Patient views on using artificial intelligence in medicine: trust is good, control is better (Preprint)
暂无分享,去创建一个
Simon Lennartz | Thomas Dratsch | David Zopfs | Thorsten Persigehl | David Maintz | Nils Große Hokamp | Daniel Pinto dos Santos
[1] T. Helbich,et al. Stand-Alone Artificial Intelligence for Breast Cancer Detection in Mammography: Comparison With 101 Radiologists. , 2019, Journal of the National Cancer Institute.
[2] C. Nelson,et al. Patient Perspectives on the Use of Artificial Intelligence for Skin Cancer Screening: A Qualitative Study. , 2020, JAMA dermatology.
[3] Tae-Yeong Kwak,et al. Artificial Intelligence in Pathology , 2018, Journal of pathology and translational medicine.
[4] Sebastian Thrun,et al. Dermatologist-level classification of skin cancer with deep neural networks , 2017, Nature.
[5] Xiaofeng Zhu,et al. Artificial Intelligence in Radiotherapy Treatment Planning: Present and Future , 2019, Technology in cancer research & treatment.
[6] Ahmed Hosny,et al. Artificial intelligence in radiology , 2018, Nature Reviews Cancer.
[7] Shuqing Gao,et al. Public Perception of Artificial Intelligence in Medical Care: Content Analysis of Social Media , 2020, Journal of medical Internet research.
[8] Saar Hommes,et al. A Qualitative Study to Understand Patient Perspective on the Use of Artificial Intelligence in Radiology. , 2019, Journal of the American College of Radiology : JACR.
[9] Ronald M Summers,et al. Automated Liver Fat Quantification at Nonenhanced Abdominal CT for Population-based Steatosis Assessment. , 2019, Radiology.
[10] Yu Jiang,et al. Attitudes Of Chinese Cancer Patients Toward The Clinical Use Of Artificial Intelligence , 2019, Patient preference and adherence.
[11] Fang Liu,et al. A review of recent publication trends from top publishing countries , 2018, Systematic Reviews.
[12] D. Stoyanov,et al. Attitudes of Patients and Their Relatives Towards Artificial Intelligence in Neurosurgery. , 2020, World neurosurgery.
[13] F. Sardanelli,et al. Artificial intelligence in medical imaging: threat or opportunity? Radiologists again at the forefront of innovation in medicine , 2018, European Radiology Experimental.
[14] D. Maintz,et al. Medical students' attitude towards artificial intelligence: a multicentre survey , 2018, European Radiology.
[15] Oleg S. Pianykh,et al. Current Applications and Future Impact of Machine Learning in Radiology. , 2018, Radiology.
[16] I. Glenn Cohen,et al. Informed Consent and Medical Artificial Intelligence: What to Tell the Patient? , 2020 .
[17] Derya Yakar,et al. Patients’ views on the implementation of artificial intelligence in radiology: development and validation of a standardized questionnaire , 2019, European Radiology.
[18] Nabile M. Safdar,et al. Ethics of Artificial Intelligence in Radiology: Summary of the Joint European and North American Multisociety Statement. , 2019, Journal of the American College of Radiology : JACR.
[19] Geoffrey E. Hinton. Deep Learning-A Technology With the Potential to Transform Health Care. , 2018, JAMA.
[20] Rosario Girasa. AI as a Disruptive Technology , 2020 .
[21] Anna Tarasova,et al. Scanning the Future of Medical Imaging. , 2019, Journal of the American College of Radiology : JACR.
[22] Ariane Chan,et al. A Review of the Role of Augmented Intelligence in Breast Imaging: From Automated Breast Density Assessment to Risk Stratification. , 2019, AJR. American journal of roentgenology.
[23] Jitendra Malik,et al. Expert-level detection of acute intracranial hemorrhage on head computed tomography using deep learning , 2019, Proceedings of the National Academy of Sciences.
[24] Kimmo Kartasalo,et al. Artificial intelligence for diagnosis and grading of prostate cancer in biopsies: a population-based, diagnostic study. , 2020, The Lancet. Oncology.
[25] Philippe Ravaud,et al. Patients’ views of wearable devices and AI in healthcare: findings from the ComPaRe e-cohort , 2019, npj Digital Medicine.
[26] T. Davenport,et al. The potential for artificial intelligence in healthcare , 2019, Future Healthcare Journal.