Sycai Medical
Public Health & Prevention · Health Care
Overview
By enabling early detection for abdominal cancer a universal standard. Automating the detection and temporal follow-up.
Funding and backers
Backers
3
LUMO Labs, Draper B1
Momentum
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Last sign of life
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a posting or a news item
The story so fareach stage dated by its source: the company's releases, the press, registers, filings
Oct 2026
Formerly Sycai Technologies (sycaitechnologies.com)
Jul 13
Certified Sycai Medical Obtains CE Marking for Its Artificial Intelligence Algorithm for Liver Cancer Detection · sycaimedical.com
2020
Founded
Tractionpublic signals, read monthly
Web presence
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Registers and programsofficial lists and records that name the company
| Legal entity | SYCAI TECHNOLOGIES SL | its site |
Backed byfrom the funds' portfolios and accelerator catalogs
LUMO Labs 
Draper B1 
Ship2B Investors in similar startupsfunds that back the companies most like this one
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News
Sycai Medical Obtains CE Marking for Its Artificial Intelligence Algorithm for Liver Cancer Detection
Sycai Medical Obtains CE Marking for Its Artificial Intelligence Algorithm for Liver Cancer Detection In clinical validation, the algorithm achieved a sensitivity of 90,7% and a specificity of 86,8% in detecting liver lesions from routine abdominal CT sca
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Report
AI for Early Abdominal Cancer Detection: Insights from Sara Toledano
AI for Early Abdominal Cancer Detection: Insights from Sara Toledano Explore how Sycai Medical is advancing early abdominal cancer detection using artificial intelligence. In this Clinical AI Spotlight, CEO Sara Toledano explains how opportunistic screeni
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Sycai Medical at the XXIV SEDIA Congress: validating AI for the detection of Pancreatic Cystic Lesions
Sycai Medical at the XXIV SEDIA Congress: validating AI for the detection of Pancreatic Cystic Lesions Last October, our collaboration with Vall d'Hebron University Hospital reached a new milestone: at the XXIV SEDIA Congress, held in Bilbao, Dr Andreu An
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Our New Publication: Advancing Reliable AI for Medical Imaging with the CURVAS Challenge
Our New Publication: Advancing Reliable AI for Medical Imaging with the CURVAS Challenge We are excited to announce the publication of our latest work: the results of the CURVAS Challenge (Calibration and Uncertainty for Multi-Rater Volume Assessment in M
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AI for Early Pancreatic Lesion Detection: Highlights from the Congrés de Radiòlegs de Catalunya
AI for Early Pancreatic Lesion Detection: Highlights from the Congrés de Radiòlegs de Catalunya Last month, we had the pleasure of participating in the X Congrés Nacional de Radiòlegs de Catalunya, held in Barcelona. On the opening day, Dr Montserrat Duh
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Enhancing Pancreatic Cystic Lesion Diagnosis with AI-Driven Radiomics
Enhancing Pancreatic Cystic Lesion Diagnosis with AI-Driven Radiomics In today's medical imaging landscape, the accurate classification of pancreatic cystic lesions (PCLs) remains a significant challenge in radiological oncology. Our recent multicenter st
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La startup Sycai Medical capta tres millones para su tecnología de detección del cáncer
La empresa cierra una ronda de financiación con LUMO Labs, Ship2B Ventures (con el respaldo de Banco Sabadell, FEI y Axis), Athos y Namarel
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Liver Lesion Tracking with AI: Highlights from RSNA 2024
Liver Lesion Tracking with AI: Highlights from RSNA 2024 Tracking liver lesions on CT scans is a critical yet highly complex task in radiological oncology. The intricate anatomy of the abdomen, coupled with the challenge of analyzing temporal changes in i
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Sycai Medical advances in the prevention of abdominal cancer with the obtention of the CE mark
Sycai Medical advances in the prevention of abdominal cancer with the obtention of the CE mark Barcelona, September 2024 - The Catalan startup Sycai Medical, dedicated to developing software as a medical device, has achieved a significant milestone in its
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The role of artificial intelligence in the diagnosis of liver lesions
The role of artificial intelligence in the diagnosis of liver lesions Focal liver lesions (FLLs) can be difficult to detect, classify, and differentiate - especially when it comes to identifying which ones are benign and which are potentially malignant or
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