논문상세정보
' Artificial Intelligence in Pathology' 의 주제별 논문영향력
논문영향력 선정 방법
논문영향력 요약
주제
  • Artificial intelligence
  • Deep learning
  • Image analysis
  • pathology
동일주제 총논문수 논문피인용 총횟수 주제별 논문영향력의 평균
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' Artificial Intelligence in Pathology' 의 참고문헌

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    Antol S [2015]
  • Using deep convolutional neural networks to identify and classify tumor-associated stroma in diagnostic breast biopsies
  • Toward normative expert systems: Part I. The Pathfinder project
  • The Cancer Genome Atlas
  • Terabyte-scale deep multiple instance learning for classification and localization in pathology
  • Supervised deep learning embeddings for the prediction of cervical cancer diagnosis
    Fernandes K [2018]
  • Scalable and accurate deep learning with electronic health records
    Rajkomar A [2018]
  • RNA splicing : the human splicing code reveals new insights into the genetic determinants of disease
    Xiong HY [2015]
  • Quantification of histochemical staining by color deconvolution
  • Probability-based representations for efficient knowledge acquisition and inference
  • Predicting non-small cell lung cancer prognosis by fully automated microscopic pathology image features
    Yu KH [2016]
  • Predicting cancer outcomes from histology and genomics using convolutional networks
  • Operations research and health care:a handbook of methods and applications
    Schaefer AJ [2004]
  • Mycin: a knowledge-based computer program applied to infectious diseases
  • Mitosis detection in breast cancer histology images with deep neural networks
  • Minds, brains, and programs
    Searle JR [1980]
  • Microscopy cell counting and detection with fully convolutional regression networks
    Xie W [2016]
  • Mastering the game of Go without human knowledge
    Silver D [2017]
  • Markov decision processes : a tool for sequential decision making under uncertainty
    Alagoz O [2010]
  • Machines who think : a personal inquiry into the history and prospects of artificial intelligence
    McCorduck P [2004]
  • Machine learning methods for histopathological image analysis
    Komura D [2018]
  • Machine learning for medical diagnosis : history, state of the art and perspective
  • Long short-term memory
  • Loan default prediction using logistic regression and a loan pricing model
  • Large scale digital prostate pathology image analysis combining feature extraction and deep neural network
  • Intraoperative margin assessment of human breast tissue in optical coherence tomography images using deep neural networks
  • Interobserver variability in Gleason histological grading of prostate cancer
    Ozkan TA [2016]
  • Implications of observer variation in Gleason scoring of prostate cancer on clinical management : a collaborative audit
    Harbias A [2017]
  • Implementing machine learning in radiology practice and research
    Kohli M [2017]
  • ImmunoRatio : a publicly available web application for quantitative image analysis of estrogen receptor(ER), progesterone receptor(PR), and Ki-67
    Tuominen VJ [2010]
  • I. Computing machinery and intelligence
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  • Human-level control through deep reinforcement learning
    Mnih V [2015]
  • High-magnification multi-views based classification of breast fine needle aspiration cytology cell samples using fusion of decisions from deep convolutional networks
    Garud H [2017]
  • High-definition medicine
    Torkamani A [2017]
  • Handling limited datasets with neural networks in medical applications : a small-data approach
    Shaikhina T [2017]
  • Gradient-based learning applied to document recognition
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  • Google’s neural machine translation system: bridging the gap between human and machine translation
  • Going deeper with convolutions
    Szegedy, C. [2015]
  • End-to-end learning to predict survival in patients with gastric cancer using convolutional neural networks
    Meier A [2018]
  • Effective approaches to attention-based neural machine translation
    Luong MT [2015]
  • ELIZA : a computer program for the study of natural language communication between man and machine
  • Development and validation of a deep learning algorithm for improving Gleason scoring of prostate cancer
  • Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs
    Gulshan V [2016]
  • DeepPap : deep convolutional networks for cervical cell classification
    Zhang L [2017]
  • Deep speech: scaling up end-toend speech recognition
  • Deep learning in biomedicine
    Wainberg M [2018]
  • Deep learning for digital pathology image analysis : a comprehensive tutorial with selected use cases
    Janowczyk A [2016]
  • Deep learning for computational biology
  • Deep learning as a tool for increased accuracy and efficiency of histopathological diagnosis
    Litjens G [2016]
  • Deep learning
    LeCun Y [2015]
  • DCAN: deep contour-aware networks for accurate gland segmentation
    Chen H [2016]
  • Computeraided detection(CAD)in screening mammography : sensitivity of commercial CAD systems for detecting architectural distortion
    Baker JA [2003]
  • Computer vision and artificial intelligence in mammography
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  • Combining fully convolutional networks and graph-based approach for automated segmentation of cervical cell nuclei
    Zhang L [2017]
  • Classification and mutation prediction from non-small cell lung cancer histopathology images using deep learning
    Coudray N [2018]
  • Cell segmentation : 50 years down the road [life sciences]
  • Cancer metastasis detection with neural conditional random field
  • CAMELYON16. CAMELYON16 ISBI challenge on cancer metastasis detection in lymph node, 2015
  • Better Bayesian filtering
  • Automatic classification of ovarian cancer types from cytological images using deep convolutional neural networks
    Wu M [2018]
  • Automated grading of gliomas using deep learning in digital pathology images : a modular approach with ensemble of convolutional neural networks
    Ertosun MG [2015]
  • Automated classification of lung cancer types from cytological images using deep convolutional neural networks
    Teramoto A [2017]
  • Automated Gleason grading of prostate cancer tissue microarrays via deep learning
    Arvaniti E [2018]
  • Artificial intelligence for pathologists is not near : it is here : description of a prototype that can transform how we practice pathology tomorrow
    Ye JJ [2015]
  • Artificial intelligence : a modern approach
    Russell SJ [2003]
  • Artificial intelligence
  • Advances in neural information processing systems 29
    Kim JH [2016]
  • Advances in Neural Information Processing Systems 25
  • A universal SNP and smallindel variant caller using deep neural networks
    Poplin R [2018]
  • A threshold selection method from gray-level histograms
    Otsu N [1979]
  • A survey on deep learning in medical image analysis
    Litjens G [2017]
  • A deep convolutional neural network for classification of red blood cells in sickle cell anemia
    Xu M [2017]
  • A computer-based Markov decision analysis of the management of symptomatic bifascicular block : the threshold probability for pacing
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