Last Update Date: Aug 30, 2019
- Use of Machine Learning to Identify Follow-Up Recommendations in Radiology Reports.
Carrodeguas Emmanuel et al. Journal of the American College of Radiology : JACR 2019 Mar 16(3) 336-343 - [Endoscopic Diagnosis Using Artificial Intelligence].
Hirasawa Toshiaki et al. Gan to kagaku ryoho. Cancer & chemotherapy 2019 Mar 46(3) 412-417 - Predicting in-hospital mortality of patients with acute kidney injury in the ICU using random forest model.
Lin Ke et al. International journal of medical informatics 2019 12555-61 - Evaluation of an AI-Based Detection Software for Acute Findings in Abdominal Computed Tomography Scans: Toward an Automated Work List Prioritization of Routine CT Examinations.
Winkel David J et al. Investigative radiology 2019 54(1) 55-59 - [Artificial Intelligence in Smart Health: Investigation of Theory and Practice].
Lin Shu-Hung et al. Hu li za zhi The journal of nursing 2019 Apr 66(2) 7-13 - Artificial intelligence for melanoma diagnosis: how can we deliver on the promise?
Mar V J et al. Annals of oncology : official journal of the European Society for Medical Oncology 2018 29(8) 1625-1628 - Dual-mode artificially-intelligent diagnosis of breast tumours in shear-wave elastography and B-mode ultrasound using deep polynomial networks.
Zhang Qi et al. Medical engineering & physics 2019 641-6 - Surgical Aid Visualization System for Glioblastoma Tumor Identification based on Deep Learning and In-Vivo Hyperspectral Images of Human Patients.
Fabelo Himar et al. Proceedings of SPIE--the International Society for Optical Engineering 2019 Feb 10951 - Realities of conducting digital health research: Challenges to consider.
de Redon Emily et al. Digital health 52055207619869466 - m-Health 2.0: New perspectives on mobile health, machine learning and big data analytics.
Istepanian Robert S H et al. Methods (San Diego, Calif.) 2018 15134-40 - Explainable machine-learning predictions for the prevention of hypoxaemia during surgery.
Lundberg Scott M et al. Nature biomedical engineering 2018 2(10) 749-760 - Real-Time Use of Artificial Intelligence in Identification of Diminutive Polyps During Colonoscopy: A Prospective Study.
Mori Yuichi et al. Annals of internal medicine 2018 169(6) 357-366 - Informatics and Data Science for the Precision in Symptom Self-Management Center.
Bakken Suzanne et al. Studies in health technology and informatics 2019 Aug 2641827-1828 - Association of Multifaceted Mobile Technology–Enabled Primary Care Intervention With Cardiovascular Disease Risk Management in Rural Indonesia
A Patel et al, JAMA Cardiology, August 2019 - Using Telemedicine to Treat Opioid Use Disorder in Rural Areas
R Rubin, JAMA< August 28, 2019 - Artificial intelligence for medicine needs a Turing test. Obesity would be a good one
M Joyner, StatNews, August 28, 2019 - Detection of Suicide Attempters among Suicide Ideators Using Machine Learning.
Ryu Seunghyong et al. Psychiatry investigation 2019 Aug 16(8) 588-593 - Using gait analysis' parameters to classify Parkinsonism: A data mining approach.
Ricciardi Carlo et al. Computer methods and programs in biomedicine 2019 Aug 180105033 - In Pursuit of Evidence in Air Pollution Epidemiology: The Role of Causally Driven Data Science.
Carone Marco et al. Epidemiology (Cambridge, Mass.) 2019 Aug - Can Machine Learning help us in dealing with treatment resistant depression? A review.
Pigoni Alessandro et al. Journal of affective disorders 2019 Aug 25921-26
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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