相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。Deep learning to detect significant coronary artery disease from plain chest radiographs AI4CAD
Giuseppe D'Ancona et al.
INTERNATIONAL JOURNAL OF CARDIOLOGY (2023)
Obtaining genetics insights from deep learning via explainable artificial intelligence
Gherman Novakovsky et al.
NATURE REVIEWS GENETICS (2023)
Deep learning enables genetic analysis of the human thoracic aorta
James P. Pirruccello et al.
NATURE GENETICS (2022)
A guide to machine learning for biologists
Joe G. Greener et al.
NATURE REVIEWS MOLECULAR CELL BIOLOGY (2022)
Use of Multi-Modal Data and Machine Learning to Improve Cardiovascular Disease Care
Saeed Amal et al.
FRONTIERS IN CARDIOVASCULAR MEDICINE (2022)
devCellPy is a machine learning-enabled pipeline for automated annotation of complex multilayered single-cell transcriptomic data
Francisco X. Galdos et al.
NATURE COMMUNICATIONS (2022)
Development of non-bias phenotypic drug screening for cardiomyocyte hypertrophy by image segmentation using deep learning
Jin Komuro et al.
BIOCHEMICAL AND BIOPHYSICAL RESEARCH COMMUNICATIONS (2022)
Anti-senescent drug screening by deep learning-based morphology senescence scoring
Dai Kusumoto et al.
NATURE COMMUNICATIONS (2021)
Effective gene expression prediction from sequence by integrating long-range interactions
Ziga Avsec et al.
NATURE METHODS (2021)
Using Deep Learning to Emulate the Use of an External Contrast Agent in Cardiovascular 4D Flow MRI
Mariana Bustamante et al.
JOURNAL OF MAGNETIC RESONANCE IMAGING (2021)
Real-time volumetric reconstruction of biological dynamics with light-field microscopy and deep learning
Zhaoqiang Wang et al.
NATURE METHODS (2021)
Artificial intelligence to deep learning: machine intelligence approach for drug discovery
Rohan Gupta et al.
MOLECULAR DIVERSITY (2021)
Artificial intelligence-enabled electrocardiograms for identification of patients with low ejection fraction: a pragmatic, randomized clinical trial
Xiaoxi Yao et al.
NATURE MEDICINE (2021)
Deep learning for detecting congenital heart disease in the fetus
Shaine A. Morris et al.
NATURE MEDICINE (2021)
Bad News, You're Older Than Suspected Can Deep Learning Estimate Biological Age From Chest Radiographs?
Manish Motwani
JACC-CARDIOVASCULAR IMAGING (2021)
Three-dimensional residual channel attention networks denoise and sharpen fluorescence microscopy image volumes
Jiji Chen et al.
NATURE METHODS (2021)
Deep learning-based transformation of H&E stained tissues into special stains
Kevin de Haan et al.
NATURE COMMUNICATIONS (2021)
Development and validation of a reinforcement learning algorithm to dynamically optimize mechanical ventilation in critical care
Arne Peine et al.
NPJ DIGITAL MEDICINE (2021)
Deep Learning for Quantitative Cardiac MRI
Qian Tao et al.
AMERICAN JOURNAL OF ROENTGENOLOGY (2020)
Comparing the performance of artificial intelligence and conventional diagnosis criteria for detecting left ventricular hypertrophy using electrocardiography
Joon-Myoung Kwon et al.
EUROPACE (2020)
Detection of Hypertrophic Cardiomyopathy Using a Convolutional Neural Network-Enabled Electrocardiogram
Wei-Yin Ko et al.
JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY (2020)
Automatic Triage of 12-Lead ECGs Using Deep Convolutional Neural Networks
Rutger R. van de Leur et al.
JOURNAL OF THE AMERICAN HEART ASSOCIATION (2020)
Deep learning models for electrocardiograms are susceptible to adversarial attack
Xintian Han et al.
NATURE MEDICINE (2020)
Prediction of mortality from 12-lead electrocardiogram voltage data using a deep neural network
Sushravya Raghunath et al.
NATURE MEDICINE (2020)
A promising approach for screening pulmonary hypertension based on frontal chest radiographs using deep learning: A retrospective study
Xiao-Ling Zou et al.
PLOS ONE (2020)
Direct evidence of secondary reconnection inside filamentary currents of magnetic flux ropes during magnetic reconnection
Salah Al-Zaiti et al.
NATURE COMMUNICATIONS (2020)
A population-based phenome-wide association study of cardiac and aortic structure and function
Wenjia Bai et al.
NATURE MEDICINE (2020)
Machine learning and statistical methods for clustering single-cell RNA-sequencing data
Raphael Petegrosso et al.
