* Veuillez noter qu'en raison du déménagement dans nos nouveaux locaux, le rapport de veille de la semaine du 7 juin prochain sera reporté à la semaine suivante. Merci de votre compréhension. *

 

Bonjour,

Voici votre rapport de veille pour cette semaine.

Fréquence : Hebdomadaire.

Sources : Banques de données probantes, quotidiens et médias sociaux. 

Questions, ajouts et commentaires : sebastien.champagne.chum@ssss.gouv.qc.ca

 

Bonne lecture!

Au plaisir de collaborer,

 

Sébastien Champagne, M.S.I.

Bibliothécaire

Bibliothèque du CHUM

 

 

Contexte hospitalier

Creation of an artificial intelligence model for intubation difficulty classification by deep learning (convolutional neural network) using face images: an observational study

Author Names: Hayasaka T.,Kawano K.,Kurihara K.,Suzuki H.,Nakane M.,Kawamae K. Database Source: Embase Journal Title: Journal of Intensive Care,Journal of Intensive Care Article Title: Creation of an artificial intelligence model for intubation difficulty classification by deep learning (convolutional neural network) using face images: an observational …

Accéder au contenu

The Use of Artificial Neural Networks to Determine In-Hospital Mortality After Coronary Artery Bypass Surgery

Author Names: Sen E.,Seckiner S.U. Database Source: Embase Journal Title: Journal of Cardiothoracic and Vascular Anesthesia,Journal of Cardiothoracic and Vascular Anesthesia Article Title: The Use of Artificial Neural Networks to Determine In-Hospital Mortality After Coronary Artery Bypass Surgery Year: 2021 Issue: Volume: Abstract: Objectives: The aim of this …

Accéder au contenu

Automated EEG pathology detection based on different convolutional neural network models: Deep learning approach

Author Names: Bajpai R.,Yuvaraj R.,Prince A.A. Database Source: Embase Journal Title: Computers in Biology and Medicine,Computers in Biology and Medicine Article Title: Automated EEG pathology detection based on different convolutional neural network models: Deep learning approach Year: 2021 Issue: Volume: 133 Abstract: The brain electrical activity, recorded and …

Accéder au contenu

Strengths and Limitations of Machine Learning in Surgical Care

Author Names: Kelz R.R.,Airoldi E.M.,Keele L. Database Source: Embase Journal Title: Journal of the American College of Surgeons,Journal of the American College of Surgeons Article Title: Strengths and Limitations of Machine Learning in Surgical Care Year: 2021 Issue: 6 Volume: 232 Abstract:

Accéder au contenu

Smart chest X-ray worklist prioritization using artificial intelligence: a clinical workflow simulation

Author Names: Baltruschat I.,Steinmeister L.,Nickisch H.,Saalbach A.,Grass M.,Adam G.,Knopp T.,Ittrich H. Database Source: Embase Journal Title: European Radiology,European Radiology Article Title: Smart chest X-ray worklist prioritization using artificial intelligence: a clinical workflow simulation Year: 2021 Issue: 6 Volume: 31 Abstract: Objective: The aim is to …

Accéder au contenu

AI in patient flow: applications of artificial intelligence to improve patient flow in NHS acute mental health inpatient units

Heliyon. 2021 May 12;7(5):e06993. doi: 10.1016/j.heliyon.2021.e06993. eCollection 2021 May.ABSTRACTINTRODUCTION: Growing demand for mental health services, coupled with funding and resource limitations, creates an opportunity for novel technological solutions including artificial intelligence (AI). This study aims to identify issues in patient flow on mental health units and align them with …

Accéder au contenu

Artificial intelligence in clinical decision support and outcome prediction - applications in stroke

J Med Imaging Radiat Oncol. 2021 May 28. doi: 10.1111/1754-9485.13193. Online ahead of print.ABSTRACTArtificial intelligence (AI) is making a profound impact in healthcare, with the number of AI applications in medicine increasing substantially over the past five years. In acute stroke, it is playing an increasingly important role in clinical decision-making. …

Accéder au contenu

Artificial Intelligence for Clinical Decision Support in Sepsis

Front Med (Lausanne). 2021 May 13;8:665464. doi: 10.3389/fmed.2021.665464. eCollection 2021.ABSTRACTSepsis is one of the main causes of death in critically ill patients. Despite the continuous development of medical technology in recent years, its morbidity and mortality are still high. This is mainly related to the delay in starting treatment and non-adherence of …

