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José Luis Martínez Fernández (Projects)

 

A significant portion of technologies involves interacting with people through user interfaces in interactive systems. Therefore, it is necessary to design accessible user interfaces which ensure that all people can access and operate these systems regardless of their visual, auditory, cognitive or motor abilities. For this reason, the primary aim of this project is to show the viability and application of accessibility techniques for the design and development of of video conferencing systems that ensure persons with disabilities (PWDs) can access and operate them. Due to the nature of accessibility requirements, this project will use a multidisciplinary approach based on the shared scientific knowledge that methods from fields such as Artificial Intelligence (AI) and Human-Computer Interaction (HCI) can provide.

There are users with sensory impairments, such as blind people, individuals with low vision, deaf individuals, or those with hearing impairments, who need video conferencing applications that include necessary accessibility requirements, such as services providing audio descriptions of videos and images, interfaces that are adapted in relation to sensory characteristics, subtitling services, voice-operated applications or screen readers. Furthermore, there are cognitive accessibility barriers that affect both people with intellectual disabilities and the elderly, all of whom require intuitive user interfaces, text simplification services, and the generation for text summarization summaries, among other tools, to assist in the understanding of texts, as set out in this project.

As specific contributions, design standards will be defined following HCI methods for the design of accessible and adaptable user interfaces. Additionally, affective computing and computational semiotic techniques will be explored with regards to their application in the interactive elements of user interfaces. Moreover, telematic techniques used to generate subtitles will be researched, as well as the use of AI techniques for the generation of high-quality transcriptions through the post-processing of subtitles. In the area of AI and Natural Language Processing (NLP), approaches will be explored to carry out the lexical simplification and the creation of corpora in the fields of Easy-to-Read texts and Plain Language. Furthermore, deep learning techniques used to text summarization will also be researched.

 

  • Reference: PID2020-116527RB-I00
  • Financing: Convocatoria 2020 Proyectos Generación del Conocimiento y Retos Investigación. MINISTERIO DE CIENCIA E INNOVACIÓN
  • Project type: Público
  • State: Activo
  • Principal investigator: Lourdes Moreno
  • Other investigator: Paloma Martínez, Belén Ruiz-Mezcua, Isabel Segura-Bedmar, Israel González Carrasco, Jose Luis Lopez-Cuadrado, José Luis Martínez Fernández, Rodrigo Alarcón, Cristóbal Colón Ruiz
  • Duration: -
  • https://access2meet.uc3m.es/

