yusuke1997/dblp-id-title huggingface dataset:
Clinical Intervention Prediction and Understanding with Deep Neural Networks
Benchmarking Reliability of Deep Learning Models for Pathological Gait Classification
Hidden Risks of Machine Learning Applied to Healthcare: Unintended Feedback Loops Between Models and Future Data Causing Model Degradation
FLARe: Forecasting by Learning Anticipated Representations
Deep EHR: Chronic Disease Prediction Using Medical Notes
Dynamically Personalized Detection of Hemorrhage
FineRadScore: A Radiology Report Line-by-Line Evaluation Technique Generating Corrections with Severity Scores
Effective Use of Bidirectional Language Modeling for Transfer Learning in Biomedical Named Entity Recognition
ICE-NODE: Integration of Clinical Embeddings with Neural Ordinary Differential Equations
An Evaluation of the Doctor-Interpretability of Generalized Additive Models with Interactions
Clinically Accurate Chest X-Ray Report Generation
Early Recognition of Sepsis with Gaussian Process Temporal Convolutional Networks and Dynamic Time Warping
Patient Similarity Using Population Statistics and Multiple Kernel Learning
Multinomial belief networks for healthcare data
Few-Shot Learning for Dermatological Disease Diagnosis
Feature Robustness in Non-stationary Health Records: Caveats to Deployable Model Performance in Common Clinical Machine Learning Tasks
ALGES: Active Learning with Gradient Embeddings for Semantic Segmentation of Laparoscopic Surgical Images
MRI-based Diagnosis of Rotator Cuff Tears using Deep Learning and Weighted Linear Combinations
MedAug: Contrastive learning leveraging patient metadata improves representations for chest X-ray interpretation
Reproducible Survival Prediction with SEER Cancer Data
3D Point Cloud-Based Visual Prediction of ICU Mobility Care Activities
Uncertainty-Aware Time-to-Event Prediction using Deep Kernel Accelerated Failure Time Models
Counterfactual Reasoning for Fair Clinical Risk Prediction
Thyroid Cancer Malignancy Prediction From Whole Slide Cytopathology Images
Diagnostic Inferencing via Improving Clinical Concept Extraction with Deep Reinforcement Learning: A Preliminary Study
Self-Supervised Pretraining with DICOM metadata in Ultrasound Imaging
A Spatiotemporal Approach to Predicting Glaucoma Progression Using a CT-HMM
Enhancing high-content imaging for studying microtubule networks at large-scale
Unified Auto Clinical Scoring (Uni-ACS) with Interpretable ML models
EVA: Generating Longitudinal Electronic Health Records Using Conditional Variational Autoencoders
Anomaly Detection in Human Brain via Inductive Learning on Temporal Multiplex Networks
Hierarchical Information Criterion for Variable Abstraction
Comparisons Between Hamiltonian Monte Carlo and Maximum A Posteriori For A Bayesian Model For Apixaban Induction Dose & Dose Personalization
Evaluating and interpreting caption prediction for histopathology images
Beyond Clinical Trials: Using Real World Evidence to Investigate Heterogeneous, Time-Varying Treatment Effects
CheXpert++: Approximating the CheXpert Labeler for Speed, Differentiability, and Probabilistic Output
HiCu: Leveraging Hierarchy for Curriculum Learning in Automated ICD Coding
Development and Validation of ML-DQA - a Machine Learning Data Quality Assurance Framework for Healthcare
Learning to Exploit Invariances in Clinical Time-Series Data using Sequence Transformer Networks
UDAMA: Unsupervised Domain Adaptation through Multi-discriminator Adversarial Training with Noisy Labels Improves Cardio-fitness Prediction
Machine Learning for Healthcare Conference, MLHC 2023, 11-12 August 2023, New York, USA
PRECISe : Prototype-Reservation for Explainable classification under Imbalanced and Scarce-Data Settings
Hawkes Process with Flexible Triggering Kernels
Neural Conditional Event Time Models
In-depth Benchmarking of Deep Neural Network Architectures for ECG Diagnosis
MIMIC-SBDH: A Dataset for Social and Behavioral Determinants of Health
Bidirectional Generative Pre-training for Improving Healthcare Time-series Representation Learning
