Deep Patient: An Unsupervised Representation to Predict the Future of Patients from the Electronic Health Records
Cited by (1,005)
Items 301–400 of 1,005
- Feature learning for fault detection in high-dimensional condition monitoring signalsGabriel Michau, Yang Hu, Thomas Palmé, Olga Fink · 2019 · Proceedings of the Institution of Mechanical Engineers Part O Journal of Risk and Reliability
- Regularization Learning Networks: Deep Learning for Tabular DatasetsIra Shavitt, Eran Segal · 2018 · arXiv (Cornell University)
- Learning Tasks for Multitask Learning: Heterogenous Patient Populations in the ICUSuresh, Harini, Gong, Jen J., Guttag, John V. · 2018 · Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining
- Deep learning in systems medicineHaiying Wang, Estelle Pujos‐Guillot, Blandine Comte, João Luís de Miranda, Vojtěch Spiwok, Ivan Chorbev, Filippo Castiglione, Paolo Tieri, Steven Watterson, Roisin McAllister et al. · 2020 · Briefings in Bioinformatics
- MUFASA: Multimodal Fusion Architecture Search for Electronic Health RecordsXu, Zhen, So, David R., Dai, Andrew M. · 2021 · Proceedings of the AAAI Conference on Artificial Intelligence
- MNN: Multimodal Attentional Neural Networks for Diagnosis PredictionZhi Qiao, Xian Wu, Shen Ge, Wei Fan · 2019 · International Joint Conference on Artificial Intelligence
- How data science and AI-based technologies impact genomicsLin Jing, Kee Yuan Ngiam · 2023 · Singapore Medical Journal
- Predicting age by mining electronic medical records with deep learning characterizes differences between chronological and physiological ageZichen Wang, Li Li, Benjamin Scott Glicksberg, Ariel Israel, Joel T. Dudley, Avi Ma’ayan · 2017 · Journal of Biomedical Informatics
- Deep learning for health informatics: Recent trends and future directionsSiddharth Srivastava, Sumit Soman, Astha Rai, Praveen Kumar Srivastava · 2017 · International Conference on Advances in Computing, Communications and Informatics (ICACCI)
- Personal and social patterns predict influenza vaccination decisionAdir Shaham, Gabriel Chodick, Varda Shalev, Dan Yamin · 2020 · BMC Public Health
- Artificial intelligence in cardiovascular medicineSagar Ranka, Madhu Reddy, Amit Noheria · 2020 · Current Opinion in Cardiology
- Prediction of unplanned 30-day readmission for ICU patients with heart failureMaryam Pishgar, Julian Theis, M Del Rios, Amer Kasim Ardati, Hadis Anahideh, Houshang Darabi · 2022 · BMC Medical Informatics and Decision Making
- Semantic Information Retrieval on Medical TextsLynda Tamine, Lorraine Goeuriot · 2021 · ACM Computing Surveys
- Machine Learning in Relation to Emergency Medicine Clinical and Operational Scenarios: An OverviewSangil Lee, Nicholas M. Mohr, Wall Street, Prakash M. Nadkarni · 2019 · Western Journal of Emergency Medicine
- Deep Learning for Electronic Health Records AnalyticsGaspard Harerimana, Jong Wook Kim, Hoon Yoo, Beakcheol Jang · 2019 · IEEE Access
- DeePaN: deep patient graph convolutional network integrating clinico-genomic evidence to stratify lung cancers for immunotherapyChao Fang, Dong He Xu, Jing Su, Jonathan R. Dry, Bolan Linghu · 2021 · npj Digital Medicine
- Feature engineering with clinical expert knowledge: A case study assessment of machine learning model complexity and performanceKenneth D. Roe, Vibhu Jawa, Xiaohan Zhang, Christopher G. Chute, Jeremy Aaron Epstein, Jordan Matelsky, Ilya Shpitser, Casey Overby Taylor · 2020 · PLoS ONE
- Selecting relevant features from the electronic health record for clinical code predictionElyne Scheurwegs, Boris Čule, Kim Luyckx, Léon Luyten, Walter M. P. Daelemans · 2017 · Journal of Biomedical Informatics
