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Network Configurations in the Human Brain Reflect Choice Bias during Rapid Face Processing. https://www.ncbi.nlm.nih.gov/pubmed/29118108 J Neurosci. 2017 Dec 13;37(50):12226-12237. doi: 10.1523/JNEUROSCI.1677-17.2017. Epub 2017 Nov 8. Network Configurations in the Human Brain Reflect Choice Bias during Rapid Face Processing. Tu T1, Schneck N1,2, Muraskin J1, Sajda P3,4,5. Author information Abstract Network interactions are likely to be instrumental in processes underlying rapid percep.. 더보기
Invariant recognition drives neural representations of action sequences https://www.ncbi.nlm.nih.gov/pubmed/29253864 PLoS Comput Biol. 2017 Dec 18;13(12):e1005859. doi: 10.1371/journal.pcbi.1005859. eCollection 2017 Dec. Invariant recognition drives neural representations of action sequences. Tacchetti A1, Isik L1, Poggio T1. Author information 1 Center for Brains Minds and Machines, Massachusetts Institute of Technology, Cambridge, MA, United States. Abstract Recog.. 더보기
Machine learning in cardiovascular medicine: are we there yet? https://www.ncbi.nlm.nih.gov/pubmed/29352006 Heart. 2018 Jan 19. pii: heartjnl-2017-311198. doi: 10.1136/heartjnl-2017-311198. [Epub ahead of print] Machine learning in cardiovascular medicine: are we there yet? Shameer K1,2,3,4,5,6, Johnson KW2,3,4,5, Glicksberg BS2,3,4,5,7, Dudley JT2,3,4,5, Sengupta PP8. Author information Abstract Artificial intelligence (AI) broadly refers to analytical alg.. 더보기
Encouraging Physical Activity in Patients With Diabetes: Intervention Using a Reinforcement Learning System. https://www.ncbi.nlm.nih.gov/pubmed/29017988 J Med Internet Res. 2017 Oct 10;19(10):e338. doi: 10.2196/jmir.7994.Encouraging Physical Activity in Patients With Diabetes: Intervention Using a Reinforcement Learning System.Yom-Tov E1, Feraru G2, Kozdoba M3, Mannor S3, Tennenholtz M4, Hochberg I5.Author information1Microsoft Research, Herzeliya, Israel.2Technion - Israel Institute of Technology, Fa.. 더보기
A Removal of Eye Movement and Blink Artifacts from EEG Data Using Morphological Component Analysis. https://www.ncbi.nlm.nih.gov/pubmed/28194221 Comput Math Methods Med. 2017;2017:1861645. doi: 10.1155/2017/1861645. Epub 2017 Jan 17.A Removal of Eye Movement and Blink Artifacts from EEG Data Using Morphological Component Analysis.Singh B1, Wagatsuma H2.Author information1Graduate School of Life Science and Systems Engineering, Kyushu Institute of Technology (KYUTECH), Kitakyushu, Japan.2Gradua.. 더보기
Conflicting results between the analysis of skin lesions using a mobile-phone application and a dermatologist's clinical diagnosis: a pilot study. https://www.ncbi.nlm.nih.gov/pubmed/28295172 Br J Dermatol. 2017 Mar 10. doi: 10.1111/bjd.15443. [Epub ahead of print]Poor agreement between a mobile phone application for the analysis of skin lesions and the clinical diagnosis of the dermatologist, a pilot study.Nabil R1, Bergman W1, Kukutsch NA1.Author information:1Department of Dermatology, Leiden University Medical Center, Albinusdreef 2, 23.. 더보기
Models of logistic regression analysis, support vector machine, and back-propagation neural network based on serum tumor markers in colorectal cancer diagnosis https://www.ncbi.nlm.nih.gov/pubmed/27323037 Genet Mol Res. 2016 May 13;15(2). doi: 10.4238/gmr.15028643.Models of logistic regression analysis, support vector machine, and back-propagation neural network based on serum tumor markers in colorectal cancer diagnosis.Zhang B1, Liang XL2, Gao HY2, Ye LS2, Wang YG1.Author information1Training Department, Third Military Medical University of Chinese P.. 더보기
Exploring Deep Learning and Transfer Learning for Colonic Polyp Classification. https://www.ncbi.nlm.nih.gov/pubmed/27847543 Comput Math Methods Med. 2016;2016:6584725. Epub 2016 Oct 26.Exploring Deep Learning and Transfer Learning for Colonic Polyp Classification.Ribeiro E1, Uhl A2, Wimmer G2, Häfner M3.Author information1Department of Computer Sciences, University of Salzburg, Salzburg, Austria; Department of Computer Sciences, Federal University of Tocantins, Palmas, TO,.. 더보기
Mass detection in digital breast tomosynthesis: Deep convolutional neural network with transfer learning from mammography. https://www.ncbi.nlm.nih.gov/pubmed/27908154 Med Phys. 2016 Dec;43(12):6654.Mass detection in digital breast tomosynthesis: Deep convolutional neural network with transfer learning from mammography.Samala RK1, Chan HP1, Hadjiiski L1, Helvie MA1, Wei J1, Cha K1.Author information1Department of Radiology, University of Michigan, Ann Arbor, Michigan 48109.AbstractPURPOSE:Develop a computer-aided de.. 더보기
Pulmonary Nodule Classification with Deep Convolutional Neural Networks on Computed Tomography Images. https://www.ncbi.nlm.nih.gov/pubmed/28070212 Comput Math Methods Med. 2016;2016:6215085. doi: 10.1155/2016/6215085. Epub 2016 Dec 14.Pulmonary Nodule Classification with Deep Convolutional Neural Networks on Computed Tomography Images.Li W1, Cao P1, Zhao D1, Wang J2.Author information1Medical Image Computing Laboratory of Ministry of Education, Northeastern University, Shenyang 110819, China; Co.. 더보기

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