EASL: A Framework for Designing, Implementing, and Evaluating ML Solutions in Clinical Healthcare Settings
Towards an Automated SOAP Note: Classifying Utterances from Medical Conversations
Classifying Lung Cancer Severity with Ensemble Machine Learning in Health Care Claims Data
Dynamic Survival Analysis for EHR Data with Personalized Parametric Distributions
Deep Survival Analysis
Power Constrained Bandits
Selective Fine-tuning on LLM-labeled Data May Reduce Reliance on Human Annotation: A Case Study Using Schedule-of-Event Table Detection
Learning from the experts: From expert systems to machine-learned diagnosis models
Multimodal Sleep Apnea Detection with Missing or Noisy Modalities
Addressing Sample Size Challenges in Linked Data Through Data Fusion
Marked Point Process for Severity of Illness Assessment
Uncovering the Varied Impact of Behavioral Change Messages on Population Groups
Directly Modeling Missing Data in Sequences with RNNs: Improved Classification of Clinical Time Series
FairEHR-CLP: Towards Fairness-Aware Clinical Predictions with Contrastive Learning in Multimodal Electronic Health Records
A Non-parametric Bayesian Approach for Estimating Treatment-Response Curves from Sparse Time Series
Characterizing personalized effects of family information on disease risk using graph representation learning
Using Domain Knowledge to Overcome Latent Variables in Causal Inference from Time Series
Learning to Summarize Electronic Health Records Using Cross-Modality Correspondences
Towards data-driven stroke rehabilitation via wearable sensors and deep learning
Learning Robust Features using Deep Learning for Automatic Seizure Detection
Updating Clinical Risk Stratification Models Using Rank-Based Compatibility: Approaches for Evaluating and Optimizing Clinician-Model Team Performance
Back to the basics with inclusion of clinical domain knowledge - A simple, scalable and effective model of Alzheimer's Disease classification
A Neural Model for Predicting Dementia from Language
How fair is your graph? Exploring fairness concerns in neuroimaging studies
Temporal prediction of multiple sclerosis evolution from patient-centered outcomes
Jointly Extracting Interventions, Outcomes, and Findings from RCT Reports with LLMs
Risk stratification through class-conditional conformal estimation: A strategy that improves the rule-out performance of MACE in the prehospital setting
gLOP: the global and Local Penalty for Capturing Predictive Heterogeneity
Self-Attention Based Molecule Representation for Predicting Drug-Target Interaction
Few-Shot Learning with Semi-Supervised Transformers for Electronic Health Records
PrivECG: generating private ECG for end-to-end anonymization
Coarse race data conceals disparities in clinical risk score performance
Hawkes Process Modeling of Adverse Drug Reactions with Longitudinal Observational Data
Contrastive Learning of Medical Visual Representations from Paired Images and Text
Deep Cox Mixtures for Survival Regression
A Domain Guided CNN Architecture for Predicting Age from Structural Brain Images
Proceedings of the Machine Learning for Healthcare Conference, MLHC 2020, 7-8 August 2020, Virtual Event, Durham, NC, USA
Proceedings of the 1st Machine Learning in Health Care, MLHC 2016, Los Angeles, CA, USA, August 19-20, 2016
Boosted Trees for Risk Prognosis
Using Contextual Information to Improve Blood Glucose Prediction
Semi-Supervised Generative Models for Disease Trajectories: A Case Study on Systemic Sclerosis
Evaluating Uncertainty-Based Deep Learning Explanations for Prostate Lesion Detection
Surgeon Technical Skill Assessment using Computer Vision based Analysis
Multimodal Machine Learning for Automated ICD Coding
Visualizing Clinical Significance with Prediction and Tolerance Regions
A Meta-Evaluation of Faithfulness Metrics for Long-Form Hospital-Course Summarization
Clinical Tagging with Joint Probabilistic Models
Preparing a Clinical Support Model for Silent Mode in General Internal Medicine
Proceedings of the Machine Learning for Healthcare Conference, MLHC 2018, 17-18 August 2018, Palo Alto, California
