Revista Emprendedores have searched for the most innovative projects of 2023 in the Spanish market to produce the 8th Emprendedores List of innovative startups. Spanish, innovative and very young. We have passed through these three filters to the country’s leading companies to draw up what is already the 8th Entrepreneurs List of innovative startups. So…
Artificial intelligence brings to medicine a different and more complete data analysis system than those used to date. In the latest episode of KREAB Fika Café, Carlos M. Galmarini reflected with Antonio San José on the application of AI in the diagnosis of diseases and in the development of new drugs. La inteligencia artificial aporta…
If we asked the most famous artificial intelligence (AI) based chat today about the role that data analysis plays in everyday clinical practice, it would respond that it is increasingly important to help improve human health. However, even AI warns humans of how crucial it is to have scientific criteria based on healthcare professionals to…
NutriGuard is a machine learning framework designed and developed by Topazium to harness the potential of food components for promoting and preserving health. It is inspired by the need to understand the physiological effects exerted by food components from a well-grounded rationale based on scientific evidence. NutriGuard utilizes different sources of information to achieve its goal and…
Introduction. Diagnostic errors between nevic lesions and skin tumors are frequent for non-specialist physicians. Therefore, there is a need to create a simple and practical tool based on artificial intelligence to assists them in distinguishing potentially malignant lesions from benign ones, improving early detection of skin cancer. Objective. To evaluate the performance of SkinGuard, an…
En un mundo en constante cambio y evolución como el nuestro, pocos métodos o doctrinas pueden tener el honor de permanecer vigentes durante más de 2.000 años. Uno de estos excepcionales casos es el método hipocrático, gracias al cual la medicina abandonó la superstición y la magia ejercidas por sacerdotes-médicos en aquella época y se…
Background: To understand the transcriptomic response to SARS-CoV-2 infection, is of the utmost importance to design diagnostic tools predicting the severity of the infection. Methods: We have performed a deep sampling analysis of the viral transcriptomic data oriented towards drug repositioning. Using different samplers, the basic principle of this methodology the biological invariance, which means…
Background: Patients with K-RAS wild-type (WT) metastatic colorectal cancer (mCRC) are currently considered the optimal candidates for upfront treatment with combinations of chemotherapy and EGFR inhibitors. These combinations significantly extend overall survival (OS) compared to chemotherapy alone. However, a proportion of patients would not achieve this goal. This study has investigated the ability of an…
Background: Synthetic fingerprints integrate clinical data within computational models allowing the identification of particular clinical subpopulations at a given moment. We here describe a deep learning strategy to detect super-responder and super-survivor patients with squamous NSCLC by setting up synthetic fingerprints and using unsupervised deep learning frameworks (UDLF). Methods: Through www.projectdatasphere.org, we accessed the control…
Background: Predicting the clinical course of metastatic disease remains a key challenge in CRC. Estimating prognosis of these late-stage patients can avoid undertreatment or overtreatment and also guide the follow-up intensity. This study has investigated the ability of an artificial intelligence-based analytical tool to identify those mCRC patients with high risk of disease progression and…