BRIEFINGS IN BIOINFORMATICS (2020)
Development and Validation of a Deep-Learning Model to Screen for Hyperkalemia From the Electrocardiogram
Conner D. Galloway et al.
JAMA CARDIOLOGY (2019)
An artificial intelligence-enabled ECG algorithm for the identification of patients with atrial fibrillation during sinus rhythm: a retrospective analysis of outcome prediction
Zachi Attia et al.
LANCET (2019)
Screening for cardiac contractile dysfunction using an artificial intelligence-enabled electrocardiogram
Zachi I. Attia et al.
NATURE MEDICINE (2019)
Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network
Awni Y. Hannun et al.
NATURE MEDICINE (2019)
Challenges in unsupervised clustering of single-cell RNA-seq data
Vladimir Yu Kiselev et al.
NATURE REVIEWS GENETICS (2019)
Deep Learning for Cardiac MRI: The Time Has Come
Patrick M. Colletti
RADIOLOGY (2019)
The application of convolutional neural network to stem cell biology
Dai Kusumoto et al.
INFLAMMATION AND REGENERATION (2019)
Deep Learning to Assess Long-term Mortality From Chest Radiographs
Michael T. Lu et al.
JAMA NETWORK OPEN (2019)
A machine learning model to predict the risk of 30-day readmissions in patients with heart failure: a retrospective analysis of electronic medical records data
Sara Bersche Golas et al.
BMC MEDICAL INFORMATICS AND DECISION MAKING (2018)
Deep Learning Techniques for Automatic MRI Cardiac Multi-Structures Segmentation and Diagnosis: Is the Problem Solved?
Olivier Bernard et al.
IEEE TRANSACTIONS ON MEDICAL IMAGING (2018)
Artificial Intelligence in Cardiology
Kipp W. Johnson et al.
JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY (2018)
Artificial Intelligence-Based Assessment of Left Ventricular Filling Pressures From 2-Dimensional Cardiac Ultrasound Images
Alaa Mabrouk Salem Omar et al.
JACC-CARDIOVASCULAR IMAGING (2018)
Automated Deep Learning-Based System to Identify Endothelial Cells Derived from Induced Pluripotent Stem Cells
Dai Kusumoto et al.
STEM CELL REPORTS (2018)
Using recurrent neural network models for early detection of heart failure onset
Edward Choi et al.
JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION (2017)
Mastering the game of Go without human knowledge
David Silver et al.
NATURE (2017)
Dermatologist-level classification of skin cancer with deep neural networks
Andre Esteva et al.
NATURE (2017)
Cardiovascular Event Prediction by Machine Learning The Multi-Ethnic Study of Atherosclerosis
Bharath Ambale-Venkatesh et al.
CIRCULATION RESEARCH (2017)
Machine-Learning Algorithms to Automate Morphological and Functional Assessments in 2D Echocardiography
Sukrit Narula et al.
JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY (2016)
Mastering the game of Go with deep neural networks and tree search
David Silver et al.
NATURE (2016)
Evaluation of a Prediction Model for the Development of Atrial Fibrillation in a Repository of Electronic Medical Records
Matthew J. Kolek et al.
JAMA CARDIOLOGY (2016)
Machine Learning in Medicine
Rahul C. Deo
CIRCULATION (2015)
Right ventricle segmentation from cardiac MRI: A collation study
Caroline Petitjean et al.
MEDICAL IMAGE ANALYSIS (2015)
Predicting the sequence specificities of DNA- and RNA-binding proteins by deep learning
Babak Alipanahi et al.
NATURE BIOTECHNOLOGY (2015)
Machine learning applications in genetics and genomics
Maxwell W. Libbrecht et al.
NATURE REVIEWS GENETICS (2015)
Deep learning in neural networks: An overview
Juergen Schmidhuber
NEURAL NETWORKS (2015)
Identification of type 2 diabetes subgroups through topological analysis of patient similarity
Li Li et al.
SCIENCE TRANSLATIONAL MEDICINE (2015)
Unsupervised pattern discovery in human chromatin structure through genomic segmentation
Michael M. Hoffman et al.
NATURE METHODS (2012)
Illuminating eukaryotic transcription start sites
John A. Stamatoyannopoulos
NATURE METHODS (2010)
mRNA-Seq whole-transcriptome analysis of a single cell
Fuchou Tang et al.
NATURE METHODS (2009)
Predicting gene expression from sequence
MA Beer et al.
CELL (2004)
Artificial intelligence in medicine
AN Ramesh et al.
ANNALS OF THE ROYAL COLLEGE OF SURGEONS OF ENGLAND (2004)