El objetivo es el desarrollo de un sistema para procesamiento del texto libre de las historias clínicas electrónicas (HCE) del Hospital Universitario Fundación de Alcorcón (HUFA) utilizando técnicas de procesamiento de lenguaje natural y métodos de deep learning. HUFA fue uno de los primeros hospitales de la Comunidad de Madrid en disponer de HCE, desde su apertura a finales de 1997. En la actualidad la Comunidad de Madrid tiene integradas más 5 millones de HCE de las que sólo se procesan los metadatos estructurados. El resto de la información, en formato no estructurado (texto libre), a día de hoy permanece sin ser poder ser explotada por procesos automáticos. El desarrollo de tecnología capaz de procesar y explotar información no estructurada en texto libre de la HCE en el contexto actual de big data, puede tener muchas aplicaciones tanto en la mejora de la práctica clínica (generación automática de resúmenes de episodios relacionados con un paciente, sistemas de ayuda a la decisión clínica para personalizar diagnósticos y tratamiento de enfermedades, alertas de enfermedades infecciosas, mejora de los sistemas de farmacovigilancia, etc.) como en investigación (semi-automatización de los estudios epidemiológicos, por ejemplo en la identificación de los cohortes de pacientes). En concreto, la realización de estudios epidemiológicos implica una ardua labor en la revisión manual de un elevado número de HCE, lo que a su vez conlleva un gran número de recursos humanos y una ingente cantidad de horas de trabajo. Por tanto es crucial promover el desarrollo de técnicas automáticas que permitan obtener información de forma más ágil, convirtiendo la información no estructurada en estructurada y procesable por algoritmos automáticos, y facilitando así la toma de decisiones estratégicas.
El objetivo del proyecto es el desarrollo de técnicas de PLN y método de deep learning para el análisis de la información no estructurada de la HCE, con el fin último del de reducir el coste, en tiempo y recursos, de los estudios epidemiológicos. El proyecto tiene dos centros participantes: (Subproyecto 1) Grupo LABDA de la UC3M que desarrollará el sistema automático para el procesamiento de la HCE y (Subproyeto 2) HUFA cuyo equipo está formado por especialistas de la unidad de Alergología, que serán los encargados de llevar a cabo un estudio epidemiológico a partir de los datos obtenidos de la HCE mediante al uso de PLN y métodos de deep learning. En concreto, el estudio epidemiológico tendrán como principal objetivo estudiar la prevalencia de la anafilaxia en la población definida como caso de uso de aplicación. Varios profesionales del servicio de informática de HUFA serán los encargados de anonimizar las HCE para garantizar la protección de datos de los pacientes.
Aunque el sistema será desarrollado sobre la HCE del HUFA, la tecnología que se pretende desarrollar en el proyecto solicitado, podría ser aplicada directamente a la HCE de cualquier otro hospital. Además, su adaptación al estudio epidemiológico de otras patologías distintas a la anafilaxia (cáncer de mama, ictus, etc) es relativamente sencilla ya que los enfoques (deep learning) que se quieren abordar durante el proyecto son independientes del problema a tratar.

  • Reference: TIN2017-87548-C2-1-R
  • Financing:
  • Project type: Público
  • State: Activo
  • Principal investigator: Paloma Martínez Fernández, Isabel Segura Bedmar
  • Other investigator: Jose Luis Lopez-Cuadrado, Israel González Carrasco, José Luis Martínez Fernández, Lourdes Moreno, Belén Ruiz-Mezcua, Cristóbal Colón Ruiz, Rodrigo Alarcón
  • Duration: -

Public administrations are rapidly advancing towards the provision of basic and extended services for the citizen through the Web (EU eGovernment Report 2014). In addition to the decrement of costs, this effort will support all people’s civil right to have access to all public services (including people with disabilities and elderly people). For this reason the EU started diverse initiatives to “Meeting new societal needs by using emerging technologies in the public sector” in order to “foster efficient, open citizen-centric public services”. Efforts have been made for enhancing the usability and accessibility of public administrations’ websites but several studies revealed that this is not sufficient to support acceptable eGovernment applications. Other factors such as content/information quality and security are also required. Our overall objective is to produce a model-based software architecture for methodologically developing personalized inclusive public eServices that allow any user to interact with them in a satisfactory way, no matter the device used. This requires integrating appropriate user profiling and adaptation techniques into the model to tailor eServices to users’ characteristics, available technology, and service’s functionality. Hence, this project has a multidisciplinary nature and will be addressed through collaboration between researchers and experts in information technology and professionals of the eGovernment, combining diverse scientific backgrounds: • Modelling eGovernment services • Data mining to search for user patterns to feed user models • Human-computer interaction for user tailored interfaces, including universal accessibility and multidevice access • Natural language processing for accessible user interfaces • Model based software architectures for the methodological development of eGovernment applications. It is structured into two subprojects: Subproject 1, leaded by the EHU, will exploit real user interaction data from the eServices provided by Provincial Council of Gipuzkoa (PCG) to extract common usage patterns, anomalous usage of services, and accessibility barriers. Models of eServices will be built with the inclusion in the workgroup of experts on eGovernment (from the Quality Institute Netherlander Municipalities, the Service for Modernization of the PCG, and IZFE, a developer of applications for eAdministration). Starting from these models, user adaptive Web access will be provided by means of presentation, content and navigation adaptations. Subproject 2, leaded by UC3M, will create a software architecture for model-based development of eGovernment applications that includes support for accessibility and multidevice use (assisted by experts from the University of Lisbon). The definition of a model-based software architecture will be done in collaboration with the LoUISE research team from UCLM, which is currently developing a framework that can be extended to fit our needs. The results of the complete project will include models of: users of eGovernment applications; e-Services; and web adaptations required to ensure universal and multidevice accessibility. All of them will be integrated by the model-based architecture that will allow the creation of tools to develop fully accessible high quality eGovernment applications. In this way the project will contribute to increase citizens’ participation, to produce savings for governments and businesses, and to reduce administrative burden.