Accéder au contenu

Impact of ECG Characteristics on the Performance of an Artificial Intelligence Enabled ECG for Predicting Left Ventricular Dysfunction

Circ Arrhythm Electrophysiol. 2021 May;14(5):e009871. doi: 10.1161/CIRCEP.121.009871. Epub 2021 May 17.NO ABSTRACTPMID:33993719 | DOI:10.1161/CIRCEP.121.009871

Accéder au contenu

Gestion

Artificial intelligence derived literature searches can provide more relevant data, more quickly than traditional reference databases: a case study

Author Names: Michelson M.,Dogra R.,Goldberg N. Database Source: Embase Journal Title: Current Medical Research and Opinion Article Title: Artificial intelligence derived literature searches can provide more relevant data, more quickly than traditional reference databases: a case study Year: 2021 Issue: SUPPL 1 Volume: 37 Abstract: Objective: Artificial intelligence (AI)-led applications …

Accéder au contenu

To buy or not to buy-evaluating commercial AI solutions in radiology (the ECLAIR guidelines)

Author Names: Omoumi P.,Ducarouge A.,Tournier A.,Harvey H.,Kahn C.E.,Louvet-de Verchere F.,Pinto Dos Santos D.,Kober T.,Richiardi J. Database Source: Embase Journal Title: European Radiology,European Radiology Article Title: To buy or not to buy-evaluating commercial AI solutions in radiology (the ECLAIR guidelines) Year: 2021 …

Accéder au contenu

From clinical decision support to clinical reasoning support systems.

Journal of Evaluation in Clinical Practice; 06/01/2021Despite the great promises that artificial intelligence (AI) holds for health care, the uptake of such technologies into medical practice is slow. In this paper, we focus on the epistemological issues arising from the development and implementation of a class of AI for clinical …

Accéder au contenu

A Deep Learning Framework for Automated ICD-10 Coding

Stud Health Technol Inform. 2021 May 27;281:347-351. doi: 10.3233/SHTI210178.ABSTRACTThe International Statistical Classification of Diseases and Related Health Problems (ICD) is one of the widely used classification system for diagnoses and procedures to assign diagnosis codes to Electronic Health Record (EHR) associated with a patient's stay. The aim of this …

Accéder au contenu

How to Establish an Automation Center of Excellence

Email Updates on AI, Data, & Machine Learning. Get monthly email updates on how artificial intelligence and big data are affecting the development and ...

Accéder au contenu

Rethinking Industry's Role in a National Emergency

The U.S.'s approach to its Strategic National Stockpile needs to be overhauled before the next pandemic. Here's how.

Accéder au contenu

Enseignement et recherche

The Role of Simulation in Attaining Proficiency in Minimally Invasive Hepatopancreatobiliary Surgery

J Laparoendosc Adv Surg Tech A. 2021 May;31(5):561-564. doi: 10.1089/lap.2021.0083.ABSTRACTThe implementation of robotic surgery in the field of hepato-pancreato-biliary (HPB) has been a slow but significant process. HPB procedures offer a unique challenge when for new technologies, as the surgeries themselves are complex, with long learning curves. Yet the …

Accéder au contenu

The Evolving Importance of Artificial Intelligence and Radiology in Medical Trainee Education

Author Names: Fischetti C.,Bhatter P.,Frisch E.,Sidhu A.,Helmy M.,Lungren M.,Duhaime E. Database Source: Embase Journal Title: Academic Radiology,Academic Radiology Article Title: The Evolving Importance of Artificial Intelligence and Radiology in Medical Trainee Education Year: 2021 Issue: Volume: Abstract: Radiology education is understood to be an …

Accéder au contenu

The Value of Artificial Intelligence in Laboratory Medicine

Author Names: Paranjape K.,Schinkel M.,Hammer R.D.,Schouten B.,Nannan Panday R.S.,Elbers P.W.G.,Kramer M.H.H.,Nanayakkara P. Database Source: Embase Journal Title: American journal of clinical pathology Article Title: The Value of Artificial Intelligence in Laboratory Medicine Year: 2021 Issue: 6 Volume: 155 Abstract: OBJECTIVES: …

Accéder au contenu

Enjeux éthiques

A Proposed Framework on Integrating Health Equity and Racial Justice into the Artificial Intelligence Development Lifecycle.

