Last Update Date: Jan 11, 2020
- Artificial Intelligence Makes Bad Medicine Even Worse
WIRED, January 10, 2020 - Evaluating the Potential Role of Social Media in Preventive Health Care
RM Merchant, JAMA< January 10, 2020 - Artificial intelligence has come to medicine. Are patients being put at risk?
L Szabo, LA Times, January 2020 - Network physiology in insomnia patients: Assessment of relevant changes in network topology with interpretable machine learning models.
Jansen Christoph et al. Chaos (Woodbury, N.Y.) 2019 Dec 29(12) 123129 - Artificial Intelligence for Adult Spinal Deformity.
Joshi Rushikesh S et al. Neurospine 2019 Dec 16(4) 686-694 - A New Algorithm Optimized for Initial Dose Settings of Vancomycin Using Machine Learning.
Imai Shungo et al. Biological & pharmaceutical bulletin 2020 43(1) 188-193 - Big Data Analysis: The Leap into a New Science Methodology.
Cacciola Alberto et al. World neurosurgery 2020 13397-98 - International evaluation of an AI system for breast cancer screening.
McKinney Scott Mayer et al. Nature 2020 577(7788) 89-94 - FOLFOX treatment response prediction in metastatic or recurrent colorectal cancer patients via machine learning algorithms.
Lu Wei et al. Cancer medicine 2020 Jan - A practical model for the identification of congenital cataracts using machine learning.
Lin Duoru et al. EBioMedicine 2020 Jan 51102621 - Artificial Intelligence in Plastic Surgery: Applications and Challenges.
Liang Xuebing et al. Aesthetic plastic surgery 2020 Jan - Accurate prediction of responses to transarterial chemoembolization for patients with hepatocellular carcinoma by using artificial intelligence in contrast-enhanced ultrasound.
Liu Dan et al. European radiology 2020 Jan - The Detection of Opioid Misuse and Heroin Use From Paramedic Response Documentation: Machine Learning for Improved Surveillance.
Prieto José Tomás et al. Journal of medical Internet research 2020 Jan 22(1) e15645 - Automated volumetric assessment with artificial neural networks might enable a more accurate assessment of disease burden in patients with multiple sclerosis.
Brugnara Gianluca et al. European radiology 2020 Jan - Use of Machine Learning for Predicting Escitalopram Treatment Outcome From Electroencephalography Recordings in Adult Patients With Depression.
Zhdanov Andrey et al. JAMA network open 2020 Jan 3(1) e1918377 - Reversibility of impaired brain structures after transsphenoidal surgery in Cushing's disease: a longitudinal study based on an artificial intelligence-assisted tool.
Hou Bo et al. Journal of neurosurgery 2020 Jan 1-10 - Automated Differentiation of Benign Renal Oncocytoma and Chromophobe Renal Cell Carcinoma on Computed Tomography Using Deep Learning.
Baghdadi Amir et al. BJU international 2020 Jan - Using Machine Learning in Psychiatry: The Need to Establish a Framework That Nurtures Trustworthiness.
Chandler Chelsea et al. Schizophrenia bulletin 2020 Jan 46(1) 11-14 - Modeling motor task activation from resting-state fMRI using machine learning in individual subjects.
Niu Chen et al. Brain imaging and behavior 2020 Jan - Social Media- and Internet-Based Disease Surveillance for Public Health.
Aiello Allison E et al. Annual review of public health 2020 Jan
Disclaimer: Articles listed in Non-Genomics Precision Health Update are selected by the CDC Office of Public Health Genomics to provide current awareness of the scientific literature and news. Inclusion in the update does not necessarily represent the views of the Centers for Disease Control and Prevention nor does it imply endorsement of the article's methods or findings. CDC and DHHS assume no responsibility for the factual accuracy of the items presented. The selection, omission, or content of items does not imply any endorsement or other position taken by CDC or DHHS. Opinion, findings and conclusions expressed by the original authors of items included in the Clips, or persons quoted therein, are strictly their own and are in no way meant to represent the opinion or views of CDC or DHHS. References to publications, news sources, and non-CDC Websites are provided solely for informational purposes and do not imply endorsement by CDC or DHHS.
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