  • Reference: TIN2014-52665-C2-2-R
  • Financing: Ministerio de Economía y Competitividad
  • Project type: Público
  • State: Activo
  • Principal investigator: Paloma Martínez Fernández
  • Other investigator: Paloma Martínez Fernández, Lourdes Moreno, Isabel Segura Bedmar, José Luis Martínez Fernández, Belén Ruiz-Mezcua, Victor Suarez Paniagua, Israel González Carrasco, Jose Luis Lopez-Cuadrado
  • Duration: -
  • https://egovernability.wordpress.com

The aim of this project is to define and develop information extraction and retrieval techniques based on texts from the medical domain. This will be carried out following two basic tasks: firstly, processing scientific documents in English about pharmacology, and secondly, processing informative texts about health topics in other languages such as Spanish and Arabic. These information extraction techniques include domain entities recognition, pattern recognition, machine learning for extracting semantic relations, and the integration of lexical resources which are specific within the public health system (UMLS, SNOMED and so on) in order to improve applications. On the other hand, the information extracted from the processing task must be used to enrich the information retrieval tools. Thus, three prototypes of searching information will be created in order to show the feasibility of the proposed techniques. The first of them is an application oriented to pharmacists to extract knowledge about drug-drug interactions from scientific publications. The second prototype will be a tool focused on general public or patients to search information about illnesses and medicines. The third one will use the terminology extracted from the Spanish-Arabic parallel corpus to aid terminology teaching in the biomedical domain.

  • Reference: TIN2010-20644-C03-01
  • Financing: Plan Nacional de I+D, Ministerio de Ciencia e Innovación
  • Project type: Público
  • State: Activo
  • Principal investigator: Paloma Martínez Fernández
  • Other investigator: Paloma Martínez Fernández, Lourdes Moreno, Elena Castro Galán, Ana M. Iglesias Maqueda, Isabel Segura Bedmar, María Teresa Vicente-Díez, José Luis Martínez Fernández, Julián Moreno Schneider, Daniel Sánchez Cisneros, María Herrero Zazo
  • Duration: -
  • http://labda.inf.uc3m.es/multimedica/
  • Reference: CEN-20091026
  • Financing: DAEDALUS S.A dentro del SUBPROGRAMA DE APOYO A CONSORCIOS ESTRATÉGICOS NACIONALES DE INVESTIGACIÓN TÉCNICA (CENIT-E), CEN-20091026
  • Project type: Público
  • State: Activo
  • Principal investigator: Paloma Martínez Fernández
  • Other investigator: Paloma Martínez Fernández, Dolores Cuadra Fernández, Lourdes Moreno, Elena Castro Galán, Ana M. Iglesias Maqueda, Francisco Javier Calle Gómez, Harith Al-Jumaily, César De Pablo Sánchez, Isabel Segura Bedmar, María Teresa Vicente-Díez, David del Valle Agudo, José Luis Martínez Fernández, Jesica Rivero Espinosa, Daniel Sánchez Cisneros, María González García, María Herrero Zazo
  • Duration: -
  • http://www.cenitbuscamedia.es

The main goal of the project is the design and development of a system, which implements a process of automatic generation of subtitles for prerecorded video or audio accompanied by an accurate transcription (screenplay). In this project wants develop a prototype. It will be a tool that will offer support for subtitling of audiovisual content in recorded (movies, documentaries, series, etc…) for different media way such as television, Internet and mobile devices. In this context, the process is called recorded subtitling (off-line or canned) because is not processed in real time; it is treated previously without anytime limits. This automatic support provide a synchronization process of the screenplay with audio by adding time stamps, analyze of errors resulted in the process, and the text subtitles segmentation conform to current standards.