- Deep Learning Techniques for Electronic Health Record AnalysisLuciano Caroprese, Pierangelo Veltri, Eugenio Vocaturo, Ester Zumpano · 2018 · International Conference on Information, Intelligence, Systems & Applications (IISA)
- Machine Learning and Artificial Intelligence in Pediatric Research: Current State, Future Prospects, and Examples in Perioperative and Critical CareHannah Lonsdale, Ali Jalali, Luis M Ahumada, Clyde T. Matava · 2020 · The Journal of Pediatrics
- Analysis of Deep Learning Methods for Healthcare Sector - Medical Imaging Disease DetectionHemlata Sahu, Ramgopal Kashyap, Surbhi Bhatia, Bhupesh Kumar Dewangan, Nora A. Alkhaldi, Samson Anosh Babu Parisapogu, Senthilkumar Mohan · 2023 · Contemporary Mathematics
- Applying Deep Learning to Individual and Community Health Monitoring Data: A SurveyZhenjie Yao, Jie Bi, Yixin Chen · 2018 · Machine Intelligence Research
- Development and Validation of a Deep Learning Radiomics Model Predicting Lymph Node Status in Operable Cervical CancerTaotao Dong, Chun Yang, Baoxia Cui, Ting Zhang, Xiubin Sun, Kun Song, Linlin Wang, Beihua Kong, Xingsheng Yang · 2020 · Frontiers in Oncology
- Multivariate Time Series Missing Data Imputation Using Recurrent Denoising AutoencoderZhang, Jianye, Yin, Peng · 2019 · 2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
- Variationally regularized graph-based representation learning for electronic health recordsWeicheng Zhu, Narges Razavian · 2021 · ACM Conference on Health, Inference, and Learning (CHIL)
- A Non-invasive Approach to Identify Insulin Resistance with Triglycerides and HDL-c Ratio Using Machine learningMadam Chakradar, Alok Aggarwal, Xiaochun Cheng, Anuj Rani, Manoj Kumar, Achyut Shankar · 2021 · Neural Processing Letters
- A risk score including body mass index, glycated haemoglobin and triglycerides predicts future glycaemic control in people with type 2 diabetesDorijn F. L. Hertroijs, Arianne Elissen, Martijn C.G.J. Brouwers, Nicolaas C. Schaper, Sebastian Köhler, Mirela Carmia Popa, Stylianos Asteriadis, Steven H. Hendriks, Henk J. G. Bilo, Dirk Ruwaard · 2017 · Diabetes Obesity and Metabolism
- Osteoporotic hip fracture prediction from risk factors available in administrative claims data – A machine learning approachAlexander Engels, Katrin Christiane Reber, Ivonne Lindlbauer, Kilian Rapp, Gisela Büchele, Jochen Klenk, Andreas Daniel Meid, Clemens Becker, Hans‐Helmut König · 2020 · PLoS ONE
- Patient representation learning and interpretable evaluation using clinical notesMadhumita Sushil, Simon Šuster, Kim Luyckx, Walter M. P. Daelemans · 2018 · Journal of Biomedical Informatics
- A Novel Deep Neural Network Model for Multi-Label Chronic Disease PredictionXiaoqing Zhang, Hongling Zhao, Shuo Zhang, Runzhi Li · 2019 · Frontiers in Genetics
- Automated detection of altered mental status in emergency department clinical notes: a deep learning approachJihad S. Obeid, Erin R. Weeda, Andrew J. Matuskowitz, Kevin J. Gagnon, Tami L. Crawford, Christine M. Carr, Lewis J. Frey · 2019 · BMC Medical Informatics and Decision Making
- Monitoring ICU Mortality Risk with A Long Short-Term Memory Recurrent Neural NetworkKe Yu, Mingda Zhang, Tianyi Cui, Miloš Hauskrecht · 2019 · Pacific Symposium on Biocomputing (PSB)
- A Multi-Task Neural Network Architecture for Renal Dysfunction Prediction in Heart Failure Patients With Electronic Health RecordsBinhua Wang, Kunlun He, Yongyi Bai, Zhenjie Yao, Jiangong Li, Wei Dong, Yanhui Tu, Wanguo Xue, Yaping Tian, Yifei Wang · 2019 · IEEE Access
