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Proceedings of Machine Learning Research

Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research
Proceedings of Machine Learning Research
PMLR · 2026-05-29 · via Proceedings of Machine Learning Research

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Volume 182: Machine Learning for Healthcare Conference, 5-6 August 2022, 301 W Morgan St, Durham, NC 27701

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Editors: Zachary Lipton, Rajesh Ranganath, Mark Sendak, Michael Sjoding, Serena Yeung

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Contrastive Learning of Medical Visual Representations from Paired Images and Text

; Proceedings of the 7th Machine Learning for Healthcare Conference, PMLR 182:2-25

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Unified Auto Clinical Scoring (Uni-ACS) with Interpretable ML models

Anthony Li, Ming Lun Ong, Chien Wei Oei, Weixiang Lian, Hwee Pin Phua, Lin Htun Htet, Wei Yen Lim, Mehul Motani; Proceedings of the 7th Machine Learning for Healthcare Conference, PMLR 182:26-53

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Deep Cascade Learning for Optimal Medical Image Feature Representation

Junwen Wang, Xin Du, Katayoun Farrahi, Mahesan Niranjan; Proceedings of the 7th Machine Learning for Healthcare Conference, PMLR 182:54-78

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Survival Seq2Seq: A Survival Model based on Sequence to Sequence Architecture

Ebrahim Pourjafari, Navid Ziaei, Mohammad R. Rezaei, Amir Sameizadeh, Mohammad Shafiee, Mohammad Alavinia, Mansour Abolghasemian, Nick Sajadi; Proceedings of the 7th Machine Learning for Healthcare Conference, PMLR 182:79-100

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Density-Aware Personalized Training for Risk Prediction in Imbalanced Medical Data

Zepeng Huo, Xiaoning Qian, Shuai Huang, Zhangyang Wang, Bobak J. Mortazavi; Proceedings of the 7th Machine Learning for Healthcare Conference, PMLR 182:101-122

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Ensembling Neural Networks for Improved Prediction and Privacy in Early Diagnosis of Sepsis

Shigehiko Schamoni, Michael Hagmann, Stefan Riezler; Proceedings of the 7th Machine Learning for Healthcare Conference, PMLR 182:123-145

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Learning Optimal Dynamic Treatment Regimes Using Causal Tree Methods in Medicine

Theresa Blumlein, Joel Persson, Stefan Feuerriegel; Proceedings of the 7th Machine Learning for Healthcare Conference, PMLR 182:146-171

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GeoECG: Data Augmentation via Wasserstein Geodesic Perturbation for Robust Electrocardiogram Prediction

Jiacheng Zhu, Jielin Qiu, Zhuolin Yang, Douglas Weber, Michael A. Rosenberg, Emerson Liu, Bo Li, Ding Zhao; Proceedings of the 7th Machine Learning for Healthcare Conference, PMLR 182:172-197

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HiCu: Leveraging Hierarchy for Curriculum Learning in Automated ICD Coding

Weiming Ren, Ruijing Zeng, Tongzi Wu, Tianshu Zhu, Rahul G. Krishnan; Proceedings of the 7th Machine Learning for Healthcare Conference, PMLR 182:198-223

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Survival Mixture Density Networks

Xintian Han, Mark Goldstein, Rajesh Ranganath; Proceedings of the 7th Machine Learning for Healthcare Conference, PMLR 182:224-248

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Latent Temporal Flows for Multivariate Analysis of Wearables Data

Magda Amiridi, Gregory Darnell, Sean Jewell; Proceedings of the 7th Machine Learning for Healthcare Conference, PMLR 182:249-269

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An hybrid CNN-Transformer model based on multi-feature extraction and attention fusion mechanism for cerebral emboli classification

Yamil Vindas, Blaise Kevin Guepie, Marilys Almar, Emmanuel Roux, Philippe Delachartre; Proceedings of the 7th Machine Learning for Healthcare Conference, PMLR 182:270-296