Clinical Judgement Study using Question Answering from Electronic Health Records
LLMSYN: Generating Synthetic Electronic Health Records Without Patient-Level Data
Personalized Input-Output Hidden Markov Models for Disease Progression Modeling
Relaxed Parameter Sharing: Effectively Modeling Time-Varying Relationships in Clinical Time-Series
Scaling Clinical Trial Matching Using Large Language Models: A Case Study in Oncology
Multi-task Learning with Weak Class Labels: Leveraging iEEG to Detect Cortical Lesions in Cryptogenic Epilepsy
Deep Cascade Learning for Optimal Medical Image Feature Representation
Multi-Label Learning from Medical Plain Text with Convolutional Residual Models
Racial Disparities and Mistrust in End-of-Life Care
Deep Kernel Survival Analysis and Subject-Specific Survival Time Prediction Intervals
Mitochondria-based Renal Cell Carcinoma Subtyping: Learning from Deep vs. Flat Feature Representations
Developing Personalized Models of Blood Pressure Estimation from Wearable Sensors Data Using Minimally-trained Domain Adversarial Neural Networks
ShortFuse: Biomedical Time Series Representations in the Presence of Structured Information
Learning to Ask Medical Questions using Reinforcement Learning
Direct Preference Optimization for Suppressing Hallucinated Prior Exams in Radiology Report Generation
The Medical Deconfounder: Assessing Treatment Effects with Electronic Health Records
Neurological Prognostication of Post-Cardiac-Arrest Coma Patients Using EEG Data: A Dynamic Survival Analysis Framework with Competing Risks
Leveraging LLMs for Multimodal Medical Time Series Analysis
Using Kernel Methods and Model Selection for Prediction of Preterm Birth
An hybrid CNN-Transformer model based on multi-feature extraction and attention fusion mechanism for cerebral emboli classification
Needles in Needle Stacks: Meaningful Clinical Information Buried in Noisy Sensor Data
Online Unsupervised Representation Learning of Waveforms in the Intensive Care Unit via a novel cooperative framework: Spatially Resolved Temporal Networks (SpaRTEn)
Predicting Drug Sensitivity of Cancer Cell Lines via Collaborative Filtering with Contextual Attention
GeoECG: Data Augmentation via Wasserstein Geodesic Perturbation for Robust Electrocardiogram Prediction
MedFuse: Multi-modal fusion with clinical time-series data and chest X-ray images
Students Need More Attention: BERT-based Attention Model for Small Data with Application to Automatic Patient Message Triage
Efficient Representation Learning for Healthcare with Cross-Architectural Self-Supervision
Proceedings of the Machine Learning for Healthcare Conference, MLHC 2019, 9-10 August 2019, Ann Arbor, Michigan, USA
Which Explanation Makes Sense? A Critical Evaluation of Local Explanations for Assessing Cervical Cancer Risk
Automated Treatment Planning in Radiation Therapy using Generative Adversarial Networks
Understanding Coagulopathy using Multi-view Data in the Presence of Sub-Cohorts: A Hierarchical Subspace Approach
The Data Addition Dilemma
Multi-view Modelling of Longitudinal Health Data for Improved Prognostication of Colorectal Cancer Recurrence
Multiple Instance Learning for ECG Risk Stratification
Approximate Bayesian Computation for an Explicit-Duration Hidden Markov Model of COVID-19 Hospital Trajectories
Interpretable (not just posthoc-explainable) heterogeneous survivors bias-corrected treatment effects for assignment of postdischarge interventions to prevent readmissions
Reducing Contextual Bias in Cardiac Magnetic Resonance Imaging Deep Learning Using Contrastive Self-Supervision
Directing Human Attention in Event Localization for Clinical Timeline Creation
Continuous State-Space Models for Optimal Sepsis Treatment: a Deep Reinforcement Learning Approach
Survival Mixture Density Networks
Spatially-Continuous Plantar Pressure Reconstruction Using Compressive Sensing
Attentive Adversarial Network for Large-Scale Sleep Staging
Why predicting risk can't identify 'risk factors': empirical assessment of model stability in machine learning across observational health databases
