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

Machine Learning Applications in Heart Failure Disease Management: Hype or Hope?

Author Names: Greenberg B.,Brann A.,Campagnari C.,Adler E.,Yagil A. Database Source: Embase Journal Title: Current Treatment Options in Cardiovascular Medicine,Current Treatment Options in Cardiovascular Medicine Article Title: Machine Learning Applications in Heart Failure Disease Management: Hype or Hope? Year: 2021 Issue: 6 Volume: 23 Abstract: Purpose of the review: …

Accéder au contenu

Chronic cholestasis detection by a novel tool: automated analysis of cytokeratin 7-stained liver specimens

Author Names: Sjoblom N.,Boyd S.,Manninen A.,Knuuttila A.,Blom S.,Farkkila M.,Arola J. Database Source: Embase Journal Title: Diagnostic pathology Article Title: Chronic cholestasis detection by a novel tool: automated analysis of cytokeratin 7-stained liver specimens Year: 2021 Issue: 1 Volume: 16 Abstract: BACKGROUND: The objective was to build a …

Accéder au contenu

Differentiation of inflammatory from degenerative changes in the sacroiliac joints by machine learning supported texture analysis

Author Names: Kepp F.H.,Huber F.A.,Wurnig M.C.,Mannil M.,Kaniewska M.,Guglielmi R.,Del Grande F.,Guggenberger R. Database Source: Embase Journal Title: European Journal of Radiology,European Journal of Radiology Article Title: Differentiation of inflammatory from degenerative changes in the sacroiliac joints by machine learning …

Accéder au contenu

Artificial intelligence in musculoskeletal imaging: a perspective on value propositions, clinical use, and obstacles

Skeletal Radiol. 2021 May 13. doi: 10.1007/s00256-021-03802-y. Online ahead of print.ABSTRACTArtificial intelligence and deep learning (DL) offer musculoskeletal radiology exciting possibilities in multiple areas, including image reconstruction and transformation, tissue segmentation, workflow support, and disease detection. Novel DL-based image reconstruction algorithms correcting aliasing artifacts, signal loss, and noise …

Accéder au contenu

Presenting artificial intelligence, deep learning, and machine learning studies to clinicians and healthcare stakeholders: an introductory reference with a guideline and a Clinical AI Research (CAIR) checklist proposal

Acta Orthop. 2021 May 14:1-13. doi: 10.1080/17453674.2021.1918389. Online ahead of print.ABSTRACTBackground and purpose - Artificial intelligence (AI), deep learning (DL), and machine learning (ML) have become common research fields in orthopedics and medicine in general. Engineers perform much of the work. While they gear the results towards healthcare professionals, the difference …

Accéder au contenu

Artificial intelligence: A rapid case for advancement in the personalization of Gynaecology/Obstetric and Mental Health care

Womens Health (Lond). 2021 Jan-Dec;17:17455065211018111. doi: 10.1177/17455065211018111.ABSTRACTTo evaluate and holistically treat the mental health sequelae and potential psychiatric comorbidities associated with obstetric and gynaecological conditions, it is important to optimize patient care, ensure efficient use of limited resources and improve health-economic models. Artificial intelligence applications could assist in achieving the above. …

Accéder au contenu

Machine Learning and Syncope Management in the ED: The Future Is Coming

Medicina (Kaunas). 2021 Apr 6;57(4):351. doi: 10.3390/medicina57040351.ABSTRACTIn recent years, machine learning (ML) has been promisingly applied in many fields of clinical medicine, both for diagnosis and prognosis prediction. Aims of this narrative review were to summarize the basic concepts of ML applied to clinical medicine and explore its main applications in …

Accéder au contenu

Gestion

A robust ensemble technique in forecasting workload of local healthcare departments

Author Names: Piccialli F.,Giampaolo F.,Salvi A.,Cuomo S. Database Source: Embase Journal Title: Neurocomputing,Neurocomputing Article Title: A robust ensemble technique in forecasting workload of local healthcare departments Year: 2021 Issue: Volume: 444 Abstract: With the exponential growth of the Internet of Things and Cloud Computing, especially in recent years, …

Accéder au contenu

Taming Artificial Intelligence’s Can/Should Problem | Ayanna Howard and Deven Desai

Our expert columnists offer opinion and analysis on important issues facing modern businesses and managers. More in this series What to Read Next Bias in artificial intelligence seems to be an unending and endemic problem. Arguments abound about whether problems arise because the data going into AI analysis is biased, …

Accéder au contenu

Enseignement et recherche

A reinforcement learning based algorithm for personalization of digital, just-in-time, adaptive interventions

Artificial Intelligence in Medicine, Volume 115, 2021 May, Article 102062 | Gönül, Suat; Namlı, Tuncay; Coşar, Ahmet;...Highlights•Personalized lifestyle patterns can be captured with reinforcement learning •Habit formation can be simulated realistically •Reinforcement learning can provide personalized self-management support •Personalized self-management support i...