- eHealth in transplantationWiebke Duettmann, Marcel Ganesh Naik, Bianca Zukunft, Bilgin Osmonodja, Friederike Bachmann, Mira Choi, Roland Roller, Manuel Mayrdorfer, Fabian Halleck, Danilo Schmidt et al. · 2020 · Transplant International
- Challenges and opportunities of artificial intelligence in African health spaceMuslim Alaran, Salim Kamaludeen Lawal, Mustapha Husseini Jiya, Salihu Alhassan Egya, Mohamed Mustaf Ahmed, Abdullateef Abdulsalam, Usman Abubakar Haruna, Muhammad Kabir Musa, Don Eliseo Lucero‐Prisno · 2025 · Digital Health
- EMR-based medical knowledge representation and inference via Markov random fields and distributed representation learningZhao, Chao, Jiang, Jingchi, Guan, Yi, Guo, Xitong, He, Bin · 2018 · Artificial Intelligence in Medicine
- Fine-grained Patient Similarity Measuring using Deep Metric LearningJiazhi Ni, Jie Liu, Chenxin Zhang, Dan Ye, Zhirou Ma · 2017 · ACM International Conference on Information and Knowledge Management (CIKM)
- Deep learning for named entity recognition on Chinese electronic medical records: Combining deep transfer learning with multitask bi-directional LSTM RNNXishuang Dong, Shanta Chowdhury, Lijun Qian, Xiangfang Li, Yi Guan, Jinfeng Yang, Qiubin Yu · 2019 · PLoS ONE
- Representation learning for clinical time series prediction tasks in electronic health recordsTong Ruan, Liqi Lei, Yangming Zhou, Jie Zhai, Le Zhang, Ping He, Ju Gao · 2019 · BMC Medical Informatics and Decision Making
- Early temporal prediction of Type 2 Diabetes Risk Condition from a General Practitioner Electronic Health Record: A Multiple Instance Boosting ApproachMichele Bernardini, Micaela Morettini, Luca Romeo, Emanuele Frontoni, Laura Burattini · 2020 · Artificial Intelligence in Medicine
- Using machine learning for predicting cervical cancer from Swedish electronic health records by mining hierarchical representationsRebecka Weegar, Karin Sundström · 2020 · PLoS ONE
- Phe2vec: Automated disease phenotyping based on unsupervised embeddings from electronic health recordsJessica K. De Freitas, Kipp W. Johnson, Eddye Golden, Girish N. Nadkarni, Joel T. Dudley, Erwin P. Böttinger, Benjamin Scott Glicksberg, Riccardo Miotto · 2021 · Patterns
- Evaluating Machine Learning ArticlesFinale Doshi‐Velez, Roy H. Perlis · 2019 · JAMA
- Precision medicine and artificial intelligence: overview and relevance to reproductive medicineIman Hajirasouliha, Olivier Elemento · 2020 · Fertility and Sterility
- Optimal Predictive analytics of Pima Diabetics using Deep LearningH. Balaji, N. Ch. S. N. Iyengar, Ronnie D. Caytiles · 2017 · International Journal of Database Theory and Application
- Feature Ranking in Predictive Models for Hospital-Acquired Acute Kidney InjuryLijuan Wu, Yong Qiang Hu, Xiaoxiao Liu, Xiangzhou Zhang, Weiqi Chen, Alan S.L. Yu, John A. Kellum, Lemuel Russell Waitman, Mei Liu · 2018 · Scientific Reports
- WearableDL: Wearable Internet-of-Things and Deep Learning for Big Data Analytics—Concept, Literature, and FutureAras R. Dargazany, Paolo Stegagno, Kunal Mankodiya · 2018 · Mobile Information Systems
- Clinical prediction rules: a systematic review of healthcare provider opinions and preferencesKennedy, Georgina, Gallego, Blanca · 2019 · International Journal of Medical Informatics
- Improving triaging from primary care into secondary care using heterogeneous data-driven hybrid machine learningBing Wang, Weizi Li, Anthony Bradlow, Eghosa Bazuaye, Antoni T.Y. Chan · 2022 · Decision Support Systems