Diagnosing Epileptogenesis with Deep Anomaly Detection
Weakly Supervised Deep Instance Nuclei Detection using Points Annotation in 3D Cardiovascular Immunofluorescent Images
What Clinicians Want: Contextualizing Explainable Machine Learning for Clinical End Use
Predictive Powered Inference for Healthcare; Relating Optical Coherence Tomography Scans to Multiple Sclerosis Disease Progression
Reducing Reliance on Spurious Features in Medical Image Classification with Spatial Specificity
Dynamically Extracting Outcome-Specific Problem Lists from Clinical Notes with Guided Multi-Headed Attention
Bayesian Trees for Automated Cytometry Data Analysis
Predicting Long-Term Allograft Survival in Liver Transplant Recipients
Point Processes for Competing Observations with Recurrent Networks (POPCORN): A Generative Model of EHR Data
Searching for Fine-Grained Queries in Radiology Reports Using Similarity-Preserving Contrastive Embedding
Diagnostic Prediction Using Discomfort Drawings with IBTM
Detecting Heart Disease from Multi-View Ultrasound Images via Supervised Attention Multiple Instance Learning
Classifying Unstructured Clinical Notes via Automatic Weak Supervision
An Improved Multi-Output Gaussian Process RNN with Real-Time Validation for Early Sepsis Detection
Integrating Hypertension Phenotype and Genotype with Hybrid Non-negative Matrix Factorization
Conceptualizing Machine Learning for Dynamic Information Retrieval of Electronic Health Record Notes
Decision-Focused Model-based Reinforcement Learning for Reward Transfer
Ensembling Neural Networks for Improved Prediction and Privacy in Early Diagnosis of Sepsis
AIRIVA: A Deep Generative Model of Adaptive Immune Repertoires
Reproducibility in critical care: a mortality prediction case study
Towards Understanding ECG Rhythm Classification Using Convolutional Neural Networks and Attention Mappings
AudiFace: Multimodal Deep Learning for Depression Screening
EEGtoText: Learning to Write Medical Reports from EEG Recordings
KCRL: A Prior Knowledge Based Causal Discovery Framework with Reinforcement Learning
A New Semi-supervised Learning Benchmark for Classifying View and Diagnosing Aortic Stenosis from Echocardiograms
Deep Convolutional Neural Networks for Microscopy-Based Point of Care Diagnostics
Detecting Atrial Fibrillation in ICU Telemetry data with Weak Labels
General-Purpose Retrieval-Enhanced Medical Prediction Model Using Near-Infinite History
Deep Reinforcement Learning for Closed-Loop Blood Glucose Control
Predicting long-term mortality with first week post-operative data after Coronary Artery Bypass Grafting using Machine Learning models
A Multi Instance Learning Approach for Critical View of Safety Detection in Laparoscopic Cholecystectomy
Read, Attend, and Code: Pushing the Limits of Medical Codes Prediction from Clinical Notes by Machines
Differentially Private Survival Function Estimation
Medically Aware GPT-3 as a Data Generator for Medical Dialogue Summarization
Learning functional sections in medical conversations: iterative pseudo-labeling and human-in-the-loop approach
MedAutoCorrect: Image-Conditioned Autocorrection in Medical Reporting
Towards Early Diagnosis of Epilepsy from EEG Data
Transferring Knowledge from Text to Predict Disease Onset
Using deep networks for scientific discovery in physiological signals
Contactless Oxygen Monitoring with Radio Waves and Gated Transformer
Multi-task multiple kernel learning reveals relevant frequency bands for critical areas localization in focal epilepsy
Phenotyping with Prior Knowledge using Patient Similarity
Incorporating External Information in Tissue Subtyping: A Topic Modeling Approach
ScanMap: Supervised Confounding Aware Non-negative Matrix Factorization for Polygenic Risk Modeling
Deep Survival Analysis: Nonparametrics and Missingness
XDT-CXR: Investigating Cross-Disease Transferability in Zero-Shot Binary Classification of Chest X-Rays
Predicting Disease Progression with a Model for Multivariate Longitudinal Clinical Data
