HC@AIxIA 2024 CALL FOR PAPERS + AI&Health Seminar Series (2024) - SEPTEMBER 16

[apologize for multiple postings]

Please find below the Call for Papers to HC@AIxIA 2024 + some pieces of
information about the next seminar in the AI&Health Seminar Series (2024).



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Third AIxIA Workshop on Artificial Intelligence For Healthcare
HC@AIxIA 2024

November 25 - 28, 2024, Bolzano, Italy
https://sites.google.com/unical.it/hcaixia2024
CO-LOCATED with the 23rd International Conference of the Italian
Association for Artificial Intelligence (AIxIA 2024) (
https://aixia2024.events.unibz.it/)
JOINT event with the 5th Data4SmartHealth workshop (D4SH 2024) (
https://www.data4smarthealth.it/)
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= IMPORTANT DATES (tentative) =
Abstract submission:     September 17, 2024
Paper submission:        September 24, 2024
Notification to authors: October 6-13, 2024
Camera-ready copy due:   October 20, 2024
Main Workshop starts:    November 25, 2024 (maybe subject to slight
adjustments, please check the website regularly)
Working Group meeting:   Right after the workshop


= Background =
In recent years, we have witnessed the ubiquitous application of Artificial
Intelligence in real-world domains; in particular, AI-based solutions
significantly changed the game in medicine and healthcare in several
respects (research, management, clinical practice). Indeed, applications of
AI in the healthcare domain become a major research topic, that attracts
cross-disciplinary research groups.
Medicine and health care require highly complex decision-making to ensure
that the trajectory a patient with a disease needs to take for diagnosis,
treatment, recovery, and finally outcome is optimal in some sense.
Consequently, researchers have to draw methods from the entire field of AI.
On the other hand, healthcare and medicine are built upon a rich and
evolving body of knowledge, e.g., concerning the pathophysiology of
diseases, molecular, genetic, cytological, and histological
characterization of stages of a disease, described by temporal and spatial
patterns. Such knowledge can also act as background knowledge to guide
machine learning. To move towards effective and long-lasting applications
of AI in healthcare, it is crucial to elucidate the relationship between
what can be expected from AI methods when applied to healthcare problems
and the role knowledge of healthcare and clinical medicine can play in
developing AI solutions to healthcare and clinical problems.


= The Workshop =
Following the success of the first two editions, the HC@AIxIA workshop aims
at gathering researchers from academia, industry and medical centres to
present and discuss the latest research results and ongoing works related
to the application and impact of AI in the healthcare domain, to the larger
extent, thus aiming at covering a wide spectrum of topics, including
theoretical and practical aspects, methodologies, technologies, and systems.

Topics include, ***but are not limited to***:
 - Machine learning methods, data mining and statistical methods for
clinical decision support
 - Probabilistic graphical models for clinical decision-making and causal
networks
 - Learning, representation and reasoning with time
 - Knowledge representation, reasoning and formal argumentation in
healthcare
 - Methods for diagnosis, treatment selection, treatment planning, and
prognosis
 - Monitoring patients in healthcare
 - Ontologies and medical vocabularies
 - Personalized medicine
 - Computer-interpretable clinical guidelines
 - Support for natural language generation/understanding in connection with
electronic patient records
 - Tools for supporting authoring, execution and maintenance of clinical
protocols and guidelines
 - Tools for building and deployment of clinical decision-support systems


= Contributions =
The workshop will feature presentations of refereed contributions; four
types of submissions are invited:
 - full papers (min 10 and up to 15 pages plus references);
 - short papers (min 5 and up to 9 pages, including references):
particularly suitable for presenting work in progress, software prototypes,
extended abstracts of doctoral theses, or general overviews of research
projects;
 - systems or prototype software descriptions (min 5 and up to 9 pages,
including references): must include a brief description, prepared according
to the guidelines given for short papers, and a specification of the
required hardware and software equipment. Systems of both research and
industrial character are welcome;
 - papers already submitted/published to other conferences or journals (no
page restrictions), i.e., non-original works suitable for dissemination and
opening discussion.
Besides demos, some contributions might be invited to be presented as
posters.


= Submission Instructions =
Authors are invited to submit their manuscripts in PDF via the EasyChair
system at the link:
    https://easychair.org/conferences/?conf=hcaixia2024

No page limit is set for non-original contributions.
Manuscripts should be formatted using the CEUR-ART style available at the
link:
    https://ceur-ws.org/HOWTOSUBMIT.html.