- A flexible symbolic regression method for constructing interpretable clinical prediction modelsWilliam La Cava, Paul C. Lee, Imran Ajmal, Xiruo Ding, Priyanka Solanki, Jordana B. Cohen, Jason H. Moore, Daniel S. Herman · 2023 · npj Digital Medicine
- Deep Learning Solutions for Classifying Patients on Opioid Use.Zhengping Che, Jennifer L. St. Sauver, Hongfang Liu, Yan Liu · 2017 · PubMed Central
- Review of Machine Learning in Predicting Dermatological OutcomesAmy Du, Sepideh Emam, Robert Gniadecki · 2020 · Frontiers in Medicine
- An explainable artificial intelligence approach for predicting cardiovascular outcomes using electronic health recordsSergiusz Wesołowski, Gordon Lemmon, Edgar Javier Hernandez, Alex Henrie, Thomas A. Miller, Derek L. Weyhrauch, Michael D. Puchalski, Bruce E. Bray, Rashmee U. Shah, Vikrant G. Deshmukh et al. · 2022 · PLOS Digital Health
- Rethinking Confidence Calibration for Failure PredictionFei Zhu, Zhen Cheng, Xu-Yao Zhang, Cheng‐Lin Liu · 2022 · Lecture notes in computer science
- RNA trafficking and subcellular localization—a review of mechanisms, experimental and predictive methodologiesJun Wang, Marc Horlacher, Lixin Cheng, Ole Winther · 2023 · Briefings in Bioinformatics
- Deep learning opens new horizons in personalized medicine (Review)Georgios Z. Papadakis, Apostolos H. Karantanas, Manolis Tsiknakis, Aristidis Michael Tsatsakis, Demetrios A. Spandidos, Kostas Marias A · 2019 · Biomedical Reports
- Interpretation of machine learning predictions for patient outcomes in electronic health recordsWilliam La Cava, Christopher R. Bauer, Jason H. Moore, Sarah A. Pendergrass · 2020 · PubMed Central
- P eax : Interactive Visual Pattern Search in Sequential Data Using Unsupervised Deep Representation LearningFritz Lekschas, Brant K. Peterson, Daniel Haehn, Eric J. Ma, Nils Gehlenborg, Hanspeter Pfister · 2020 · Computer Graphics Forum
- KAICD: A knowledge attention-based deep learning framework for automatic ICD codingYifan Wu, Min Zeng, Zhihui Fei, Ying Yu, Fang‐Xiang Wu, Min Li · 2020 · Neurocomputing
- OptiLIME: Optimized LIME Explanations for Diagnostic Computer AlgorithmsG. Visani, Enrico Bagli, F. Chesani · 2020 · International Conference on Information and Knowledge Management
- A scoping review of ethics considerations in clinical natural language processingOliver J. Bear Don’t Walk, Harry Reyes Nieva, Sandra Soo‐Jin Lee, Noémie Elhadad · 2022 · JAMIA Open
- Unveiling the Complexity of Medical Imaging through Deep Learning ApproachesNovsheena Rasool, Javaid Iqbal Bhat · 2023 · Chaos Theory and Applications
- Predicting 30-day all-cause readmissions from hospital inpatient discharge dataChengliang Yang, Chris Delcher, Elizabeth A. Shenkman, Sanjay Ranka · 2016 · IEEE International Conference on e-Health Networking, Applications and Services (Healthcom)
- ECG-derived spatial QRS-T angle is associated with ICD implantation, mortality and heart failure admissions in patients with LV systolic dysfunctionSarah Gleeson, Yi-Wen Liao, Clementina Dugo, Andrew Cave, Lifeng Zhou, Zina Ayar, J. Christiansen, Tony Scott, Liane Dawson, A. Gavin et al. · 2017 · PLoS ONE
- Machine Learning Techniques for Screening and Diagnosis of Diabetes: a SurveyYunlei Sun, Dalin Zhang · 2019 · Tehnicki vjesnik - Technical Gazette
- Disease Concept-Embedding Based on the Self-Supervised Method for Medical Information Extraction from Electronic Health Records and Disease Retrieval: Algorithm Development and Validation StudyYen-Pin Chen, Yuan–Hsun Lo, Feipei Lai, Chien‐Hua Huang · 2021 · Journal of Medical Internet Research
