1st Workshop Machine Learning for Health Care 2019
Associated to the Mexican
International Conference on AI MICAI 2019, Xalapa,
Veracruz,
October 28, 2019, 14:00 – 18:00 hours
Place:
Universidad Veracruzana, Centro de Investigación en Inteligencia Articial,
CIIA room 01. See
map
The MLHC workshop aims to bring
together experts from ever more
interacting disciplines: on one hand,computer
scientists with artificial intelligence, machine learning, and big data
expertise, and on the other hand,clinicians/medical
researchers working on the several branches of healthcare.
MLHC supports the
advancement of data analytics, knowledge discovery, and meaningful use of
complex medical data by fostering collaborations and the exchange of ideas
between these communities.To
pursue this goal, MLHC includes invited and accepted oral presentations, to
stimulate the dissemination of novel research among Mexican scientists and
their partners working onthe mentioned areas.
Papers list
Contact us: matias@cs.cinvestav.mx, alfonso.rojas@gmail.com.
Deadline for camera ready papers: November
2019
Papers are to be
submitted to the Workshop Organizers via email. Contributions should be
formatted in accordance with the Springer LNCS format guidelines and limited to
8 pages (including Abstract, Introduction, Related
work, Methodology, Results & Discussion, Conclusion and Bibliography).
Accepted papers will be allocated 20 minutes for oral presentation and
discussion. We welcome original contributions (completed research as well as
work in progress) in the following topics:
Bioinformatics
& Biomedicine: tumor vs immune-system
interaction, cancer early diagnosis, cancer metastasis, other complex diseases
like diabetes, and epidemiology.
Methods: data science,
deep learning, machine learning, and high performance computing, with
applications to healthcare (prevention, diagnosis and treatment of disease and
illness).
Approaches: Artificial and
Computational Intelligence, and Systems Biology for healthcare.
MLHC has a peer-review process and proceedings track in the Journal of Research in
Computing Science
Dr. Matías Alvarado, Depto. de Computación,
CINVESTAV-IPN, matias@cs.cinvestav.mx
Dr. Alfonso
Rojas Domínguez, TNM-Campus León, Gto.,
alfonso.rojas@gmail.com
Matías Alvarado, CINVESTAV, México (Machine
Learning for healthcare)
Didier Barradas, KAUST, Arabia Saudita
(Biochemistry)
Mariana Benítez Keinrad, UNAM, México
(Systems Biology)
Elisa Domínguez Hüttinger, UNAM, México
(Systems Biology & Mathematics)
Carlos Lara Álvarez, CINVESTAV,
México (Biorobotics)
Rosana Pelayo Camacho, IMSS, México
(Immunology)
Carlos Alberto Reyes, INAOE-CONACyT, México (Biosignals and Computer Medicine)
Alfonso Rojas Domínguez, TNM-ITL, México (Machine Learning for
healthcare)
Carlos Villarreal Luján, UNAM,
México (Biophysics)