Machine-learned analysis of the association of next-generation sequencing based genotypes with persistent pain after breast cancer surgery. Kringel Dario et al. Pain 2019 May

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Last Posted: May 23, 2019

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• Cardiovascular disease risk prediction using automated machine learning: A prospective study of 423,604 UK Biobank participants.
  Alaa Ahmed M et al. PloS one 2019 14(5) e0213653
• Machine-learned analysis of the association of next-generation sequencing based genotypes with persistent pain after breast cancer surgery.
  Kringel Dario et al. Pain 2019 May
• Predicting breast cancer metastasis by using serum biomarkers and clinicopathological data with machine learning technologies.
  Tseng Yi-Ju et al. International journal of medical informatics 2019 May
• -Omics biomarker identification pipeline for translational medicine.
  Bravo-Merodio Laura et al. Journal of translational medicine 2019 May 17(1) 155
• An Introduction to Machine Learning for Clinicians.
  Rowe Michael et al. Academic medicine : journal of the Association of American Medical Colleges 2019 May
• Artificial intelligence (AI) and cancer prevention: the potential application of AI in cancer control programming needs to be explored in population laboratories such as COMPASS.
  Leatherdale Scott T et al. Cancer causes & control : CCC 2019 May
• Artificial Intelligence in Cardiovascular Medicine.
  Seetharam Karthik et al. Current treatment options in cardiovascular medicine 2019 May 21(6) 25
• Automated Detection of Macular Diseases by Optical Coherence Tomography and Artificial Intelligence Machine Learning of Optical Coherence Tomography Images.
  Kuwayama Soichiro et al. Journal of ophthalmology 2019 20196319581
• Challenges in IBD Research: Precision Medicine.
  Denson Lee A et al. Inflammatory bowel diseases 2019 May 25(Supplement_2) S31-S39
• Detecting middle ear fluid using smartphones.
  Chan Justin et al. Science translational medicine 2019 May 11(492)

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