- Machine learning in requirements elicitation: a literature reviewCheligeer Cheligeer, Jingwei Huang, Guosong Wu, Nadia Bhuiyan, Yuan Xu, Yong Zeng · 2022 · Artificial intelligence for engineering design analysis and manufacturing
- Collaborative Cohort of Cohorts for COVID-19 Research (C4R) Study: Study DesignElizabeth C. Oelsner, Akshaya Krishnaswamy, Pallavi Balte, Norrina B. Allen, Tauqeer Ali, Pramod Anugu, Howard Andrews, Komal Arora, Alyssa Asaro, R. Graham Barr et al. · 2022 · American Journal of Epidemiology
- Bibliometric analysis on the adoption of artificial intelligence applications in the e-health sectorAbdul Khalique Shaikh, Saadat Mehmood Alhashmi, Nadia Khalique, Ahmed M. Khedr, Kaamran Raahemifar, Sadaf Bukhari · 2023 · Digital Health
- Combining unsupervised, supervised and rule-based learning: the case of detecting patient allergies in electronic health recordsGeir Thore Berge, Ole‐Christoffer Granmo, Tor Oddbjørn Tveit, Anna Linda Ruthjersen, Jivitesh Sharma · 2023 · BMC Medical Informatics and Decision Making
- A transfer learning approach via procrustes analysis and mean shift for cancer drug sensitivity predictionTurki Turki, Zhi Wei, Jason T. L. Wang · 2018 · Journal of Bioinformatics and Computational Biology
- Predicting type 2 diabetes via machine learning integration of multiple omics from human pancreatic isletsTina Rönn, Alexander Perfilyev, Nikolay Oskolkov, Charlotte Ling · 2024 · Scientific Reports
- Proteome-based systems biology in chronic painDavid Gómez‐Varela, Allison M Barry, Manuela Schmidt · 2018 · Journal of Proteomics
- A multi-omics supervised autoencoder for pan-cancer clinical outcome endpoints predictionKaiwen Tan, Weixian Huang, Jinlong Hu, Shoubin Dong · 2020 · BMC Medical Informatics and Decision Making
- Latent representation learning in biology and translational medicineAndreas Kopf, Manfred Claassen · 2021 · Patterns
- Prediction of Adverse Events in Patients Undergoing Major Cardiovascular ProceduresBobak J. Mortazavi, Nihar R. Desai, Jing Zhang, Andreas C. Coppi, Fred Warner, Harlan M. Krumholz, Sahand N. Negahban · 2017 · IEEE Journal of Biomedical and Health Informatics
- From big data to better patient outcomesTim Hulsen, David Friedecký, Harald E. Renz, Els Melis, Pieter Vermeersch, Pilar Fernández–Calle · 2022 · Clinical Chemistry and Laboratory Medicine (CCLM)
- Explainable AI in Healthcare ApplicationSiva Raja Sindiramutty, Wee Jing Tee, Sumathi Balakrishnan, Sukhminder Kaur, Rajan Thangaveloo, Husin Jazri, Navid Ali Khan, Abdalla Hassan Gharib, Amaranadha Reddy Manchuri · 2024 · Advances in computational intelligence and robotics book series
- A novel deep learning algorithm for real-time prediction of clinical deterioration in the emergency department for a multimodal clinical decision support systemArom Choi, Kwanhyung Lee, Heejung Hyun, Kwang Joon Kim, Byung Eun Ahn, Kyung Hyun Lee, Sangchul Hahn, So Yeon Choi, Ji Hoon Kim · 2024 · Scientific Reports
- Deep Generative Classifiers for Thoracic Disease Diagnosis with Chest X-ray ImagesChengsheng Mao, Liang Yao, Yiheng Pan, Yuan Luo, Zexian Zeng · 2018 · IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
- Pharmacogenomic Biomarkers and Their Applications in PsychiatryKam, Heejin, Jeong, Hotcherl · 2020 · Genes
- Artificial intelligence in oncology: From bench to clinicJamal A. Elkhader, Olivier Elemento · 2021 · Seminars in Cancer Biology
- Regional Tree Regularization for Interpretability in Deep Neural NetworksWu, Mike, Parbhoo, Sonali, Hughes, Michael, Kindle, Ryan, Celi, Leo, Zazzi, Maurizio, Roth, Volker, Doshi-Velez, Finale · 2020 · Proceedings of the AAAI Conference on Artificial Intelligence
