Related references
Note: Only part of the references are listed.The ethical, legal and social implications of using artificial intelligence systems in breast cancer care
Stacy M. Carter et al.
BREAST (2020)
Lessons Learned About Autonomous AI: Finding a Safe, Efficacious, and Ethical Path Through the Development Process
Michael D. Abramoff et al.
AMERICAN JOURNAL OF OPHTHALMOLOGY (2020)
Action-Informed Artificial Intelligence-Matching the Algorithm to the Problem
Christopher J. Lindsell et al.
JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION (2020)
Artificial intelligence versus clinicians: systematic review of design, reporting standards, and claims of deep learning studies
Myura Nagendran et al.
BMJ-BRITISH MEDICAL JOURNAL (2020)
Health Economic and Safety Considerations for Artificial Intelligence Applications in Diabetic Retinopathy Screening
Yuchen Xie et al.
TRANSLATIONAL VISION SCIENCE & TECHNOLOGY (2020)
Human-computer collaboration for skin cancer recognition
Philipp Tschandl et al.
NATURE MEDICINE (2020)
Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension
Xiaoxuan Liu et al.
NATURE MEDICINE (2020)
Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extension
Samantha Cruz Rivera et al.
NATURE MEDICINE (2020)
Adversarial attacks on medical machine learning
Samuel G. Finlayson et al.
SCIENCE (2019)
Machine Learning in Medicine
Alvin Rajkomar et al.
NEW ENGLAND JOURNAL OF MEDICINE (2019)
A systematic review shows no performance benefit of machine learning over logistic regression for clinical prediction models
Evangelia Christodoulou et al.
JOURNAL OF CLINICAL EPIDEMIOLOGY (2019)
Sample-Size Determination Methodologies for Machine Learning in Medical Imaging Research: A Systematic Review
Indranil Balki et al.
CANADIAN ASSOCIATION OF RADIOLOGISTS JOURNAL-JOURNAL DE L ASSOCIATION CANADIENNE DES RADIOLOGISTES (2019)
A Machine Learning Algorithm to Predict Severe Sepsis and Septic Shock: Development, Implementation, and Impact on Clinical Practice*
Heather M. Giannini et al.
CRITICAL CARE MEDICINE (2019)
Prognostic models will be victims of their own success, unless...
Matthew C. Lenert et al.
JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION (2019)
The Missing Pieces of Artificial Intelligence in Medicine
Coryandar Gilvary et al.
TRENDS IN PHARMACOLOGICAL SCIENCES (2019)
Developing a framework for evidence-based grading and assessment of predictive tools for clinical decision support
Mohamed Khalifa et al.
BMC MEDICAL INFORMATICS AND DECISION MAKING (2019)
Making Machine Learning Models Clinically Useful
Nigam H. Shah et al.
JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION (2019)
Potential Liability for Physicians Using Artificial Intelligence
W. Nicholson Price et al.
JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION (2019)
How to Read Articles That Use Machine Learning Users' Guides to the Medical Literature
Yun Liu et al.
JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION (2019)
Dissecting racial bias in an algorithm used to manage the health of populations
Ziad Obermeyer et al.
SCIENCE (2019)
Diagnosis of thyroid cancer using deep convolutional neural network models applied to sonographic images: a retrospective, multicohort, diagnostic study
Xiangchun Li et al.
LANCET ONCOLOGY (2019)
Lifecycle Regulation of Artificial Intelligence- and Machine Learning-Based Software Devices in Medicine
Thomas J. Hwang et al.
JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION (2019)
Addressing Bias in Artificial Intelligence in Health Care
Ravi B. Parikh et al.
JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION (2019)
A guide to deep learning in healthcare
Andre Esteva et al.
NATURE MEDICINE (2019)
The practical implementation of artificial intelligence technologies in medicine
Jianxing He et al.
NATURE MEDICINE (2019)
High-performance medicine: the convergence of human and artificial intelligence
Eric J. Topol
NATURE MEDICINE (2019)
Artificial intelligence, bias and clinical safety
Robert Challen et al.
BMJ QUALITY & SAFETY (2019)
A comparison of deep learning performance against health-care professionals in detecting diseases from medical imaging: a systematic review and meta-analysis
Xiaoxuan Liu et al.