Accéder au contenu

Machine learning in oral squamous cell carcinoma: Current status, clinical concerns and prospects for future—A systematic review

Artificial Intelligence in Medicine, Volume 115, 2021 May, Article 102060 | Alabi, Rasheed Omobolaji; Youssef, Omar; Pirinen, Matti;...Highlights•This study reviews the published studies on the application of machine learning techniques for oral squamous cell carcinoma. •It examines the concerns and limitations to the actual implementation of machine learning-based models in clin...

Accéder au contenu

EAR-UNet: A deep learning-based approach for segmentation of tympanic membranes from otoscopic images

Artificial Intelligence in Medicine, Volume 115, 2021 May, Article 102065 | Pham, Van-Truong; Tran, Thi-Thao; Wang, Pa-Chun;...Highlights•This study presents a deep learning based-approach for fully automatic image segmentation of tympanic membranes. •The proposed EAR-Unet composes of three main paradigms: EfficientNet for encoder; Attention gate for skip connection; ResN...

Accéder au contenu

A hybrid deep learning approach for gland segmentation in prostate histopathological images

Artificial Intelligence in Medicine, Volume 115, 2021 May, Article 102076 | Salvi, Massimo; Bosco, Martino; Molinaro, Luca;...Highlights•Gland architecture plays a crucial role in prostate cancer reporting. •A new hybrid deep learning method is presented to segment prostate glands. •A softmax-driven active contour model is proposed to detect the glandular areas. •No perf...

Accéder au contenu

Automated emotion classification in the early stages of cortical processing: An MEG study

Artificial Intelligence in Medicine, Volume 115, 2021 May, Article 102063 | Kheirkhah, Mina; Brodoehl, Stefan; Leistritz, Lutz;...Highlights•The automated classification of human emotions is feasible in very early time-intervals within 100–300 ms post-stimulus. •MEG is well suited to automatically classify human emotions very early with high performances. •This study suggest...

Accéder au contenu

A novel approach for computerized quantitative image analysis of proximal femur bone shape deformities based on the hip joint symmetry

Artificial Intelligence in Medicine, Volume 115, 2021 May, Article 102057 | Memiş, Abbas; Varlı, Songül; Bilgili, FuatGraphical abstract Highlights•A novel approach was proposed for proximal femur shape deformity quantification. •Deformities in proximal femurs were quantified using the hip joint symmetry in 2D. •Bilateral MRI slices of Legg-Calve-Perthes disease ...

Accéder au contenu

Challenges and solutions to employing natural language processing and machine learning to measure patients' health literacy and physician writing complexity: The ECLIPPSE study

Author Names: Brown W.,Balyan R.,Karter A.J.,Crossley S.,Semere W.,Duran N.D.,Lyles C.,Liu J.,Moffet H.H.,Daniels R.,McNamara D.S.,Schillinger D. Database Source: Embase Journal Title: Journal of Biomedical Informatics,Journal of Biomedical Informatics Article Title: Challenges and solutions to employing …

Accéder au contenu

Is artificial intelligence really a new topic in medical education?

Author Names: Sonicki Z.,Kern J. Database Source: Embase Journal Title: Croatian medical journal Article Title: Is artificial intelligence really a new topic in medical education? Year: 2021 Issue: 2 Volume: 62 Abstract:

Accéder au contenu

Effects of computer-based education on health professionals' knowledge, skills, and behavior: A scoping review

Author Names: Hussein R.,Lin E.C.J.,Grindrod K. Database Source: Embase Journal Title: Journal of the American Pharmacists Association,Journal of the American Pharmacists Association Article Title: Effects of computer-based education on health professionals' knowledge, skills, and behavior: A scoping review Year: 2021 Issue: 3 Volume: 61 Abstract: Background: Computer-based platforms …

Accéder au contenu

Enjeux éthiques

Addressing Fairness, Bias, and Appropriate Use of Artificial Intelligence and Machine Learning in Global Health

