Alejandro Sierra

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Verified

Alejandro verified their affiliation via an institutional email.

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• Master of Science
• PhD Student at Hasso Plattner Institute

As machine learning techniques are being increasingly employed for text processing tasks, the need for training data has become a major bottleneck for their application. Manual generation of large scale training datasets tailored to each task is a time consuming and expensive process, which necessitates their automated generation. In this work, we...

Creating art is often viewed as a uniquely human endeavor. In this paper, we introduce a multi-conditional Generative Adversarial Network (GAN) approach trained on large amounts of human paintings to synthesize realistic-looking paintings that emulate human art. Our approach is based on the StyleGAN neural network architecture, but incorporates a c...

Creating meaningful art is often viewed as a uniquely human endeavor. A human artist needs a combination of unique skills, understanding, and genuine intention to create artworks that evoke deep feelings and emotions. In this paper, we introduce a multi-conditional Generative Adversarial Network (GAN) approach trained on large amounts of human pain...

Named entity recognition (NER) is an important task that constitutes the basis for multiple downstream natural language processing tasks. Traditional machine learning approaches for NER rely on annotated corpora. However, these are only largely available for standard domains, e.g., news articles. Domain-specific NER often lacks annotated training d...

Extracting valuable knowledge from Electronic Health Records (EHR) represents a challenging task due to the presence of both structured and unstructured data, including codified fields, images and test results. Narrative text in particular contains a variety of notes which are diverse in language and detail, as well as being full of ad hoc terminol...

When a company requires analytical capabilities using data that might include sensitive information, it is important to use a solution that protects those sensitive portions, while maintaining its usefulness. An analysis of existing anonymization approaches found out that some of them only permit to disclose aggregated information about large group...

Objetivo: La implementación de las guías de práctica clínica está limitada por la falta de herramientas que faciliten los procesos de auditoría y retroalimentación a los profesionales de salud. Este estudio evalúa la herramienta automatizada (EXEMED), diseñada para valorar la adherencia a las guías de práctica clínica a partir de la información con...

Extracting valuable knowledge from Electronic Health Records (EHR) represents a challenging task due to the presence of both structured and unstructured data, including codified fields, images and test results. Narrative text in particular contains a variety of notes which are diverse in language and detail, as well as being full of ad hoc terminol...

Medical practice, monitoring and control guidelines enable standardization, assessment and quality improvementin healthcare. This often implies collecting and analyzing electronic medical records (EMRs)in order to calculate compliance metrics and support evidence-based decision-making. However, forthese benefits to materialize a set of challenges m...

In health care information systems, electronic health records are an important part of the knowledge concerning individual health histories. Extracting valuable knowledge from these records represents a challenging task because they are composed of data of different kind: images, test results, narrative texts that include both highly codified and a...

Information Retrieval has the task of receiving a piece of information need expressed as a query usually from a human user and retrieve pieces of information to fulfill this information need. Additionally knowledge bases (KBs) store world knowledge in structured form and allows us to empower machines with it in order to improve their performance on...