Publications

The State of Artificial Intelligence in Pediatric Surgery: A Systematic Review
Mohamed Elahmedi
Riya Sawhney
Elena Guadagno
Fabio Botelho
Understanding metric-related pitfalls in image analysis validation
Annika Reinke
Minu D. Tizabi
Michael Baumgartner
Matthias Eisenmann
DOREEN HECKMANN-NÖTZEL
A. EMRE KAVUR
TIM RÄDSCH
Carole H. Sudre
Laura Acion
Michela Antonelli
Spyridon Bakas
Arriel Benis
Matthew Blaschko
Florian Buettner
M. Jorge Cardoso
Veronika Cheplygina
Jianxu Chen
Evangelia Christodoulou
BETH A. CIMINI … (voir 58 de plus)
Gary S. Collins
Keyvan Farahani
LUCIANA FERRER
Adrian Galdran
Bram van Ginneken
Ben Glocker
PATRICK GODAU
Robert Haase
Daniel A. Hashimoto
Michael M. Hoffman
Merel Huisman
Fabian Isensee
Pierre Jannin
CHARLES E. KAHN
Dagmar Kainmueller
BERNHARD KAINZ
Alexandros Karargyris
Alan Karthikesalingam
Hannes Kenngott
Jens Kleesiek
Florian Kofler
Thijs Kooi
Annette Kopp-Schneider
Michal Kozubek
Anna Kreshuk
Tahsin Kurc
Bennett A. Landman
GEERT LITJENS
Amin Madani
Klaus Maier-Hein
Anne L. Martel
Peter Mattson
Erik Meijering
Bjoern Menze
Karel G. M. Moons
Henning Müller
Felix Nickel
Jens Petersen
Susanne M. Rafelski
Nasir Rajpoot
Mauricio Reyes
MICHAEL A. RIEGLER
Nicola Rieke
Julio Saez-Rodriguez
Clara I. Sánchez
Shravya Shetty
Maarten van Smeden
Ronald M. Summers
Abdel A. Taha
Aleksei Tiulpin
Sotirios A. Tsaftaris
Ben Van Calster
Manuel Wiesenfarth
Ziv R. Yaniv
PAUL F. JÄGER
Lena Maier-Hein
Validation metrics are key for the reliable tracking of scientific progress and for bridging the current chasm between artificial intelligen… (voir plus)ce (AI) research and its translation into practice. However, increasing evidence shows that particularly in image analysis, metrics are often chosen inadequately in relation to the underlying research problem. This could be attributed to a lack of accessibility of metric-related knowledge: While taking into account the individual strengths, weaknesses, and limitations of validation metrics is a critical prerequisite to making educated choices, the relevant knowledge is currently scattered and poorly accessible to individual researchers. Based on a multi-stage Delphi process conducted by a multidisciplinary expert consortium as well as extensive community feedback, the present work provides the first reliable and comprehensive common point of access to information on pitfalls related to validation metrics in image analysis. Focusing on biomedical image analysis but with the potential of transfer to other fields, the addressed pitfalls generalize across application domains and are categorized according to a newly created, domain-agnostic taxonomy. To facilitate comprehension, illustrations and specific examples accompany each pitfall. As a structured body of information accessible to researchers of all levels of expertise, this work enhances global comprehension of a key topic in image analysis validation.
Using Artificial Intelligence to Label Free-Text Operative and Ultrasound Reports for Grading Pediatric Appendicitis.
Waseem Abu-Ashour
Sister Mary Emil
Sherif Emil
Blockwise Self-Supervised Learning at Scale
Shoaib Ahmed Siddiqui
David M. Krueger
Stephane Deny
Integrating accompanying patients into clinical oncology teams: limiting and facilitating factors
Marie-Pascale Pomey
Jesseca Paquette
Monica Iliescu Nelea
Cécile Vialaron
Rim Mourad
Karine Bouchard
Louise Normandin
Marie-Andrée Côté
Mado Desforges
Pénélope Pomey-Carpentier
Israël Fortin
Isabelle Ganache
Zeev Rosberger
Danielle Charpentier
Marie-France Vachon
Lynda Bélanger
Michel Dorval
Djahanchah P. Ghadiri
Mélanie Lavoie-Tremblay … (voir 5 de plus)
Antoine Boivin
Jean-François Pelletier
Nicolas Fernandez
Alain M. Danino
Michèle de Guise
Objectives Since 2018, four establishments in Quebec have been instrumental in implementing the PAROLE-Onco program, which introduced accomp… (voir plus)anying patients (APs) in healthcare teams to improve cancer patients’ experience. APs are patient advisors who have acquired specific experiential knowledge related to living with cancer, using services, and interacting with healthcare professionals. They are therefore in a unique and reliable position to be able to provide emotional, informational, cognitive and navigational support to patients dealing with cancer. We aimed to explore APs’ perspectives regarding the limiting and facilitating factors in terms of how they are integrated into the clinical oncology teams. Methods A qualitative study based on semi-structured interviews and focus groups was conducted with 20 APs at the beginning of their intervention (T1) and two years afterwards (T2). Limiting and facilitating factors of APs’ integration into clinical teams were analyzed in terms of governance, culture, resources and tools. Results The most significant limiting factors raised by APs to be integrated into clinical teams were: governance involvement, organizational boundaries, team members' availabilities, and confusion about the specific roles played by APs. Communication challenges were also raised, leading to inadequate promotion of the program to patients. The lack of time, space and compensation were also mentioned as limiting factors. Creating opportunities for team members to meet APs, building trust and teaching team members how APs’ activities are complementary to theirs were enhancing factors. Other facilitators include APs being involved in decision-making committees, being leaders in the PAROLE-Onco program promotion to patients and clinical team members and creating opportunities to communicate with team members to help enhance their work and provide feedback to improve patient services. Awareness of APs’ added value for the team and patients is also a key facilitator. Regarding tools, offering accompanying services by telephone allows both patients and APs to benefit from the flexibility they need. Conclusion Over time, APs were able to identify the best factors for successful implementation. Recommendations include APs and professionals working in co-construction on organization, leadership, resources, and status factors. This could help catalyze a change in culture within health establishments and allow people dealing with cancer to benefit from the experiential knowledge of other patients within their clinical team.