Front Artif Intell. 2021 Apr 15;3:561802. doi: 10.3389/frai.2020.561802. eCollection 2020.ABSTRACTIn Low- and Middle- Income Countries (LMICs), machine learning (ML) and artificial intelligence (AI) offer attractive solutions to address the shortage of health care resources and improve the capacity of the local health care infrastructure. However, AI and ML should also be used …

Accéder au contenu

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

AJOB Neurosci. 2021 May 14:1-14. doi: 10.1080/21507740.2021.1918284. Online ahead of print.ABSTRACTWell before COVID-19, there was growing excitement about the potential of various digital technologies such as tele-health, smartphone apps, or AI chatbots to revolutionize mental healthcare. As the SARS-CoV-2 virus spread across the globe, clinicians warned of the mental illness epidemic …

Accéder au contenu

Attacking and defence pathways for Intelligent Medical Diagnosis System (IMDS)

Author Names: He Y.,Camacho R.S.,Soygazi H.,Luo C. Database Source: Embase Journal Title: International Journal of Medical Informatics,International Journal of Medical Informatics Article Title: Attacking and defence pathways for Intelligent Medical Diagnosis System (IMDS) Year: 2021 Issue: Volume: 148 Abstract: Background: The Intelligent Medical Diagnosis System (IMDS) has …

Accéder au contenu

Ethical evaluation of artificial intelligence applications in radiotherapy using the Four Topics Approach.

Artificial Intelligence in Medicine; 05/01/2021(AN 150290115); ISSN: 09333657CINAHL Complete

Accéder au contenu

IA en oncologie

How AI and data analytics can impact oncology

Professor Karol Sikora, chief medical officer at Rutherford Health, discusses how artificial intelligence and analytics can address the most pressing ...

Accéder au contenu

Application of artificial intelligence in gynecologic malignancies: A review

J Obstet Gynaecol Res. 2021 May 10. doi: 10.1111/jog.14818. Online ahead of print.ABSTRACTWith the development of machine learning and deep learning models, artificial intelligence is now being applied to the field of medicine. In oncology, the use of artificial intelligence for the diagnostic evaluation of medical images such as radiographic images, …

Accéder au contenu

The use of artificial intelligence for the diagnosis of bladder cancer: a review and perspectives

Curr Opin Urol. 2021 May 11. doi: 10.1097/MOU.0000000000000900. Online ahead of print.ABSTRACTPURPOSE OF REVIEW: White light cystoscopy is the current standard for primary diagnosis and surveillance of bladder cancer. However, cancer changes can be subtle and may be easily missed. With the advancement of deep learning (DL), image recognition by artificial …

Accéder au contenu

A deep learning system to diagnose the malignant potential of urothelial carcinoma cells in cytology specimens

Cancer Cytopathol. 2021 May 12. doi: 10.1002/cncy.22443. Online ahead of print.ABSTRACTBACKGROUND: Although deep learning algorithms for clinical cytology have recently been developed, their application to practical assistance systems has not been achieved. In addition, whether deep learning systems (DLSs) can perform diagnoses that cannot be performed by pathologists has not been …

Accéder au contenu

Green-colored areas in laterally spreading tumors on narrow-band imaging: a future target for artificial-intelligence-assisted detection of malignancies?

Endoscopy. 2021 May 12. doi: 10.1055/a-1488-6297. Online ahead of print.NO ABSTRACTPMID:33979853 | DOI:10.1055/a-1488-6297

Accéder au contenu

Predicting optimal treatment regimens for patients with HR+/HER2- breast cancer using machine learning based on electronic health records

J Comp Eff Res. 2021 May 13. doi: 10.2217/cer-2020-0230. Online ahead of print.ABSTRACTAim: To predict optimal treatments maximizing overall survival (OS) and time to treatment discontinuation (TTD) for patients with metastatic breast cancer (MBC) using machine learning methods on electronic health records. Patients/methods: Adult females with HR+/HER2- …

Accéder au contenu

Differentiation Between Malignant and Benign Endoscopic Images of Gastric Ulcers Using Deep Learning

Clin Exp Gastroenterol. 2021 May 5;14:155-162. doi: 10.2147/CEG.S292857. eCollection 2021.ABSTRACTBACKGROUND AND AIM: Endoscopic differentiation between malignant and benign gastric ulcers (GU) affects further evaluation and prognosis. The aim of our study was to evaluate a deep learning algorithm for discrimination between benign and malignant GU in a database of endoscopic …

