LivGuard, a deep neural network for cirrhosis detection in liver ultrasound (USD)

Introduction: Ultrasound (US) is widely used for diagnosing liver disease, particularly cirrhosis, with key signs including liver shape irregularity and echostructure. The classification of liver parenchyma as smooth or coarse, indicative of chronic liver disease, is subjective and dependent on operator experience. To address this, we introduce LivGuard, a deep learning binary classifier designed to…

Ethics or Atics? The role of artificial intelligence in medicine

In an era of technological uncertainty, artificial intelligence (AI) emerges as a revolutionary tool capable of transforming multiple sectors, including medicine. However, it is crucial to understand its role as a complement rather than a substitute for human intelligence and quality, while maintaining the legacy of the Hippocratic method. The era of Artificial Intelligence (AI)…

GFPrint™: a machine learning tool for transforming genetic data into clinical insights

The increasing availability of massive genetic sequencing data in the clinical setting has triggered the need for appropriate tools to help fully exploit the wealth of information these data possess. GFPrint™ is a proprietary streaming algorithm designed to meet that need. By extracting the most relevant functional features, GFPrint™ transforms high-dimensional, noisy genetic sequencing data…

Finding a needle in a haystack: virtual screening, an artificial intelligence approach to drug discovery

Artificial intelligence (AI) is a technology well suited for dealing with large amounts of information and has long been considered a promising tool in drug discovery. It has made steady in roads in the field in the last decade by improving the probability of success and bringing greater precision, speed, and cost-efficiency to a process…

A machine learning (ML) approach for identifying genetic biomarkers and new molecular targets associated with impaired survival of breast cancer patients

BACKGROUND Machine learning (ML) tools are suitable to dive vast amounts of clinical and genetic information in order to identify genetic biomarkers of worse survival and potential new molecular targets. This study has investigated the ability of one such tool to identify genetic biomarkers associated with higher risk of mortality in breast cancer, biomarkers that…

Prospective evaluation of SkinGuard, a deep algorithmic framework for the classification of neoplastic skin lesions

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…

Harnessing the power of AI and HTE, cloud lab and automation data to transform drug discovery

Drug discovery is a lengthy and costly process affected by a high attrition rate. The revolution in experimental sciences brought about by HTE, cloud labs and lab automation should represent an excellent opportunity to completely transform drug discovery and overcome the serious problems that hinder the process. But this transformation will not be possible without…

El arte de la medicina hipocrática y la IA: un binomio al servicio del paciente

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…