Related references
Note: Only part of the references are listed.Great expectations and challenges of artificial intelligence in the screening of diabetic retinopathy
Mingwei Zhao et al.
EYE (2020)
Artificial Intelligence Tool for Optimizing Eligibility Screening for Clinical Trials in a Large Community Cancer Center
J. Thaddeus Beck et al.
JCO CLINICAL CANCER INFORMATICS (2020)
Regulation of predictive analytics in medicine
Ravi B. Parikh et al.
SCIENCE (2019)
Promoting Trust Between Patients and Physicians in the Era of Artificial Intelligence
Shantanu Nundy 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)
Artificial Intelligence-Based Breast Cancer Nodal Metastasis Detection
Yun Liu et al.
ARCHIVES OF PATHOLOGY & LABORATORY MEDICINE (2019)
A guide to deep learning in healthcare
Andre Esteva et al.
NATURE MEDICINE (2019)
Artificial Intelligence in Healthcare: Past, Present and Future
Ahmet Ilker Tekkesin
ANATOLIAN JOURNAL OF CARDIOLOGY (2019)
Artificial intelligence in healthcare: a critical analysis of the legal and ethical implications
Daniel Schonberger
INTERNATIONAL JOURNAL OF LAW AND INFORMATION TECHNOLOGY (2019)
Overview of artificial intelligence in medicine
Amisha et al.
JOURNAL OF FAMILY MEDICINE AND PRIMARY CARE (2019)
Radiomics and Artificial Intelligence for Biomarker and Prediction Model Development in Oncology
Reza Forghani et al.
COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL (2019)
Design AI so that it's fair
James Zou et al.
NATURE (2018)
Improving IoT Technology Adoption through Improving Consumer Trust
Areej AlHogail
TECHNOLOGIES (2018)
Deep learning for healthcare: review, opportunities and challenges
Riccardo Miotto et al.
BRIEFINGS IN BIOINFORMATICS (2018)
Machine Learning for Healthcare: On the Verge of a Major Shift in Healthcare Epidemiology
Jenna Wiens et al.
CLINICAL INFECTIOUS DISEASES (2018)
The ICO and artificial intelligence: The role of fairness in the GDPR framework
Michael Butterworth
COMPUTER LAW & SECURITY REVIEW (2018)
Dermatologist-level classification of skin cancer with deep neural networks
Andre Esteva et al.
NATURE (2017)
Artificial intelligence in healthcare: past, present and future
Fei Jiang et al.
STROKE AND VASCULAR NEUROLOGY (2017)
Correction: World Health Organization Estimates of the Global and Regional Disease Burden of 22 Foodborne Bacterial, Protozoal, and Viral Diseases, 2010: A Data Synthesis
Martyn D. Kirk et al.
PLOS MEDICINE (2015)
Certifying and Removing Disparate Impact
Michael Feldman et al.
KDD'15: PROCEEDINGS OF THE 21ST ACM SIGKDD INTERNATIONAL CONFERENCE ON KNOWLEDGE DISCOVERY AND DATA MINING (2015)
Why the Fitts list has persisted throughout the history of function allocation
J. C. F. de Winter et al.
COGNITION TECHNOLOGY & WORK (2014)
SEIPS 2.0: a human factors framework for studying and improving the work of healthcare professionals and patients
Richard J. Holden et al.
ERGONOMICS (2013)
Trust in Automation
Robert R. Hoffman et al.
IEEE INTELLIGENT SYSTEMS (2013)
A Survey of Multi-Agent Trust Management Systems
Han Yu et al.
IEEE ACCESS (2013)
Dual-processing accounts of reasoning, judgment, and social cognition
Jonathan St. B. T. Evans
ANNUAL REVIEW OF PSYCHOLOGY (2008)
Trust in automation: Designing for appropriate reliance
JD Lee et al.
HUMAN FACTORS (2004)
Selection of patients for clinical trials: an interactive web-based system
E Fink et al.
ARTIFICIAL INTELLIGENCE IN MEDICINE (2004)
Share Paper