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EMIXER: End-to-end Multimodal X-ray Generation via Self-supervision

Siddharth Biswal, Peiye Zhuang, Ayis Pyrros, Nasir Siddiqui, Sanmi Koyejo, Jimeng Sun; Proceedings of the 7th Machine Learning for Healthcare Conference, PMLR 182:297-324

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Diagnosing Epileptogenesis with Deep Anomaly Detection

Amr Farahat, Diyuan Lu, Sebastian Bauer, Valentin Neubert, Lara Sophie Costard, Felix Rosenow, Jochen Triesch; Proceedings of the 7th Machine Learning for Healthcare Conference, PMLR 182:325-342

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Disparate Censorship & Undertesting: A Source of Label Bias in Clinical Machine Learning

Trenton Chang, Michael W. Sjoding, Jenna Wiens; Proceedings of the 7th Machine Learning for Healthcare Conference, PMLR 182:343-390

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EHR Safari: Data is Contextual

William Boag, Mercy Oladipo, Peter Szolovits; Proceedings of the 7th Machine Learning for Healthcare Conference, PMLR 182:391-408

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A Multi Instance Learning Approach for Critical View of Safety Detection in Laparoscopic Cholecystectomy

Yariv Colbeci, Maya Zohar, Daniel Neimark, Dotan Asselmann, Omri Bar; Proceedings of the 7th Machine Learning for Healthcare Conference, PMLR 182:409-424

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Anomaly Detection in Echocardiograms with Dynamic Variational Trajectory Models

Alain Ryser, Laura Manduchi, Fabian Laumer, Holger Michel, Sven Wellmann, Julia E. Vogt; Proceedings of the 7th Machine Learning for Healthcare Conference, PMLR 182:425-458

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How fair is your graph? Exploring fairness concerns in neuroimaging studies

Fernanda Ribeiro, Valentina Shumovskaia, Thomas Davies, Ira Ktena; Proceedings of the 7th Machine Learning for Healthcare Conference, PMLR 182:459-478

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MedFuse: Multi-modal fusion with clinical time-series data and chest X-ray images

Nasir Hayat, Krzysztof J. Geras, Farah E. Shamout; Proceedings of the 7th Machine Learning for Healthcare Conference, PMLR 182:479-503

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Debiasing Deep Chest X-Ray Classifiers using Intra- and Post-processing Methods

Ricards Marcinkevics, Ece Ozkan, Julia E. Vogt; Proceedings of the 7th Machine Learning for Healthcare Conference, PMLR 182:504-536

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ICE-NODE: Integration of Clinical Embeddings with Neural Ordinary Differential Equations

Asem Alaa, Erik Mayer, Mauricio Barahona; Proceedings of the 7th Machine Learning for Healthcare Conference, PMLR 182:537-564

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Weakly Supervised Deep Instance Nuclei Detection using Points Annotation in 3D Cardiovascular Immunofluorescent Images

Nazanin Moradinasab, Yash Sharma, Laura S. Shankman, Gary K. Owens, Donald E. Brown; Proceedings of the 7th Machine Learning for Healthcare Conference, PMLR 182:565-584

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auton-survival: an Open-Source Package for Regression, Counterfactual Estimation, Evaluation and Phenotyping with Censored Time-to-Event Data

Chirag Nagpal, Willa Potosnak, Artur Dubrawski; Proceedings of the 7th Machine Learning for Healthcare Conference, PMLR 182:585-608

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AudiFace: Multimodal Deep Learning for Depression Screening

Ricardo Flores, ML Tlachac, Ermal Toto, Elke Rundensteiner; Proceedings of the 7th Machine Learning for Healthcare Conference, PMLR 182:609-630

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Reinforcement Learning For Sepsis Treatment: A Continuous Action Space Solution

Yong Huang, Rui Cao, Amir Rahmani; Proceedings of the 7th Machine Learning for Healthcare Conference, PMLR 182:631-647

