ML Anthology

CHIL 2023

34 papers

A General Framework for Visualizing Embedding Spaces Of\titlebreak Neural Survival Analysis Models Based on Angular Information George H Chen
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Adaptive Weighted Multi-View Clustering Shuo Shuo Liu, Lin Lin
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Bayesian Active Questionnaire Design for Cause-of-Death Assignment Using Verbal Autopsies Toshiya Yoshida, Trinity Shuxian Fan, Tyler McCormick, Wu Zhenke, Zehang Richard Li
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Clinical Relevance Score for Guided Trauma Injury Pattern Discovery with Weakly Supervised $β$-VAE Qixuan Jin, Jacobien HF Oosterhoff, Yepeng Huang, Marzyeh Ghassemi, Gabriel A Brat
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Collecting Data When Missingness Is Unknown: A Method for Improving Model Performance Given Under-Reporting in Patient Populations Kevin Wu, Dominik Dahlem, Christopher Hane, Eran Halperin, James Zou
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Conference on Health, Inference, and Learning (CHIL) 2023 Bobak J. Mortazavi, Tasmie Sarker, Andrew Beam, Joyce C. Ho
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Contrastive Learning of Electrodermal Activity Representations for Stress Detection Katie Matton, Robert Lewis, John Guttag, Rosalind Picard
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Denoising Autoencoders for Learning from Noisy Patient-Reported Data Harry Rubin-Falcone, Joyce M. Lee, Jenna Wiens
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Do We Still Need Clinical Language Models? Eric Lehman, Evan Hernandez, Diwakar Mahajan, Jonas Wulff, Micah J Smith, Zachary Ziegler, Daniel Nadler, Peter Szolovits, Alistair Johnson, Emily Alsentzer
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Evaluating Model Performance in Medical Datasets over Time Helen Zhou, Yuwen Chen, Zachary Lipton
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Explaining a Machine Learning Decision to Physicians via Counterfactuals Supriya Nagesh, Nina Mishra, Yonatan Naamad, James M Rehg, Mehul A Shah, Alexei Wagner
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Fair Admission Risk Prediction with Proportional Multicalibration William G La Cava, Elle Lett, Guangya Wan
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Federated Multilingual Models for Medical Transcript Analysis Andrea Manoel, Mirian del Carmen Hipolito Garcia, Tal Baumel, Shize Su, Jialei Chen, Robert Sim, Dan Miller, Danny Karmon, Dimitrios Dimitriadis
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Homekit2020: A Benchmark for Time Series Classification on a Large Mobile Sensing Dataset with Laboratory Tested Ground Truth of Influenza Infections Mike A Merrill, Esteban Safranchik, Arinbjörn Kolbeinsson, Piyusha Gade, Ernesto Ramirez, Ludwig Schmidt, Luca Foschini, Tim Althoff
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Large-Scale Study of Temporal Shift in Health Insurance Claims Christina X Ji, Ahmed M Alaa, David Sontag
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Leveraging an Alignment Set in Tackling Instance-Dependent Label Noise Donna Tjandra, Jenna Wiens
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Machine Learning for Arterial Blood Pressure Prediction Jessica Zheng, Hanrui Wang, Anand Chandrasekhar, Aaron D Aguirre, Song Han, Hae-Seung Lee, Charles G Sodini
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Missing Values and Imputation in Healthcare Data: Can Interpretable Machine Learning Help? Zhi Chen, Sarah Tan, Urszula Chajewska, Cynthia Rudin, Rich Caruna
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Modeling Multivariate Biosignals with Graph Neural Networks and Structured State Space Models Siyi Tang, Jared A Dunnmon, Qu Liangqiong, Khaled K Saab, Tina Baykaner, Christopher Lee-Messer, Daniel L Rubin
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Multi-Modal Pre-Training for Medical Vision-Language Understanding and Generation: An Empirical Study with a New Benchmark Li Xu, Bo Liu, Ameer Hamza Khan, Lu Fan, Xiao-Ming Wu
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MultiWave: Multiresolution Deep Architectures Through Wavelet Decomposition for Multivariate Time Series Prediction Iman Deznabi, Madalina Fiterau
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Neural Fine-Gray: Monotonic Neural Networks for Competing Risks Vincent Jeanselme, Chang Ho Yoon, Brian Tom, Jessica Barrett
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PTGB: Pre-Train Graph Neural Networks for Brain Network Analysis Yi Yang, Hejie Cui, Carl Yang
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Rare Life Event Detection via Mobile Sensing Using Multi-Task Learning Arvind Pillai, Subigya Nepal, Andrew Campbell
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Rediscovery of CNN’s Versatility for Text-Based Encoding of Raw Electronic Health Records Eunbyeol Cho, Minjae Lee, Kyunghoon Hur, Jiyoun Kim, Jinsung Yoon, Edward Choi
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Revisiting Machine-Learning Based Drug Repurposing: Drug Indications Are Not a Right Prediction Target Siun Kim, Jung-Hyun Won, David Seung U Lee, Renqian Luo, Lijun Wu, Yingce Xia, Tao Qin, Howard Lee
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Self-Supervised Pretraining and Transfer Learning Enable\titlebreak Flu and COVID-19 Predictions in Small Mobile Sensing Datasets Mika A Merrill, Tim Althoff
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Semantic Match: Debugging Feature Attribution Methods \titlebreak in XAI for Healthcare Giovanni Cina, Tabea E Rober, Rob Goedhard, S Ilker Birbil
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SRDA: Mobile Sensing Based Fluid Overload Detection for End Stage Kidney Disease Patients Using Sensor Relation Dual Autoencoder Mingyu Tang, Jiechao Gao, Guimin Dong, Carl Yang, Bradford Campbell, Brendan Bowman, Jamie Marie Zoellner, Emaad Abdel-Rahman, Mehdi Boukhechba
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Token Imbalance Adaptation for Radiology Report Generation Yuexin Wu, I-Chan Huang, Xiaolei Huang
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Towards the Practical Utility of Federated Learning in the Medical Domain Hyeonji Hwang, Seongjun Yang, Daeyoung Kim, Radhika Dua, Jong-Yeup Kim, Eunho Yang, Edward Choi
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Understanding and Predicting the Effect of Environmental Factors on People with Type 2 Diabetes Kailas Vodrahalli, Gregory D Lyng, Brian L Hill, Kimmo Karkkainen, Jeffrey Hertzberg, James Zou, Eran Halperin
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Virus2Vec: Viral Sequence Classification Using Machine Learning Sarwan Ali, Babatunde Bello, Prakash Chourasia, Ria Thazhe Punathil, Pin-Yu Chen, Imdad Ullah Khan, Murray Patterson
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Who Controlled the Evidence? Question Answering for Disclosure Information Extraction Hardy Hardy, Derek Ruths, Nicholas B. King
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