The impact of artificial intelligence in medicine on the future role of the physician
暂无分享,去创建一个
[1] Diana S. M. Buist,et al. Will Machine Learning Tip the Balance in Breast Cancer Screening? , 2017, JAMA oncology.
[2] Charlene Liew. The future of radiology augmented with Artificial Intelligence: A strategy for success. , 2018, European journal of radiology.
[3] Nils J. Nilsson,et al. Artificial Intelligence , 1974, IFIP Congress.
[4] Peter Szolovits,et al. The coming of age of artificial intelligence in medicine , 2009, Artif. Intell. Medicine.
[5] Alain Saad,et al. Validation of an Objective Keratoconus Detection System Implemented in a Scheimpflug Tomographer and Comparison With Other Methods , 2017, Cornea.
[6] Sejong Oh,et al. Development of machine learning models for diagnosis of glaucoma , 2017, PloS one.
[7] Mary K. Pratt. Artificial intelligence in primary care , 2018 .
[8] Nehmat Houssami,et al. Artificial intelligence for breast cancer screening: Opportunity or hype? , 2017, Breast.
[9] Jiangtao Cui,et al. Localization and diagnosis framework for pediatric cataracts based on slit-lamp images using deep features of a convolutional neural network , 2017, PloS one.
[10] Bernard F King,et al. Artificial Intelligence and Radiology: What Will the Future Hold? , 2018, Journal of the American College of Radiology : JACR.
[11] A. Yuille,et al. Deep Learning in Radiology: Now the Real Work Begins. , 2018, Journal of the American College of Radiology : JACR.
[12] Paul Nagy,et al. Big Data and Machine Learning-Strategies for Driving This Bus: A Summary of the 2016 Intersociety Summer Conference. , 2017, Journal of the American College of Radiology : JACR.
[13] J. Bisley,et al. Evaluating tactile feedback in robotic surgery for potential clinical application using an animal model , 2016, Surgical Endoscopy.
[14] Abhimanyu S. Ahuja,et al. Understanding the advent of artificial intelligence in ophthalmology , 2019, Journal of current ophthalmology.
[15] Fangyuan Zhao,et al. Feasibility of Reidentifying Individuals in Large National Physical Activity Data Sets From Which Protected Health Information Has Been Removed With Use of Machine Learning , 2018, JAMA network open.
[16] J. Kai,et al. Can machine-learning improve cardiovascular risk prediction using routine clinical data? , 2017, PloS one.
[17] C. Krittanawong,et al. The rise of artificial intelligence and the uncertain future for physicians. , 2017, European journal of internal medicine.
[18] P. Lakhani,et al. Deep Learning at Chest Radiography: Automated Classification of Pulmonary Tuberculosis by Using Convolutional Neural Networks. , 2017, Radiology.
[19] R Nick Bryan,et al. Artificial Intelligence: Threat or Boon to Radiologists? , 2017, Journal of the American College of Radiology : JACR.
[20] Bianca S. Gerendas,et al. Fully Automated Detection and Quantification of Macular Fluid in OCT Using Deep Learning. , 2017, Ophthalmology.
[21] Amir Sadeghipour,et al. Artificial intelligence in retina , 2018, Progress in Retinal and Eye Research.
[22] Ronald M. Summers,et al. Deep Learning in Medical Imaging: Overview and Future Promise of an Exciting New Technique , 2016 .
[23] E H Shortliffe,et al. Watson for Oncology and breast cancer treatment recommendations: agreement with an expert multidisciplinary tumor board , 2018, Annals of oncology : official journal of the European Society for Medical Oncology.
[24] Nico Karssemeijer,et al. Large scale deep learning for computer aided detection of mammographic lesions , 2017, Medical Image Anal..
[25] Daniel L. Rubin,et al. Deep Learning for Brain MRI Segmentation: State of the Art and Future Directions , 2017, Journal of Digital Imaging.
[26] Daniel Rueckert,et al. Machine Learning of Three-dimensional Right Ventricular Motion Enables Outcome Prediction in Pulmonary Hypertension: A Cardiac MR Imaging Study , 2017, Radiology.