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Learning Optimal Summaries of Clinical Time-series with Concept Bottleneck Models

Carissa Wu, Sonali Parbhoo, Marton Havasi, Finale Doshi-Velez; Proceedings of the 7th Machine Learning for Healthcare Conference, PMLR 182:648-672

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Classifying Unstructured Clinical Notes via Automatic Weak Supervision

Chufan Gao, Mononito Goswami, Jieshi Chen, Artur Dubrawski; Proceedings of the 7th Machine Learning for Healthcare Conference, PMLR 182:673-690

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KCRL: A Prior Knowledge Based Causal Discovery Framework with Reinforcement Learning

Uzma Hasan, Md Osman Gani; Proceedings of the 7th Machine Learning for Healthcare Conference, PMLR 182:691-714

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Error Amplification When Updating Deployed Machine Learning Models

George Alexandru Adam, Chun-Hao Kingsley Chang, Benjamin Haibe-Kains, Anna Goldenberg; Proceedings of the 7th Machine Learning for Healthcare Conference, PMLR 182:715-740

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Development and Validation of ML-DQA – a Machine Learning Data Quality Assurance Framework for Healthcare

Mark Sendak, Gaurav Sirdeshmukh, Timothy Ochoa, Hayley Premo, Linda Tang, Kira Niederhoffer, Sarah Reed, Kaivalya Deshpande, Emily Sterrett, Melissa Bauer, Laurie Snyder, Afreen Shariff, David Whellan, Jeffrey Riggio, David Gaieski, Kristin Corey, Megan Richards, Michael Gao, Marshall Nichols, Bradley Heintze, William Knechtle, William Ratliff, Suresh Balu; Proceedings of the 7th Machine Learning for Healthcare Conference, PMLR 182:741-759

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Reducing Reliance on Spurious Features in Medical Image Classification with Spatial Specificity

Khaled Saab, Sarah Hooper, Mayee Chen, Michael Zhang, Daniel Rubin, Christopher Re; Proceedings of the 7th Machine Learning for Healthcare Conference, PMLR 182:760-784

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Searching for Fine-Grained Queries in Radiology Reports Using Similarity-Preserving Contrastive Embedding

Tanveer Syeda-Mahmood, Luyao Shi; Proceedings of the 7th Machine Learning for Healthcare Conference, PMLR 182:785-799

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SurvLatent ODE : A Neural ODE based time-to-event model with competing risks for longitudinal data improves cancer-associated Venous Thromboembolism (VTE) prediction

Intae Moon, Stefan Groha, Alexander Gusev; Proceedings of the 7th Machine Learning for Healthcare Conference, PMLR 182:800-827

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Why predicting risk can’t identify ‘risk factors’: empirical assessment of model stability in machine learning across observational health databases

Aniek F. Markus, Peter R. Rijnbeek, Jenna M. Reps; Proceedings of the 7th Machine Learning for Healthcare Conference, PMLR 182:828-852

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Few-Shot Learning with Semi-Supervised Transformers for Electronic Health Records

Raphael Poulain, Mehak Gupta, Rahmatollah Beheshti; Proceedings of the 7th Machine Learning for Healthcare Conference, PMLR 182:853-873

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Evaluating Uncertainty-Based Deep Learning Explanations for Prostate Lesion Detection

Christopher M Trombley, Mehmet Akif Gulum, Merve Ozen, Enes Esen, Melih Aksamoglu, Mehmed Kantardzic; Proceedings of the 7th Machine Learning for Healthcare Conference, PMLR 182:874-891

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ALGES: Active Learning with Gradient Embeddings for Semantic Segmentation of Laparoscopic Surgical Images

Josiah Aklilu, Serena Yeung; Proceedings of the 7th Machine Learning for Healthcare Conference, PMLR 182:892-911

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此内容由惯性聚合(RSS阅读器)自动聚合整理，仅供阅读参考。 原文来自 — 版权归原作者所有。