:: Library Catalog

Copertina

Salvato in:

Dettagli Bibliografici
Autori principali:	Pande, Kalyani P., Yang, Evan, Zhu, Bryan, Mallipattu, Sandeep K., Yurovsky, Alisa, Ma, Tengfei
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Machine Learning
Accesso online:	https://arxiv.org/abs/2604.24547
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Predicting Future Risk of Dementia Using Machine Learning and Longitudinal Electronic Health Records
di: Zehao Ye, et al.
Pubblicazione: (2025)

HypEHR: Hyperbolic Modeling of Electronic Health Records for Efficient Question Answering
di: Liu, Yuyu, et al.
Pubblicazione: (2026)

PEaRL: Pathway-Enhanced Representation Learning for Gene and Pathway Expression Prediction from Histology
di: Majumder, Sejuti, et al.
Pubblicazione: (2025)

Prompting Large Language Models for Zero-Shot Clinical Prediction with Structured Longitudinal Electronic Health Record Data
di: Zhu, Yinghao, et al.
Pubblicazione: (2024)

Subtype-Aware Registration of Longitudinal Electronic Health Records
di: Gai, Xin, et al.
Pubblicazione: (2025)

Privacy-Preserving Predictive Analytics for Healthcare Risk Stratification
di: Rachapalli, Sai Kalyani
Pubblicazione: (2020)

MERGE: Multi-faceted Hierarchical Graph-based GNN for Gene Expression Prediction from Whole Slide Histopathology Images
di: Ganguly, Aniruddha, et al.
Pubblicazione: (2024)

Population stratification for prediction of mortality in post-AKI patients
di: da Silva, Flavio S. Correa, et al.
Pubblicazione: (2024)

Recent Advances in Predictive Modeling with Electronic Health Records
di: Wang, Jiaqi, et al.
Pubblicazione: (2024)

Conditional Wasserstein GAN for Simulating Neutrino Event Summaries using Incident Energy of Electron Neutrinos
di: S., Dipthi, et al.
Pubblicazione: (2026)

EMERGE: Enhancing Multimodal Electronic Health Records Predictive Modeling with Retrieval-Augmented Generation
di: Zhu, Yinghao, et al.
Pubblicazione: (2024)

Inverse Probability of Treatment Weighting with Deep Sequence Models Enables Accurate treatment effect Estimation from Electronic Health Records
di: Lee, Junghwan, et al.
Pubblicazione: (2024)

On the Numerical Stability of the Diffusion Coefficient in Microscopic Simulations
di: Yurovsky, Vladimir, et al.
Pubblicazione: (2026)

FHIRPath-QA: Executable Question Answering over FHIR Electronic Health Records
di: Frew, Michael, et al.
Pubblicazione: (2026)

Automated Fusion of Multimodal Electronic Health Records for Better Medical Predictions
di: Cui, Suhan, et al.
Pubblicazione: (2024)

Foundation Model of Electronic Medical Records for Adaptive Risk Estimation
di: Renc, Pawel, et al.
Pubblicazione: (2025)

Causal Fairness Assessment of Treatment Allocation with Electronic Health Records
di: Zhang, Linying, et al.
Pubblicazione: (2022)

Cross-Representation Benchmarking in Time-Series Electronic Health Records for Clinical Outcome Prediction
di: Chen, Tianyi, et al.
Pubblicazione: (2025)

Estimating Effects of Longitudinal Modified Treatment Policies (LMTPs) on Rates of Change in Health Outcomes
di: Shahu, Anja, et al.
Pubblicazione: (2025)

Estimating Effects of Longitudinal Modified Treatment Policies ( LMTPs ) on Rates of Change in Health Outcomes
di: Anja Shahu, et al.
Pubblicazione: (2026)

Synthesizing Multimodal Electronic Health Records via Predictive Diffusion Models
di: Zhong, Yuan, et al.
Pubblicazione: (2024)

Risk Factors for Mild Cognitive Impairment: Prediction Models Developed with Electronic Health Record Data
di: Gang Li, et al.
Pubblicazione: (2024)

Early Prediction of Alzheimers Disease Leveraging Symptom Occurrences from Longitudinal Electronic Health Records of US Military Veterans
di: Li, Rumeng, et al.
Pubblicazione: (2023)

A Comprehensive Benchmark for COVID-19 Predictive Modeling Using Electronic Health Records in Intensive Care
di: Gao, Junyi, et al.
Pubblicazione: (2022)

Trustworthy Agents for Electronic Health Records through Confidence Estimation
di: Song, Yongwoo, et al.
Pubblicazione: (2025)

Eigenstate thermalization to non-monotonic distributions in strongly-interacting chaotic lattice gases
di: Yurovsky, Vladimir A., et al.
Pubblicazione: (2025)

Heterogeneous Quantile Treatment Effect Estimation for Longitudinal Data with High-Dimensional Confounding
di: Qiu, Zhixin, et al.
Pubblicazione: (2025)

Automatic Cardiac Risk Management Classification using large-context Electronic Patients Health Records
di: Vitale, Jacopo, et al.
Pubblicazione: (2026)

Machine Learning Approaches to Clinical Risk Prediction: Multi-Scale Temporal Alignment in Electronic Health Records
di: Chang, Wei-Chen, et al.
Pubblicazione: (2025)

ASCENDgpt: A Phenotype-Aware Transformer Model for Cardiovascular Risk Prediction from Electronic Health Records
di: Sainsbury, Chris, et al.
Pubblicazione: (2025)

Augmented Risk Prediction for the Onset of Alzheimer's Disease from Electronic Health Records with Large Language Models
di: Wang, Jiankun, et al.
Pubblicazione: (2024)

Antigen Specificity: A Fluctuating Aspect in the Development of Clinical Antibodies?
di: Sandeep, et al.
Pubblicazione: (2025)

Predictive Modeling with Temporal Graphical Representation on Electronic Health Records
di: Chen, Jiayuan, et al.
Pubblicazione: (2024)

Longitudinal Mammogram Risk Prediction
di: Karaman, Batuhan K., et al.
Pubblicazione: (2024)

Annotation-Assisted Learning of Treatment Policies From Multimodal Electronic Health Records
di: Arno, Henri, et al.
Pubblicazione: (2025)

Suicide in Children and Adolescents: New Interventions and Risk FactorsBy Michelle A.Patriquin and Katrina A.Rufino (eds.), London: Taylor and Francis, 2023. 138 pp. ISBN: 9781032058412
di: V. Kalyani
Pubblicazione: (2025)

LAITAKAUPUNGIN VALOTO DE AKI KAURISMAKI
di: Jesús Miguel Sáez González
Pubblicazione: (2007)

Early Risk Prediction of Pediatric Cardiac Arrest from Electronic Health Records via Multimodal Fused Transformer
di: Lu, Jiaying, et al.
Pubblicazione: (2025)

KAT-GNN: A Knowledge-Augmented Temporal Graph Neural Network for Risk Prediction in Electronic Health Records
di: Lin, Kun-Wei, et al.
Pubblicazione: (2025)

Autocompletion of Chief Complaints in the Electronic Health Records using Large Language Models
di: Islam, K M Sajjadul, et al.
Pubblicazione: (2024)