Proceedings of the Machine Learning for Health Care Conference, MLHC 2017, Boston, Massachusetts, USA, 18-19 August 2017
Preference Learning in Assistive Robotics: Observational Repeated Inverse Reinforcement Learning
MALADE: Orchestration of LLM-powered Agents with Retrieval Augmented Generation for Pharmacovigilance
When More is Less: Incorporating Additional Datasets Can Hurt Performance By Introducing Spurious Correlations
A Comprehensive View of Personalized Federated Learning on Heterogeneous Clinical Datasets
CORE-BEHRT: A Carefully Optimized and Rigorously Evaluated BEHRT
Predicting Surgery Duration with Neural Heteroscedastic Regression
Query-Focused EHR Summarization to Aid Imaging Diagnosis
Reinforcement Learning with Action-Derived Rewards for Chemotherapy and Clinical Trial Dosing Regimen Selection
Deep Learning Applied to Chest X-Rays: Exploiting and Preventing Shortcuts
Learning from Few Subjects with Large Amounts of Voice Monitoring Data
CheXbreak: Misclassification Identification for Deep Learning Models Interpreting Chest X-rays
Disease-Atlas: Navigating Disease Trajectories using Deep Learning
Predictive Hierarchical Clustering: Learning clusters of CPT codes for improving surgical outcomes
Anomaly Detection in Echocardiograms with Dynamic Variational Trajectory Models
UPSTAGE: Unsupervised Context Augmentation for Utterance Classification in Patient-Provider Communication
Semi-supervised Meta-learning for Multi-source Heterogeneity in Time-series Data
Preterm Birth Prediction: Stable Selection of Interpretable Rules from High Dimensional Data
ASAC: Active Sensing using Actor-Critic models
Uncovering Voice Misuse Using Symbolic Mismatch
Learning Optimal Dynamic Treatment Regimes Using Causal Tree Methods in Medicine
Localising the Seizure Onset Zone from Single-Pulse Electrical Stimulation Responses with a CNN Transformer
A Deep Learning Based Framework for Joint Image Registration and Segmentation of Brain Metastases on Magnetic Resonance Imaging
Piecewise-constant parametric approximations for survival learning
Robust Semi-supervised Detection of Hands in Diverse Open Surgery Environments
Input-Output Non-Linear Dynamical Systems applied to Physiological Condition Monitoring
Learning Missing Modal Electronic Health Records with Unified Multi-modal Data Embedding and Modality-Aware Attention
Predicting Phase 3 Clinical Trial Results by Modeling Phase 2 Clinical Trial Subject Level Data Using Deep Learning
Event-Based Contrastive Learning for Medical Time Series
DOSSIER: Fact Checking in Electronic Health Records while Preserving Patient Privacy
Knowledge Graph-based Question Answering with Electronic Health Records
Temporal Graph Convolutional Networks for Automatic Seizure Detection
Optimizing Influenza Vaccine Composition: From Predictions to Prescriptions
Debiasing Deep Chest X-Ray Classifiers using Intra- and Post-processing Methods
Mixed Type Multimorbidity Variational Autoencoder: A Deep Generative Model for Multimorbidity Analysis
Disparate Censorship & Undertesting: A Source of Label Bias in Clinical Machine Learning
Clinical Collabsheets: 53 Questions to Guide a Clinical Collaboration
Predicting Sick Patient Volume in a Pediatric Outpatient Setting using Time Series Analysis
Typed Markers and Context for Clinical Temporal Relation Extraction
Reinforcement Learning For Sepsis Treatment: A Continuous Action Space Solution
TIER: Text-Image Entropy Regularization for Medical CLIP-style models
RadGraph2: Modeling Disease Progression in Radiology Reports via Hierarchical Information Extraction
An Interpretable Framework for Drug-Target Interaction with Gated Cross Attention
Generating Multi-label Discrete Patient Records using Generative Adversarial Networks
Region-based Saliency Explanations on the Recognition of Facial Genetic Syndromes
Pattern-Based Behavioural Analysis on Neurosurgical Simulation Data
Latent Temporal Flows for Multivariate Analysis of Wearables Data
Fast, Structured Clinical Documentation via Contextual Autocomplete
Towards a Directory of Rare Disease Specialists: Identifying Experts from Publication History