Accéder au contenu

CT imaging-based machine learning model: a potential modality for predicting low-risk and high-risk groups of thymoma: "Impact of surgical modality choice"

World J Surg Oncol. 2021 May 11;19(1):147. doi: 10.1186/s12957-021-02259-6.ABSTRACTINTRODUCTION: Radiomics methods are used to analyze various medical images, including computed tomography (CT), magnetic resonance, and positron emission tomography to provide information regarding the diagnosis, patient outcome, tumor phenotype, and the gene-protein signatures of various diseases. In low-risk group, …

Accéder au contenu

An application of machine learning based on real-world data: Mining features of fibrinogen in clinical stages of lung cancer between sexes

Ann Transl Med. 2021 Apr;9(8):623. doi: 10.21037/atm-20-4704.ABSTRACTBACKGROUND: Lung cancer is the most threatening malignant tumor to human health and life. Using a variety of machine learning algorithms and statistical analyses, this paper explores, discovers and demonstrates new indicators for the early diagnosis of lung cancer and their diagnostic performance …

Accéder au contenu

Integrating multi-omics data through deep learning for accurate cancer prognosis prediction

Comput Biol Med. 2021 May 9;134:104481. doi: 10.1016/j.compbiomed.2021.104481. Online ahead of print.ABSTRACTBACKGROUND: Genomic information is nowadays widely used for precise cancer treatments. Since the individual type of omics data only represents a single view that suffers from data noise and bias, multiple types of omics data are required for accurate …

Accéder au contenu

Hopes and hypes for artificial intelligence in colorectal cancer screening

Gastroenterology. 2021 May 11:S0016-5085(21)02973-5. doi: 10.1053/j.gastro.2021.04.078. Online ahead of print.NO ABSTRACTPMID:33989659 | DOI:10.1053/j.gastro.2021.04.078

Accéder au contenu

Current state of machine learning for non-melanoma skin cancer

Arch Dermatol Res. 2021 May 15. doi: 10.1007/s00403-021-02236-9. Online ahead of print.ABSTRACTBACKGROUND: Machine learning (ML) has been increasingly utilized for skin cancer screening, primarily of melanomas but also of non-melanoma skin cancers (NMSC).OBJECTIVE: This study presents the first quantitative review of the success of these techniques in …

Accéder au contenu

Differential diagnosis of benign and malignant vertebral fracture on CT using deep learning

Eur Radiol. 2021 May 16. doi: 10.1007/s00330-021-08014-5. Online ahead of print.ABSTRACTOBJECTIVES: To evaluate the performance of deep learning using ResNet50 in differentiation of benign and malignant vertebral fracture on CT.METHODS: A dataset of 433 patients confirmed with 296 malignant and 137 benign fractures was retrospectively selected from our spinal CT …

Accéder au contenu

Prognostic implications of body composition change during primary treatment in patients with ovarian cancer: A retrospective study using an artificial intelligence-based volumetric technique

Gynecol Oncol. 2021 May 13:S0090-8258(21)00363-2. doi: 10.1016/j.ygyno.2021.05.004. Online ahead of print.ABSTRACTOBJECTIVE: To investigate the impact of changes in body composition during primary treatment on survival outcomes in patients with epithelial ovarian cancer (EOC).METHODS: We retrospectively identified patients diagnosed with EOC between 2010 and 2019. Using an artificial intelligence-based …

Accéder au contenu

Augmenting lung cancer diagnosis on chest radiographs: positioning artificial intelligence to improve radiologist performance

Clin Radiol. 2021 May 11:S0009-9260(21)00237-3. doi: 10.1016/j.crad.2021.03.021. Online ahead of print.ABSTRACTAIM: To evaluate the role that artificial intelligence (AI) could play in assisting radiologists as the first reader of chest radiographs (CXRs), to increase the accuracy and efficiency of lung cancer diagnosis by flagging positive cases before …

Accéder au contenu

Diagnosis of Cervical Cancer based on Ensemble Deep Learning Network using Colposcopy Images

Biomed Res Int. 2021 May 4;2021:5584004. doi: 10.1155/2021/5584004. eCollection 2021.ABSTRACTTraditional screening of cervical cancer type classification majorly depends on the pathologist's experience, which also has less accuracy. Colposcopy is a critical component of cervical cancer prevention. In conjunction with precancer screening and treatment, colposcopy has played an essential role in lowering the …

Accéder au contenu

Entreprises

Le prochain midi #santé @IID_ULaval/@IVADO_Qc intitulé « Patients partenaires et données - accessibilité, confidentialité et usages de nos données » aura lieu ce jeudi, 20 mai 2021, à midi. Réservez vos places sur : ow.ly/LrjI50EFA3l.

