Jeffrey Dalli
Papers
2
Total Citations
17
H-Index
2
About
Jeffrey Dalli is a surgical researcher at the forefront of integrating artificial intelligence with fluorescence-guided surgery. His primary research areas include colorectal surgery, hepatic oncology, and the application of computer vision to improve intraoperative tumor identification. Dalli’s most cited work, "Real-time administration of indocyanine green in combination with computer vision and artificial intelligence for the identification and delineation of colorectal liver metastases" (2023, 13 citations), addresses a critical limitation in fluorescence-guided surgery—low specificity and impractical dosing protocols. By combining ICG with AI-driven analysis, his research offers a novel method for real-time, precise delineation of metastatic liver lesions, potentially transforming surgical decision-making. Additionally, his work on "Gas leaks through laparoscopic energy devices and robotic instrumentation" (2020, 4 citations) contributed to the urgent discourse on surgical safety during the COVID-19 pandemic, highlighting aerosolization risks from minimally invasive tools. Though early in his career, Dalli’s interdisciplinary approach—merging surgical technique with computational innovation—positions him as a rising contributor to precision oncology and safer surgical practices.
Research Focus
Key Achievements
Top Papers
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