Learning self-supervised molecular representations for drug–drug interaction prediction
Rogia Kpanou
Patrick Dallaire
Elsa Rousseau
J. Corbeil
PERFUMES: pipeline to extract RNA functional motifs and exposed structures
Arnaud Chol
Roman Sarrazin-Gendron
Éric Lécuyer
Jérôme Waldispühl
Abstract Motivation Up to 75% of the human genome encodes RNAs. The function of many non-coding RNAs relies on their ability to fold into 3D… (voir plus) structures. Specifically, nucleotides inside secondary structure loops form non-canonical base pairs that help stabilize complex local 3D structures. These RNA 3D motifs can promote specific interactions with other molecules or serve as catalytic sites. Results We introduce PERFUMES, a computational pipeline to identify 3D motifs that can be associated with observable features. Given a set of RNA sequences with associated binary experimental measurements, PERFUMES searches for RNA 3D motifs using BayesPairing2 and extracts those that are over-represented in the set of positive sequences. It also conducts a thermodynamics analysis of the structural context that can support the interpretation of the predictions. We illustrate PERFUMES’ usage on the SNRPA protein binding site, for which the tool retrieved both previously known binder motifs and new ones. Availability and implementation PERFUMES is an open-source Python package (https://jwgitlab.cs.mcgill.ca/arnaud_chol/perfumes).
The Effects of a Digital Game Simulator versus a Traditional Intervention on Paramedics’ Neonatal Resuscitation Performance
Georg M. Schmölzer
Unsupervised Discovery of Steerable Factors When Graph Deep Generative Models Are Entangled
Chengpeng Wang
Weili Nie
Hanchen Wang
Zhuoxinran Li
Bolei Zhou
Asymmetric stimulus representations bias visual perceptual learning
Pooya Laamerad
Asmara Awada
Christopher C. Pack
The primate visual cortex contains various regions that exhibit specialization for different stimulus properties, such as motion, shape, and… (voir plus) color. Within each region, there is often further specialization, such that particular stimulus features, such as horizontal and vertical orientations, are over-represented. These asymmetries are associated with well-known perceptual biases, but little is known about how they influence visual learning. Most theories would predict that learning is optimal, in the sense that it is unaffected by these asymmetries. However, other approaches to learning would result in specific patterns of perceptual biases. To distinguish between these possibilities, we trained human observers to discriminate between expanding and contracting motion patterns, which have a highly asymmetrical representation in the visual cortex. Observers exhibited biased percepts of these stimuli, and these biases were affected by training in ways that were often suboptimal. We simulated different neural network models and found that a learning rule that involved only adjustments to decision criteria, rather than connection weights, could account for our data. These results suggest that cortical asymmetries influence visual perception and that human observers often rely on suboptimal strategies for learning.
A comparison of RL-based and PID controllers for 6-DOF swimming robots: hybrid underwater object tracking
Faraz Lotfi
Khalil Virji
Nicholas Dudek
Protocol for fever control using external cooling in mechanically ventilated patients with septic shock: SEPSISCOOL II randomised controlled trial
Armelle Guénégou-Arnoux
Juliette Murris
Stéphane Bechet
Camille Jung
Johann Auchabie
Julien Dupeyrat
Nadia Anguel
Pierre Asfar
Julio Badie
Dorothée Carpentier
Benjamin Chousterman
Jeremy Bourenne
Agathe Delbove
Jérôme Devaquet
Nicolas Deye
Anne-Florence Dureau
Jean-Baptiste Lascarrou
Stephane Legriel
Christophe Guitton … (voir 14 de plus)
Caroline Jannière-Nartey
Jean-Pierre Quenot
Jean-Claude Lacherade
Julien Maizel
Armand Mekontso Dessap
Bruno Mourvillier
Philippe Petua
Gaetan Plantefeve
Jean-Christophe Richard
Alexandre Robert
Clément Saccheri
Ly Van Phach Vong
Sandrine Katsahian
Frédérique Schortgen