Journal of Health Care for the Poor & Underserved; 05/02/2021The COVID-19 pandemic has created multiple opportunities to deploy artificial intelligence (AI)-driven tools and applied interventions to understand, mitigate, and manage the pandemic and its consequences. The disproportionate impact of COVID-19 on racial/ethnic minority and socially disadvantaged populations underscores …

Accéder au contenu

A Perspective on Building Ethical Datasets for Children's Conversational Agents

Front Artif Intell. 2021 May 13;4:637532. doi: 10.3389/frai.2021.637532. eCollection 2021.ABSTRACTArtificial intelligence (AI)-powered technologies are becoming an integral part of youth's environments, impacting how they socialize and learn. Children (12 years of age and younger) often interact with AI through conversational agents (e.g., Siri and Alexa) that they speak with to …

Accéder au contenu

Is There an App for That?: Ethical Issues in the Digital Mental Health Response to COVID-19

Author Names: Skorburg J.A.,Yam J. Database Source: Embase Journal Title: AJOB neuroscience Article Title: Is There an App for That?: Ethical Issues in the Digital Mental Health Response to COVID-19 Year: 2021 Issue: Volume: Abstract: Well before COVID-19, there was growing excitement about the potential of various digital technologies …

Accéder au contenu

Mapping out the philosophical questions of AI and clinical practice in diagnosing and treating mental disorders.

Journal of Evaluation in Clinical Practice; 06/01/2021How to classify the human condition? This is one of the main problems psychiatry has struggled with since the first diagnostic systems. The furore over the recent editions of the diagnostic systems DSM‐5 and ICD‐11 has evidenced it to still pose a wicked problem. …

Accéder au contenu

Conflicting roles for humans in learning health systems and AI‐enabled healthcare.

Journal of Evaluation in Clinical Practice; 06/01/2021The goals of learning health systems (LHS) and of AI in medicine overlap in many respects. Both require significant improvements in data sharing and IT infrastructure, aim to provide more personalized care for patients, and strive to break down traditional barriers between research and …

Accéder au contenu

Evaluation of artificial intelligence clinical applications: Detailed case analyses show value of healthcare ethics approach in identifying patient care issues

Bioethics. 2021 May 28. doi: 10.1111/bioe.12885. Online ahead of print.ABSTRACTThis paper is one of the first to analyse the ethical implications of specific healthcare artificial intelligence (AI) applications, and the first to provide a detailed analysis of AI-based systems for clinical decision support. AI is increasingly being deployed across multiple domains. …

Accéder au contenu

IA en oncologie

Brain tumor segmentation based on deep learning and an attention mechanism using MRI multi-modalities brain images

Sci Rep. 2021 May 25;11(1):10930. doi: 10.1038/s41598-021-90428-8.ABSTRACTBrain tumor localization and segmentation from magnetic resonance imaging (MRI) are hard and important tasks for several applications in the field of medical analysis. As each brain imaging modality gives unique and key details related to each part of the tumor, many …

Accéder au contenu

How can artificial intelligence models assist PD-L1 expression scoring in breast cancer: results of multi-institutional ring studies

NPJ Breast Cancer. 2021 May 26;7(1):61. doi: 10.1038/s41523-021-00268-y.ABSTRACTProgrammed death ligand-1 (PD-L1) expression is a key biomarker to screen patients for PD-1/PD-L1-targeted immunotherapy. However, a subjective assessment guide on PD-L1 expression of tumor-infiltrating immune cells (IC) scoring is currently adopted in clinical practice with low concordance. Therefore, …

Accéder au contenu

Artificial Intelligence Based on Blood Biomarkers Including CTCs Predicts Outcomes in Epithelial Ovarian Cancer: A Prospective Study

Onco Targets Ther. 2021 May 18;14:3267-3280. doi: 10.2147/OTT.S307546. eCollection 2021.ABSTRACTOBJECTIVE: We aimed to develop an ovarian cancer-specific predictive framework for clinical use platinum-sensitivity and prognosis using machine learning methods based on multiple biomarkers, including circulating tumor cells (CTCs).PATIENTS AND METHODS: We enrolled 156 epithelial ovarian cancer (EOC) patients, randomly assigned …

Accéder au contenu

Deep learning analysis of the primary tumour and the prediction of lymph node metastases in gastric cancer

Br J Surg. 2021 May 27;108(5):542-549. doi: 10.1002/bjs.11928.ABSTRACTBACKGROUND: Lymph node metastasis (LNM) in gastric cancer is a prognostic factor and has implications for the extent of lymph node dissection. The lymphatic drainage of the stomach involves multiple nodal stations with different risks of metastases. The aim of this study was …