Le prochain midi #santé @IID_ULaval/@IVADO_Qc intitulé « Patients partenaires et données - accessibilité, confidentialité et usages de nos données » aura lieu ce jeudi, 20 mai 2021, à midi. Réservez vos places sur : ow.ly/LrjI50EFA3l.

Accéder au contenu

Thank you to @JDRF for your support of our work to help better the lives of individuals with diabetes. We are proud to be in this fight alongside the work you do daily for our community. jdrf.org/press-releases… #bigfootbiomed #jdrf

Thank you to @JDRF for your support of our work to help better the lives of individuals with diabetes. We are proud to be in this fight alongside the work you do daily for our community. jdrf.org/press-releases… #bigfootbiomed #jdrf

Accéder au contenu

The inaugural issue of the International Journal of Digital Health came out last week, featuring insights from Babylon doctors. Read our blog for their thoughts and learnings through our journey in implementing a Digital First model of care in the #NHS babylonhealth.com/blog/health/a-…

The inaugural issue of the International Journal of Digital Health came out last week, featuring insights from Babylon doctors. Read our blog for their thoughts and learnings through our journey in implementing a Digital First model of care in the #NHSbabylonhealth.com/blog/health/a-…

Accéder au contenu

Last week our #Founder & #CEO, Ali Parsa, spoke at @CNBC's #HealthyReturns Summit about the role #tech will play in moving the focus of #healthcare to preventative, proactive care. Thank you @cnbcevents for having us & @JenSaidIt for your brilliant moderating.

Last week our #Founder & #CEO, Ali Parsa, spoke at @CNBC's #HealthyReturns Summit about the role #tech will play in moving the focus of #healthcare to preventative, proactive care. Thank you @cnbcevents for having us & @JenSaidIt for your brilliant moderating.

Accéder au contenu

COVID-19 patients with a first-phase ejection fraction of less than 25% had a nearly five-fold higher risk of death than those with an ejection fraction of 25% or higher. auntminnie.com/index.aspx?sec…

COVID-19 patients with a first-phase ejection fraction of less than 25% had a nearly five-fold higher risk of death than those with an ejection fraction of 25% or higher. auntminnie.com/index.aspx?sec…

Accéder au contenu

Here's our latest presentation for Osteoporosis Month! Did you know that automated opportunistic screening has great potential to create a paradigm shift in osteoporosis management? Learn more about it in this presentation! youtu.be/pCojB6nlVu4

Here's our latest presentation for Osteoporosis Month! Did you know that automated opportunistic screening has great potential to create a paradigm shift in osteoporosis management? Learn more about it in this presentation!youtu.be/pCojB6nlVu4

Accéder au contenu

In the U.S., 89% of survey respondents said they intend to prioritize #AI and telehealth in the future. However, in the next three years, only 40% said they expect to invest heavily in #telehealth, and AI looks set to emerge as a key area for investment. auntminnie.com/index.aspx?sec…

In the U.S., 89% of survey respondents said they intend to prioritize #AI and telehealth in the future. However, in the next three years, only 40% said they expect to invest heavily in #telehealth, and AI looks set to emerge as a key area for investment. auntminnie.com/index.aspx?sec…

Accéder au contenu

A man who was paralysed from the neck down in an accident more than a decade ago has written sentences using a computer system that turns imagined handwriting into words! rb.gy/getwc9

A man who was paralysed from the neck down in an accident more than a decade ago has written sentences using a computer system that turns imagined handwriting into words!rb.gy/getwc9

Accéder au contenu

It’s not a miracle machine, and it isn’t a silver bullet. Here’s how it got started! @Cognixion_AI #NeuroTech #BrainTech #Technology #EEG #BMI #BCI #communicating #electroencephalogram #research #cortex #Cognixion #BrainComputerInterface #brainwave #Brain rb.gy/uzqfdt

It’s not a miracle machine, and it isn’t a silver bullet. Here’s how it got started!@Cognixion_AI #NeuroTech #BrainTech #Technology #EEG #BMI #BCI #communicating #electroencephalogram #research #cortex #Cognixion #BrainComputerInterface #brainwave #Brainrb.gy/uzqfdt