DuETT: Dual Event Time Transformer for Electronic Health Records
Transfer Learning from Well-Curated to Less-Resourced Populations with HIV
Measuring the Sympathetic Response to Intense Exercise in a Practical Setting
Dialogue-Contextualized Re-ranking for Medical History-Taking
Understanding Clinical Collaborations Through Federated Classifier Selection
EEG to fMRI Synthesis Benefits from Attentional Graphs of Electrode Relationships
SurvLatent ODE : A Neural ODE based time-to-event model with competing risks for longitudinal data improves cancer-associated Venous Thromboembolism (VTE) prediction
A Calibration Metric for Risk Scores with Survival Data
Automatically Extracting Numerical Results from Randomized Controlled Trials with Large Language Models
auton-survival: an Open-Source Package for Regression, Counterfactual Estimation, Evaluation and Phenotyping with Censored Time-to-Event Data
Multi-Label Generalized Zero Shot Learning for the Classiffcation of Disease in Chest Radiographs
A LUPI distillation-based approach: Application to predicting Proximal Junctional Kyphosis
Comparing Machine Learning Techniques for Blood Glucose Forecasting Using Free-living and Patient Generated Data
Identifiable Phenotyping using Constrained Non-Negative Matrix Factorization
ScoEHR: Generating Synthetic Electronic Health Records using Continuous-time Diffusion Models
Learning Optimal Summaries of Clinical Time-series with Concept Bottleneck Models
Risk score learning for COVID-19 contact tracing apps
Flexible Industrial Applications Through Model-Based Workflows
A' standards' Foundation for Interoperability
Knowledge Sharing in the Integrated Enterprise - Interoperability Strategies for the Enterprise Architect, 2004 International Conference on Enterprise Integration and Modelling Technology, ICEIMT 2004, The 7th International Conference on Design of Information Infrastructure Systems for Manufacturing, DIISM 2004, 9-11 October 2004, University of Toronto, Canada
Standards in Enterprise Inter- and Intra-Organisational Integration
Needs and Characteristics of Methodologies for Enterprise Integration
Steps in Enterprise Modelling
Argumentation for Explicit Representation of Control with Enterprise Modelling and Integration
Building a Better Team
Methodologies for Enterprise Integration
Development of Integrated Enterprise Models
Enterprise Modelling Languages
Component-Based Automotive Production Systems
Enterprise Integration Engineering as an Enabler for Business Process Management
Human Factors and Enterprise Integration - Workshop 1, Working Group 2
Modelling of Distributed Business Processes
System Requirements: Products, Processes and Models
Accomplishments of the ICEIMT'02
The Users View of Enterprise Integration and the Enterprise Process Architecture
Ontologies for Semantically Interoperable Electronic Commerce
Enterprise Integration Approaches in Healthcare: A Decade of Trial and Error
A Vision of Enterprise Integration Considerations - A holistic perspective as shown by the Purdue Enterprise Reference Architecture
ATHENA Integrated Project and the Mapping to International Standard ISO 15704
Manipulation Planning for Knotting Linear Objects with One Hand
Enterprise Architecture and Systems Engineering
Interoperability of Standards to Support Application Integration
Opportunities for Software Support to the Simulation Process
A Meta-methodology for Collaborative Network Organisations: A Case Study and Reflections
Characterization of the Place of the Human in Enterprise Integration
Language Semantics
The Business Process (Quiet) Revolution
Workflow Quality of Service
A Merged Future for Knowledge Management and Enterprise Modeling
Organisation Issues and the ACNOS Approach
ICEIMT in Perspective - 92 to 97
How to Model Business Processes with GPN
Agents and Advanced Virtual Enterprises: Needs and an Approach
Workbench: A Planning Tool for Faster Factory Optimization
Enterprise Modelling and Integration
A Framework for Standards which Support the Virtual Enterprise
Ontologies as a New Cost Factor in Enterprise Integration