  • Reference: Proyecto Avanza - TSI-020100-2010-184
  • Financing: Ministerio de Industria, Turismo y Comercio (proyecto AVANZA)
  • Project type: Público
  • State: Activo
  • Principal investigator: Lourdes Moreno
  • Other investigator: Paloma Martínez Fernández, Lourdes Moreno, Ana M. Iglesias Maqueda, José Luis Martínez Fernández, Belén Ruiz-Mezcua, María González García
  • Duration: -
  • http://labda.inf.uc3m.es/sagas

BRAVO is devoted to research on technologies to improve the answers search in both text and voice, and the main result is a platform for a modular answers search system which allows to measure the improvement of different techniques for questions classification, answer extraction, passages retrieval, etc. SPINDEL is one of the techniques developed in this project, an entity recognizer which, regardless of language, applies machine learning based on bootstrapping. In the framework of BRAVO project, one of the current research areas is related to the location of drug names and interactions between them in the medical literature using UMLS, dictionaries and USAN rules of naming drugs. As a result, it is available automatically annotated corpus using the DrugNer system (developed by the Advances Databases Group) with generic drug names and other biomedical concepts and manually evaluated by a pharmacological expert. The system combines information obtained by the UMLS MetaMap Transfer (MMTx) program and nomenclature rules recommended by the World Health Organization (WHO) International Nonproprietary Names (INNs) Program to identify and classify pharmaceutical substances

  • Reference: TIN2007-67407-C03-01
  • Financing:
  • Project type: Público
  • State: Activo
  • Principal investigator: Paloma Martínez Fernández
  • Other investigator: Lourdes Moreno, Elena Castro Galán, Ana M. Iglesias Maqueda, César De Pablo Sánchez, Isabel Segura Bedmar, María Teresa Vicente-Díez, José Luis Martínez Fernández, Belén Ruiz-Mezcua, Julián Moreno Schneider, Mario Crespo
  • Duration: -

The aim is to research in technology based on automatic language processing for information location and retrieval from medical texts and other resources (reports, electronic medical records, scientific documentation, etc..) specially in Spanish language. Thus, we worked in browsers with different levels of complexity that integrate medical domain-specific resources and terminology (UMLS, SNOMED, etc.) and with different treatment of syntactic and semantic levels.

  • Reference: FIT-350300-2007-75
  • Financing: Ministerio de Industria, Comercio y Turismo
  • Project type: Público
  • State: Terminado
  • Principal investigator: Paloma Martínez Fernández
  • Other investigator: Paloma Martínez Fernández, Dolores Cuadra Fernández, Elena Castro Galán, Ana M. Iglesias Maqueda, Harith Al-Jumaily, César De Pablo Sánchez, Isabel Segura Bedmar, María Teresa Vicente-Díez, José Luis Martínez Fernández
  • Duration: -

The main purpose of MIRACLE project has been to develop an Information Retrieval system that integrates several techniques and available resources (proceeding from the statistical field as well as from the linguistic technology area) in order to enhance the quality of retrieval in the scope of multilingual information retrieval. This system has been carried out togheter with the Technical University of Madrid and has been succesfuly validated in the CLEF forum (Cross Language Evaluation Forum) in 2003 and 2004 editions. Particularly, MIRACLE systems has taken part in multilingual, bilingual and monolingual tasks as well as in Image retrieval. Moreover, in 2004 edition we have also taken part in question answering task.

  • Reference: 07T/0055/2003 2
  • Financing: Comunidad de Madrid
  • Project type: Público
  • State: Terminado
  • Principal investigator: Paloma Martínez Fernández
  • Other investigator: Paloma Martínez Fernández, César De Pablo Sánchez, José Luis Martínez Fernández
  • Duration: -