Game-changer in cancer prevention: 10 things to know about PrismNN model and cancer detection
A game-changer in cancer prevention, Harvard and MIT's new risk prediction model - PrismNN - identifies high-risk patients early and significantly improves pancreatic cancer detection rates. Pancreatic cancer has a low 11% five-year survival rate due to late detection but this pioneering tool developed by Harvard-affiliated Beth Israel Deaconess Medical Center and MIT uses electronic health records and identified high-risk patients up to 18 months before diagnosis, catching 3.5 times more cases than current guidelines.
Showing promising results, the study was funded by various organisations while PrismNN aims to expand screening beyond the 10% with inherited predisposition. In an interview with HT Lifestyle, Dr Imran Shaikh, Consultant Surgical Gastro and GI Oncosurgery at Wockhardt Hospitals in Mumbai's Mira road, shared, “The use of PrismNN model in the diagnosis and treatment of pancreatic cancer has immense potential to improve patient outcomes. By using deep learning algorithms and medical imaging data, PrismNN can offer more accurate detection and classification of pancreatic tumors, leading to earlier diagnosis and intervention.”
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He gushed, “This could significantly improve survival rates for patients by enabling timely access to appropriate treatments and interventions. Moreover, the predictive capabilities of the PrismNN model can aid in personalising treatment plans for individual patients based on their unique tumor characteristics. This means that patients could receive tailored therapies that are more effective and have fewer side effects, ultimately enhancing their quality of life during treatment. The ability of PrismNN to continuously learn from real-world data presents opportunities for ongoing refinements and improvements in cancer care, paving the way for more precise interventions and better long-term outcomes for pancreatic cancer patients.”
Bringing his expertise to the same, Dr Lorance Peter, Director -Gastroenterology and Hepatology at Sakra World Hospital in Bengaluru, highlighted 10 things to know about PrismNN model and cancer detection -
1. Innovative Collaboration: PrismNN is a revolutionary risk prediction model developed jointly by MIT CSAIL scientists and Limor Appelbaum from BIDMC, combining expertise in computer science and medical research.
2. EHR Integration: It utilises electronic health records to surpass conventional screening methods, identifying individuals at risk of pancreatic cancer up to 18 months before diagnosis by analyzing comprehensive patient data.
3. Early Detection Emphasis: Unlike protocols focused solely on hereditary factors, PrismNN broadens the screening scope, emphasising early detection to enable timely interventions and enhance patient outcomes.
4. Diverse Impact: While initially targeting pancreatic cancer, PrismNN's success extends to a wider range of cancers, demonstrating its potential to advance cancer detection and treatment across various malignancies.
5. Global Significance: PrismNN's capabilities offer the potential for improved global outcomes by facilitating early detection and intervention, particularly in regions with limited access to specialized screening resources.
6. Scalable Deployment: By leveraging routine clinical data, PrismNN enables scalable deployment of risk prediction tools, making it accessible across diverse healthcare systems and populations.
7. Interdisciplinary Approach: It represents an interdisciplinary approach to cancer detection, bridging computer science, healthcare, and medical research to develop innovative solutions for critical healthcare challenges.
8. Continuous Evolution: It undergoes continuous research and development to enhance its predictive accuracy and effectiveness in cancer detection, incorporating new insights and data to drive advancements in oncology.
9. Promise for the Future: With ongoing advancements and refinements, PrismNN holds promise for revolutionizing cancer detection and treatment, offering hope for improved outcomes and quality of life for patients worldwide.
10. Expertise Integration: The collaboration between MIT CSAIL scientists and medical professionals like Limor Appelbaum ensures that PrismNN combines cutting-edge technology with clinical expertise to deliver impactful results.
