Sybil (MIT/MGH lung cancer risk from CT)
Predicts a person's six-year lung cancer risk from one low-dose CT, even when no nodule is visible.
JCO 2023: trained on NLST CTs, validated at MGH and in Taiwan; open source. Being tested to personalise screening intervals.
Generic schematic · not to scale · placeholder for the ai computation front
Flagged finding · Neural network
How it works
3D CNN over the whole CT volume trained on time-to-cancer.
Strengths
- Open, externally validated
Limitations
- Trained on screening populations
Since
2023
Latest papers
topLatest papers · live from Europe PMC
Query for this technology: (TITLE:"Sybil" OR ABSTRACT:"Sybil" OR TITLE:"MIT/MGH lung cancer risk from CT" OR ABSTRACT:"MIT/MGH lung cancer risk from CT") AND (cancer OR tumor OR tumour OR oncology OR carcinoma OR lymphoma OR leukemia OR leukaemia OR myeloma OR sarcoma OR melanoma OR glioma). Results are unfiltered search hits about Sybil (MIT/MGH lung cancer risk from CT), not a curated reading list.