Accéder au contenu

Using Interpretable Deep Learning to Model Cancer Dependencies

Bioinformatics. 2021 May 27:btab137. doi: 10.1093/bioinformatics/btab137. Online ahead of print.ABSTRACTMOTIVATION: Cancer dependencies provide potential drug targets. Unfortunately, dependencies differ among cancers and even individuals. To this end, visible neural networks (VNNs) are promising due to robust performance and the interpretability required for the biomedical field.RESULTS: We design Biological …

Accéder au contenu

Deep learning for predicting COVID-19 malignant progression

Med Image Anal. 2021 May 12;72:102096. doi: 10.1016/j.media.2021.102096. Online ahead of print.ABSTRACTAs COVID-19 is highly infectious, many patients can simultaneously flood into hospitals for diagnosis and treatment, which has greatly challenged public medical systems. Treatment priority is often determined by the symptom severity based on first assessment. However, clinical observation …

Accéder au contenu

Uncertainty quantification in skin cancer classification using three-way decision-based Bayesian deep learning

Comput Biol Med. 2021 Apr 28:104418. doi: 10.1016/j.compbiomed.2021.104418. Online ahead of print.ABSTRACTAccurate automated medical image recognition, including classification and segmentation, is one of the most challenging tasks in medical image analysis. Recently, deep learning methods have achieved remarkable success in medical image classification and segmentation, clearly becoming the state-of-the-art methods. …

Accéder au contenu

LiverNet: efficient and robust deep learning model for automatic diagnosis of sub-types of liver hepatocellular carcinoma cancer from H&E stained liver histopathology images

Int J Comput Assist Radiol Surg. 2021 May 30. doi: 10.1007/s11548-021-02410-4. Online ahead of print.ABSTRACTPURPOSE: Liver cancer is one of the most common types of cancers in Asia with a high mortality rate. A common method for liver cancer diagnosis is the manual examination of histopathology images. Due …

Accéder au contenu

Prognostic Models for Nonmetastatic Triple-Negative Breast Cancer Based on the Pretreatment Serum Tumor Markers with Machine Learning

J Oncol. 2021 May 15;2021:6641421. doi: 10.1155/2021/6641421. eCollection 2021.ABSTRACTPURPOSE: Triple-negative breast cancer (TNBC) is a heterogeneous and aggressive disease with poorer prognosis than other subtypes. We aimed to investigate the prognostic efficacy of multiple tumor markers and constructed a prognostic model for stage I-III TNBC patients. Patients and Methods. We included stage I-III …

Accéder au contenu

Machine Learning Based Risk Prediction Models for Oral Squamous Cell Carcinoma Using Salivary Biomarkers

Stud Health Technol Inform. 2021 May 27;281:498-499. doi: 10.3233/SHTI210213.ABSTRACTTumor-associated autoantibodies can be used as biomarkers for detecting different types of cancers. Our objective was to use machine learning techniques to predict high-risk cases of oral squamous cell carcinoma (OSCC) with salivary autoantibodies. The optimal model was using eXtreme Gradient Boosting (…

Accéder au contenu

Entreprises

Overwhelmed by the huge number of attendees to our presentation today at @TheAACE annual meeting. @bigfoot_ceo Jeffrey Brewer emphasized how our personal experiences, including his son’s journey with T1D, drive us to find better solutions. #BigfootBioMed #AACE2021

Overwhelmed by the huge number of attendees to our presentation today at @TheAACE annual meeting. @bigfoot_ceo Jeffrey Brewer emphasized how our personal experiences, including his son’s journey with T1D, drive us to find better solutions.#BigfootBioMed #AACE2021

Accéder au contenu

We Make Tomorrow: On becoming a biological data scientist

Back to All Blog Posts May 26, 2021 We Make Tomorrow: On becoming a biological data scientist Senior Data Scientist Janet Matsen talks about her career path, her typical work day, trends in the field, and getting your foot in the door. The road to better biofacturing is paved with the stones …

Accéder au contenu

Studies have detailed the pandemic’s outsize impact on #mammography volumes, with drops as severe as 90% at certain points. Fresh information is now underlying how these trends are hitting women of color harder than others. radiologybusiness.com/topics/imaging…

Studies have detailed the pandemic’s outsize impact on #mammography volumes, with drops as severe as 90% at certain points. Fresh information is now underlying how these trends are hitting women of color harder than others. radiologybusiness.com/topics/imaging…

