs that encourage hands-on learning and personal growth.