Accéder au contenu

La démocratisation mondiale de la communauté des neurosciences est un des bons côtés de la pandémie, dit la chercheuse mondiale CIFAR-Azrieli @meganakpeters, une fondatrice @neuromatch Academy. 🧠 Vidéo #ConférenceVirtuelleduCIFAR : youtu.be/6DdoZL-eYis

La démocratisation mondiale de la communauté des neurosciences est un des bons côtés de la pandémie, dit la chercheuse mondiale CIFAR-Azrieli @meganakpeters, une fondatrice @neuromatch Academy. 🧠Vidéo #ConférenceVirtuelleduCIFAR : youtu.be/6DdoZL-eYis

Accéder au contenu

Microsoft and NVIDIA introduce parameter-efficient multimodal transformers for video representation learning

Understanding video is one of the most challenging problems in AI, and an important underlying requirement is learning multimodal representations that capture information about objects, actions, sounds, and their long-range statistical dependencies from audio-visual signals. Recently, transformers have been successful in vision-and-language tasks such as image captioning and visual question …

Accéder au contenu

A Conversation with Jenny Ahlstrom of Myeloma Crowd about Multiple Myeloma, MRD and the Changing Treatment Landscape

May 12, 2021 A Conversation with Jenny Ahlstrom of Myeloma Crowd about Multiple Myeloma, MRD and the Changing Treatment Landscape SHARE THIS ARTICLE: Share on email Share on twitter Share on linkedin Share on facebook Susan Bobulsky, SVP, Diagnostics, clonoSEQ & Jenny Ahlstrom, Founder, Myeloma Crowd In March 2021, the blood cancer community …

Accéder au contenu

Revue de presse

Un matelas intelligent qui veille à votre santé cardiovasculaire

Ce lit intelligent peut évaluer votre état de santé cardiaque sans électrodes sur votre peau. Un professionnel de la santé pourrait observer les données à distance. SIG-NUM Preemptive healthcare, Author providedImaginez un instant qu’un électrocardiogramme intégré à votre lit puisse évaluer votre état de santé cardiaque sans qu’un …

Accéder au contenu

Brain computer interface turns mental handwriting into text on screen

Researchers have, for the first time, decoded the neural signals associated with writing letters, then displayed typed versions of these letters in real time. They hope their invention could one day help people with paralysis communicate.

Accéder au contenu

The Doctor Is In: Three Predictions For The Future Of AI In Healthcare

Health · Innovation Rules · Jumio BrandVoice | Paid Program ... The Doctor Is In: Three Predictions For The Future Of AI In Healthcare ... medical facilities forged a new way of operating — and artificial intelligence (AI) was ... A recent Intel survey (via Healthcare IT News) of healthcare decision-makers ...

Accéder au contenu

Arizona passes law to dramatically expand telehealth access

"Disparities in healthcare are a huge issue in Arizona," Dr. Ronald ... director of the Arizona Telemedicine Program, told Healthcare IT News. ... of artificial intelligence and machine learning throughout the healthcare industry. ... "By 2050, well within the careers of today's medical students, AI-enhanced ...

Accéder au contenu

Patients less likely to take advice from AI doctors if they know their names

Artificial intelligence has long been seen as a means by which healthcare can ... When the fully-AI physician used the patients' first names and referred to ... more accustomed to online health platforms during the pandemic, and may ... Artificial intelligence has the ability to make physicians' lives easier, ...

Accéder au contenu

Data interoperability, knowledge interoperability and the learning health system

To get an in-depth look at interoperability and the healthcare knowledge ... Healthcare IT News interviewed Dr. Blackford Middleton, chief informatics ... healthcare organizations use artificial intelligence and machine learning to ... as those using machine learning to create AI/cognitive assistance tools.

Accéder au contenu

Pour obtenir les articles

L'accès au texte intégral pour les articles scientifiques est restreint selon les abonnements et les accès fournis par votre établissement.

Si vous êtes à l'intérieur du réseau CHUM :

  • Cliquez sur les liens fournis avec chaque référence pour vérifier éventuellement la disponibilité du texte intégral.
  • Sinon, vérifiez ensuite la disponibilité du journal dans notre liste de périodiques électroniques et naviguez par année/volume/numéro/pages pour localiser un article.
  • Quand un article n’est pas disponible, vous pouvez faire une demande de prêt entre bibliothèques ici : https://bibliothequeduchum.ca/sp/ajouts/forms/dem_documents.php . Des frais, peuvent s’appliquer pour certaines demandes. 

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 dans ce portail, veuillez vous référer à la bibliothèque de votre institution en donnant la référence 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.