Accéder au contenu

Osteomalacia and osteoporosis are two different conditions that affect the bones. Knowing the difference between the two can help you talk with a medical professional about your symptoms and get the appropriate diagnosis and treatment. healthline.com/health/managin…

Osteomalacia and osteoporosis are two different conditions that affect the bones. Knowing the difference between the two can help you talk with a medical professional about your symptoms and get the appropriate diagnosis and treatment.healthline.com/health/managin…

Accéder au contenu

Recommendations for Reporting of Secondary Findings in Clinical Exome and Genome Sequencing

Nature Genetics in Medicine, Tempus-authored — 2021 Update: A Policy Statement of the American College of Medical Genetics and Genomics (ACMG) View the full publication here. Authors: David T. Miller, Kristy Lee, Adam S. Gordon, Laura M. Amendola, Kathy Adelman, Sherri J. Bale, Wendy K. Chung, Michael H. Gollob, Steven M. Harrison, …

Accéder au contenu

Tempus Announces Eleven Abstracts Accepted for Presentation at the 2021 American Society of Clinical Oncology Annual Meeting

Tempus, a leader in artificial intelligence and precision medicine, today announced eleven abstracts accepted for presentation at the 2021 American Society of Clinical Oncology (ASCO) Annual Meeting taking place virtually from June 4 – 8. “These high impact ASCO presentations from Tempus collaborators and investigators illustrate the power of over 35 petabytes worth of clinical …

Accéder au contenu

Qynapse reaffirms its commitment to research in Multiple Sclerosis and is pleased to announce new projects to advance research and clinical care for MS patients

Qynapse reaffirms its commitment to research in Multiple Sclerosis and is pleased to announce new projects to advance research and clinical care for MS patients BOSTON, MA, May 30, 2021 – QYNAPSE Inc., an AI neuroimaging medical technology company, joins the global multiple sclerosis (MS) community in recognition of World MS Day to …

Accéder au contenu

🏥 Vous désirez en apprendre davantage sur la nouvelle Zone d’innovation Intelligence Artificielle (IA) Santé située dans le Grand #Montréal? Venez écouter notre directrice, Développement des affaires, SVTS, Stephanie Doyle, lors de cette conférence 👉sites.grenadine.co/sites/chum/fr/…

🏥 Vous désirez en apprendre davantage sur la nouvelle Zone d’innovation Intelligence Artificielle (IA) Santé située dans le Grand #Montréal?Venez écouter notre directrice, Développement des affaires, SVTS, Stephanie Doyle, lors de cette conférence 👉sites.grenadine.co/sites/chum/fr/…

Accéder au contenu

Quelles mesures juridiques le Canada doit-il prendre pour optimiser les avantages de l’IA en santé + minimiser les risques? Partie 2 d’un rapport soutenu par le programme IA & société du CIFAR dirigé par @ColleenFlood2 @uOttawa 📖bit.ly/3bT54SH 💡bit.ly/2Sz4O4x

Quelles mesures juridiques le Canada doit-il prendre pour optimiser les avantages de l’IA en santé + minimiser les risques? Partie 2 d’un rapport soutenu par le programme IA & société du CIFAR dirigé par @ColleenFlood2 @uOttawa📖bit.ly/3bT54SH💡bit.ly/2Sz4O4x

Accéder au contenu

A Browsable Petascale Reconstruction of the Human Cortex

Posted by Tim Blakely, Software Engineer and Michał Januszewski, Research Scientist, Connectomics at Google In January 2020 we released the fly “hemibrain” connectome — an online database providing the morphological structure and synaptic connectivity of roughly half of the brain of a fruit fly (Drosophila melanogaster). This database and its supporting visualization …

Accéder au contenu

Revue de presse

Le Canada a besoin d’une stratégie nationale pour accélérer le déploiement de l’IA en santé

Grâce aux données massives, l’IA pourrait permettre d'estimer les risques de développer une maladie au cours de sa vie en se basant sur de des centaines de facteurs de risque. (Shutterstock)Le Canada est un chef de file dans le domaine de la recherche et …

Accéder au contenu

The Guardian view on medical records: NHS data grab needs explaining | Editorial

In England, ministers’ plans to suck up GP records need to be scrapped and restarted with a proper debate about their use and privacy implicationsThe government wants to extract the general practice history of every patient in England by 1 July. Haven’t you heard? Ministers are not exactly shouting about …

Accéder au contenu

Italy's digital health strategy and future plans set to be showcased at #HIMSS21Europe

Italy's digital health strategy and future plans set to be showcased at # ... state of digital healthcare is in and what the future may hold across the continent. ... artificial intelligence platforms, point-of-care diagnostics and on platforms ... Synthetic data's growing role in healthcare AI, machine learning and ...