To ease the reviewing process, the authors of regular papers may add an
appendix (although reviewers are not required to consider it in their
evaluation).

All contributions must be written in English.

For each accepted contribution, at least one of the authors is required to:
 - register to AIxIA 2024;
 - attend HC@AIxIA 2024 workshop and present the paper (each attendee
should not present more than 2 works at the workshop).
The event is organized by AIxIA.


= Proceedings =
All accepted original contributions (both full and short) will be published
on CEUR-WS.org. Non-original communications will be given visibility on the
workshop website, including a link to the original publication if already
published.


= Journal Special Issue =
Workshop post-proceedings will be part of a special issue of an
international journal (TBD), provided that a sufficient amount of quality
papers is collected. In such cases, authors of accepted papers (including
non-originals, if not published in a journal yet) will be invited to submit
extended and revised versions of their papers. A review formal process will
be run to meet the expected quality of a journal.


= Working Group Meeting
All authors of accepted papers are invited to participate in the annual
meeting of the AI and Healthcare Working Group of AIxIA, which will be held
right after the workshop.


= Venue =
The workshop will be held in Bolzano, Italy; the event is organized by
AIxIA 2024 (aixia2024.events.unibz.it/).


= Committees =
See https://sites.google.com/unical.it/hcaixia2024/.


= Contacts =
All questions about submissions should be emailed to
hc-aixia@googlegroups.com.



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Dear Madam/Sir,

This is to officially announce the SEVENTH seminar of the "AI & Health"
series as hosted by HC@AIxIA, i.e., the "Artificial Intelligence for
Healthcare" working group of the Italian Association for Artificial
Intelligence. *Save the date: 16 SEPTEMBER 2024.*

We hope you will attend and participate in the discussion on the relevant
topics that will be presented and by our speakers.

*Feel free to share this with those potentially interested.*
Please find some details below, and a poster attached. All directions for
participating are available at https://aixia.it/en/gruppi/hc/.

*== Are you interested in Joining the group? ==*
Please head to https://aixia.it/en/gruppi/hc/ fo find out how. Do not
hesitate to contact us at hc-aixia@googlegroups.com for any information or
clarification.


Thank you for your interest in the AI & Health seminar series and
the HC@AIxIA working group, and see you soon!

Sincerely,
Francesco Calimeri, Mauro Dragoni, Fabio Stella
(coordinators of the HC@AIxIA working group)



*== September 2024 seminar ==*
*Link to participate: *
https://unimib.webex.com/unimib/j.php?MTID=m80c19d32afb95a9e29ef9d395a516b9c

*2024 September 16 - 4:30PM CET*
*Giuseppe Jurman*, Head of DSH (Data Science for Health) Unit, Fondazione
Bruno Kessler – FBK (Trento, Italy)

*Title*:  Generative AI in sequencing: enhancing models by synthetic omics
data.

*Abstract*: Synthetic data have recently gained momentum in several
scientific areas as an effective solution to deal with several aspects of
data poverty and missingness. In translational medicine, biomedical images
and EHR data have been the first to benefit from synthetic augmentation
techniques through generative AI algorithms such as GANs or, more recently,
Diffusion-like models. Extension of these methods to omics data poses
further challenges due to the nature of the signal, such as the need of
taking into account sample variability and multilevel omics coherence. In
this talk, we will present an overview of the state-of-the-art of the
synthetic data in the omics universe, including the generative
methodologies, the future perspectives, and the related caveats, concluding
with some applicative use cases. *(joint work with Marco Chierici and
Silvia Menchetti)*

*Short Bio*: Giuseppe Jurman is a mathematician, with a PhD in Algebra,
currently Head of the Data Science for Health (DSH) Unit at FBK. His main
interest is the development and the application of artificial intelligence,
machine learning and complex network models for diagnosis, prognosis and
prediction in medicine, life science and computational biology, starting
from EHRs, omics data and biomedical images, including digital pathology,
with a particular emphasis on reproducibility and explainability. He is
also interested in scientific programming with Python and other computing
languages, and he teaches Data Visualization at the M.Sc. in Data Science
at the University of Trento.


[image: HC@AIxIA - Seminars AI & Health 2024 - Locandina 08.png]