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RESUME
Jose M. Juarez, PhD, is Associate Professor at UMU. He es co-founder of the Medical Artificial Intelligence Lab (MedAI Lab) of the University of Murcia . He has been with the Artificial Intelligence and Knowledge Engineering (AIKE) group since 2004, holding a variety of research staff positions. He has been visiting PhD student at UNIPO and UNIVR during 2005 and 2006. He joined the Department of Neuroscience of the UAL in 2007 (postdoc). Since 2008 he is faculty member at the Department of Information and Communication Engineering, UMU. He became Vice-dean of the Faculty of Computer Science (2014-2017) where he also coordinated the master studies and doctoral training programs.
Dr. Juarez’s research interests are Artificial Intelligence in general and in its uses in healthcare. In particular, he is focused on eXplainable Artificicial Intelligence and clinical decision support systems including a wide including a wide variety of AI methods.
Jose M. Juarez is board member of the European Society of Artificial Intelligence in Medicine (AIME) and co-founder and board member of the Spanish Society of AI in Biomedicine ( AI-BIOMED). He is also a Fellow of the Spanish Society of Artificial Intelligence (AEPIA) and the Spanish Society of Health Informatics (SEIS). He is member of the Program Committee Board of IJCAI (period 2022-2024). He is editorial board member of Artificial Intelligence in Medicine Journal and academic editor of PLOS ONE
Research
Main research topics: Artificial Intelligence in Medicine, clinical knolwedge discovery, explainable AI, representation and reasoning and Medical Informatics.
ASTUTENESS (leader, 2023-2024): The aim of this project is to deliver an analytical guideline based on real use cases to improve confidence in the Clinical Decision Support Systems combining the computer, sociological and medical perspectives. More info at
CONFAINCE (leader, 2022-2024): The objective of the project is to include AI as part of this chain of trust to address the challenge of fighting resistance to antimicrobials (AMR) in the National Health System. More info at
IMPACT-T2D-UMU (leader, 2022-2025): This multi-center project focus on Diabetes Type 2 for personalised medicine combining genomic and clinical information. Our team aims to identify phenotypes using Machine and Deep Learning techniques. More info at
SITSUS (co-leader, 2019-2021): The objective of this project is to develop AI methods to provide interpretable explanations and new knowledge for the surveillance of multiresistant infections. More info at
WASPSS (co-leader, 2014-2017): The main goal of this project is to propose and develop an intelligent system to support an Antimicrobial Stewardship Program. More info at
DAISY (leader, 2010-2014):Temporal Case-Based Reasoning in Ambient Assisting Living for the health risk detection of elderly people living alone. Alzheimer and Frontotemporal Dementia Prospecting. More details at
"Simple explanations to summarise subgroup discovery outcoes: a case of study concerning patient phenotyping" (Sept 2022): Scientific paper presentation in XKDD workshop @ ECML. Slides here
"Exploring Antimicrobial Resistance using Interpretable Methods" (July 2019): Scientific paper presentation in TEAAM workshop. Transparencias aquí
"Revistas y Redes Sociales para Investigadores" (Apr 2019): EIDUM PhD Courses, UMU. Transparencias aquí
"Elegir una revista científica" (May 2018): EIDUM PhD Courses, UMU. Transparencias aquí
"Inteligencia Artificial en Medicina" (March 2017). Popularization of Science in Máster Bioderecho, UM. Transparencias aquí
"Antimicrobial Visualization" (November 2015): Scientific paper presentation in CAEPIA conference. Transparencias aquí
"Entrevista: Inteligencia Artificial y aplicaciones en salud" (February 2015): Entrevista con mi colega Manuel Campos en Onda Regional. Escúchalo aquí
Teaching (Spanish)
Since 2008 teaching theoretical computer science, intelligent systems and healthcare applications.
SSII: Sistemas Inteligentes (3 año, grado Ing. Informática): funtamentos de la Inteligencia Artificial. Algunos artículos sobre el nacimiento de la IA: 1943 McCulloch-Pitts-1950 Alan Turing. Y algunos de los últimos avances: WHATSON de IBM gana al triple campeón de TV Jeopardy!, ALPHA-GO de Deepming gana al campeón del mundo de GO en revista Nature.com , GOOGLE-DUPLEX pidiendo citas por teléfono , ejemplo de Google Car y cuestiones éticas en proyecto del MIT The Moral Machine.
Introduccion a la Ciencias de Datos para la IA (ICDIA): 1 año, grado Ing. y Ciencias de Datos.
SIB: Sistemas de Información en Biomedicina (Máster MNTI): imparto módulos de CIE, HL7, SNOMED e Interoperabilidad Semántica. Una intro Prezi en | Introducción a informática médica (apuntes tema 1.1) | Datos y conocimiento en informática médica (apuntes tema 1.2) | Historia Clínica Electrónica (apuntes tema 2)
Focused on AI models, diagnosis systems, intelligent systems and their applications.
TFG: Trabajos Fin de Grado. Si buscas proyectos en IA, modelos computacionales o aplicaciones en salud, mándame un correo
TFM: Trabajos Fin de Máster. Si buscas línea en informática médica o en IA, mándame un correo
Phd Thesis: Interested in a Doctoral thesis? Send me an e-mail
Some of the students I was honored to advise.
Bernardo Canovas-Segura, PhD 2019: currently Postdoc at University of Murcia, Spain. PhD Thesis: 'Medical informatics approaches for decision support in antimicrobial stewardship'
Eduardo Lupiani, PhD 2014: currently at NTT Data, Germany. PhD Thesis: 'Temporal case-base maintentance'
Antonio Lopez Mtnez-Cararasco, MSc 2019: currently PhD student at UMU. MSc Thesis: 'SubgPyLib: Descubrimiento de subgrupos en Python'
Jose A. Martinez-Muñoz, MSc 2018: currently at CERNER CORP., Spain. MSc Thesis: 'Estudio e implementación de mensajería HL7 para la versión 2.5 y la especificación FHIR en el ámbito de la prescripción farmacológica hospitalaria'
Humberto García-Caballero, MSc 2015: currently PhD student at Eindhoven Univ. of Technology, The Netherlands. MSc Thesis: 'Visualización de antibiogramas como ayuda al tratamiento empírico'
Francesca Zerbato, MSc 2015: currently postdoc student at University of Verona, Italy. MSc Thesis: 'BPMN-based Design and Comparison of Clinical Pathways and Data for Catheter-related Bloodstream Infections' (main adv. Carlo Combi, UNIVR, IT)