LANCET DIGITAL HEALTH (2019)
Survival prediction in intensive-care units based on aggregation of long-term disease history and acute physiology: a retrospective study of the Danish National Patient Registry and electronic patient records
Annelaura B. Nielsen et al.
LANCET DIGITAL HEALTH (2019)
Scalable Joint Models for Reliable Uncertainty-Aware Event Prediction
Hossein Soleimani et al.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2018)
Application of contextual design methods to inform targeted clinical decision support interventions in sub-specialty care environments
Anne Miller et al.
INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS (2018)
What This Computer Needs Is a Physician Humanism and Artificial Intelligence
Abraham Verghese et al.
JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION (2018)
Does health informatics have a replication crisis?
Enrico Coiera et al.
JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION (2018)
Implementing Machine Learning in Health Care - Addressing Ethical Challenges
Danton S. Char et al.
NEW ENGLAND JOURNAL OF MEDICINE (2018)
Grader Variability and the Importance of Reference Standards for Evaluating Machine Learning Models for Diabetic Retinopathy
Jonathan Krause et al.
OPHTHALMOLOGY (2018)
Potential Biases in Machine Learning Algorithms Using Electronic Health Record Data
Milena A. Gianfrancesco et al.
JAMA INTERNAL MEDICINE (2018)
Impact of Deep Learning Assistance on the Histopathologic Review of Lymph Nodes for Metastatic Breast Cancer
David F. Steiner et al.
AMERICAN JOURNAL OF SURGICAL PATHOLOGY (2018)
Ensuring Fairness in Machine Learning to Advance Health Equity
Alvin Rajkomar et al.
ANNALS OF INTERNAL MEDICINE (2018)
Clinical Decision Support in the Era of Artificial Intelligence
Edward H. Shortliffe et al.
JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION (2018)
Variable generalization performance of a deep learning model to detect pneumonia in chest radiographs: A cross-sectional study
John R. Zech et al.
PLOS MEDICINE (2018)
Opening the black box of neural networks: methods for interpreting neural network models in clinical applications
Zhongheng Zhang et al.
ANNALS OF TRANSLATIONAL MEDICINE (2018)
Automation bias and verification complexity: a systematic review
David Lyell et al.
JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION (2017)
Opportunities and challenges in developing risk prediction models with electronic health records data: a systematic review
Benjamin A. Goldstein et al.
JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION (2017)
A Quantitative, Risk-Based Approach to the Management of Neonatal Early-Onset Sepsis
Michael W. Kuzniewicz et al.
JAMA PEDIATRICS (2017)
Artificial intelligence for breast cancer screening: Opportunity or hype?
Nehmat Houssami et al.
BREAST (2017)
Common data elements for secondary use of electronic health record data for clinical trial execution and serious adverse event reporting
Philipp Bruland et al.
BMC MEDICAL RESEARCH METHODOLOGY (2016)
Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs
Varun Gulshan et al.
JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION (2016)
Causal inference and the data-fusion problem
Elias Bareinboim et al.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2016)
Creating a Common Data Model for Comparative Effectiveness with the Observational Medical Outcomes Partnership
F. FitzHenry et al.
APPLIED CLINICAL INFORMATICS (2015)
Race/Ethnic Differences in the Associations of the Framingham Risk Factors with Carotid IMT and Cardiovascular Events
Crystel M. Gijsberts et al.
PLOS ONE (2015)
Intelligible Models for HealthCare: Predicting Pneumonia Risk and Hospital 30-day Readmission
Rich Caruana et al.
KDD'15: PROCEEDINGS OF THE 21ST ACM SIGKDD INTERNATIONAL CONFERENCE ON KNOWLEDGE DISCOVERY AND DATA MINING (2015)
Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies: The CHARMS Checklist
Karel G. M. Moons et al.
PLOS MEDICINE (2014)
Use of Hundreds of Electrocardiographic Biomarkers for Prediction of Mortality in Postmenopausal Women The Women's Health Initiative
Eiran Z. Gorodeski et al.
CIRCULATION-CARDIOVASCULAR QUALITY AND OUTCOMES (2011)
Share Paper