Accéder au contenu

Ada Health secures $90M Series B funding to advance health assessment technology

Ada Health has developed an AI-based health assessment and care ... in healthcare is one of the strategic imperatives for Leaps by Bayer and for the ... powerful artificial intelligence with an emphasis on medical rigour and high ... Healthcare IT News · Healthcare IT News Australia · Healthcare Finance ...

Accéder au contenu

The imaging AI field is exploding, but it carries unique challenges

The use of machine learning and artificial intelligence to analyze medical imaging ... Population health, meanwhile, involves risk-stratifying populations to ... "Without solving these challenges it is difficult to scale AI in the healthcare domain," he said. ... Kat Jercich is senior editor of Healthcare IT News.

Accéder au contenu

Pour obtenir les articles

L'accès au texte intégral des documents est restreint au personnel et aux médecins du CHUM en fonction des abonnements de la bibliothèque. Certains documents sont en accès libre sur le web.

Si vous êtes branchés sur le réseau CHUM :

  • Cliquer sur les liens fournis pour chaque référence pour vérifier la disponibilité du texte intégral.
  • Pour les articles provenant de PubMed, cliquer préalablement sur le lien suivant pour afficher la disponibilité du document.

Si vous êtes dans un autre établissement et que vous n’arrivez pas à accéder au texte intégral d’un article à partir du lien donné, vérifier auprès de la bibliothèque de votre institution en donnant la référence complète du document.


Avis de non-responsabilité

1. EXCLUSION DE GARANTIES ET LIMITATION DE RESPONSABILITÉS

Le contenu des veilles informationnelles ou stratégiques (ci-après appelée « Veilles ») est mis à votre disposition à titre informatif pour un usage personnel exclusif. Tout usage commercial du contenu des Veilles est strictement interdit.

Tous les éléments, articles, rapports ou toute autre source d’information figurant dans les Veilles, vous sont fournis «tels quels», sans garantie d’aucune sorte. Eu égard aux propos tenus dans les articles et les rapports sélectionnés pour les Veilles, le CHUM n’offre aucune garantie notamment d’exhaustivité, de fiabilité, d’actualité et d’exactitude.

Le CHUM ne pourra en aucun cas être tenu responsable envers quiconque de tout dommage quel qu’il soit, même ceux directs, encouru notamment des suites de toute réclamation, action ou poursuite découlant, même directement, de l’utilisation de ces Veilles.

2. RESPONSABILITÉ RELATIVE AUX LIENS

Les Veilles contiennent des liens vers des sites Web créés et mis à jour par des tierces parties. Ces liens sont fournis pour la commodité des utilisateurs seulement. Le CHUM n’endosse et ne garantit, ni explicitement ni implicitement, l’exactitude ou l’intégralité ni du contenu de ces hyperliens ni des opinions qui y sont exprimées.

Le CHUM n’assume aucune responsabilité à l’égard de ces sites Web externes.

3. PROPRIÉTÉ INTELLECTUELLE

Le CHUM prend tous les moyens raisonnables afin de respecter les droits de propriété intellectuelle afférents au contenu des Veilles et aux modalités du prêt entre bibliothèques, émises par l’Université de Montréal. Le contenu des Veilles, incluant la manière dont il est présenté, sont notamment protégés par la Loi sur le droit d’auteur (L.R.C. (1985), ch. C-42).

Le CHUM ne donne aucune garantie et ne fait aucune déclaration à l’effet que le contenu de ces veilles n’enfreint aucun droit d’une autre personne ou entité.

Les téléchargements et reproduction en un seul exemplaire, pour copie de sauvegarde de ces Veilles ou tirage sur papier ne sont autorisés que pour un usage privé et non commercial. Tout téléchargement, reproduction, édition, diffusion sur Internet ou l’utilisation à des fins commerciales ou publiques, la distribution, la publication sur un autre site ou sur quelque autre forme et toute autre utilisation est interdite à moins d’être faite dans le respect des règles de propriété intellectuelle applicables, et nécessitent notamment l’autorisation de l’auteur ou du créateur.

Pour obtenir cette autorisation à l’égard des Veilles, veuillez communiquer avec la Bibliothèque du CHUM, biblio.chum@ssss.gouv.qc.ca.