- Federated Learning in Smart Healthcare: A Survey of Applications, Challenges, and Future DirectionsMohammad Nasajpour, Seyedamin Pouriyeh, Reza M. Parizi, Meng Han, Fatemeh Mosaiyebzadeh, Liyuan Liu, Yixin Xie, Daniel Macêdo Batista · 2025 · Electronics
- Advancing Predictive Hepatotoxicity at the Intersection of Experimental, in Silico , and Artificial Intelligence TechnologiesKeith Fraser, Dylan M. Bruckner, Jonathan S. Dordick · 2018 · Chemical Research in Toxicology
- Disease classification: from phenotypic similarity to integrative genomics and beyondMikhail G. Dozmorov · 2018 · Briefings in Bioinformatics
- Predicting microbiomes through a deep latent spaceBeatriz García-Jiménez, Jorge Muñoz, Sara Cabello, Joaquı́n Medina, Mark D. Wilkinson · 2020 · Bioinformatics
- Structuring clinical text with AI: Old versus new natural language processing techniques evaluated on eight common cardiovascular diseasesXianghao Zhan, Marie Humbert‐Droz, Pritam Mukherjee, Olivier Gevaert · 2021 · Patterns
- A Survey of Autoencoder Algorithms to Pave the Diagnosis of Rare DiseasesDavid Pratella, Samira Ait-El-Mkadem, Sylvie Bannwarth, Véronique Paquis‐Flucklinger, Silvia Bottini · 2021 · International Journal of Molecular Sciences
- MixEHR-Guided: A guided multi-modal topic modeling approach for large-scale automatic phenotyping using the electronic health recordYuri Ahuja, Yuesong Zou, Aman D Verma, David Llewellyn Buckeridge, Yue Li · 2022 · Journal of Biomedical Informatics
- Textual analysis and visualization of research trends in data mining for electronic health recordsJingfeng Chen, Wei Wei, Chonghui Guo, Lin Tang, Leilei Sun · 2017 · Health Policy and Technology
- Harmonized representation learning on dynamic EHR graphsLee, Dongha, Jiang, Xiaoqian, Yu, Hwanjo · 2020 · Journal of Biomedical Informatics
- Privacy-Preserving Federated Learning Framework for Multi-Source Electronic Health Records Prognosis PredictionHang Zhao, Dehao Sui, Yasha Wang, Liantao Ma, Ling Wang · 2025 · Sensors
- A Clinically Applicable Approach to the Classification of B-Cell Non-Hodgkin Lymphomas with Flow Cytometry and Machine LearningValentina Gaidano, Valerio Tenace, Nathalie Santoro, Silvia Varvello, Alessandro Cignetti, Giuseppina Prato, Giuseppe Nicola Saglio, Gaetano De Rosa, Massimo Geuna · 2020 · Cancers
- Predicting postpartum psychiatric admission using a machine learning approachKim Steven Betts, Steve R Kisely, Rosa Alati · 2020 · Journal of Psychiatric Research
- Smart HealthcareHongxu Yin, Ayten Ozge Akmandor, Arsalan Mosenia, Niraj Kumar Jha · 2018 · Foundations and Trends® in Electronic Design Automation
- Multiview Incomplete Knowledge Graph Integration with application to cross-institutional EHR data harmonizationDoudou Zhou, Ziming Gan, Xu Shi, Alina Patwari, Everett Neil Rush, Clara-Lea Bonzel, Vidul Ayakulangara Panickan, Chuan Hong, Yuk-Lam Anne Ho, Tianrun A. Cai et al. · 2022 · Journal of Biomedical Informatics
- Failure to rescue: A quality indicator for postoperative careEric B. Rosero, Bryan T. Romito, Girish P. Joshi · 2020 · Best practice & research. Clinical anaesthesiology
- A glossary for big data in population and public health: discussion and commentary on terminology and research methodsDaniel Fuller, Richard Buote, Kevin Gordon Stanley · 2017 · Journal of Epidemiology & Community Health
- Interpretation of machine learning predictions for patient outcomes in electronic health recordsWilliam La Cava, Christopher R. Bauer, Jason H. Moore, Sarah A. Pendergrass · 2019 · PubMed