Publications citing MIMIC-III Clinical Database Demo v1.4

Association between antithrombin levels and prognosis in patients with sepsis: a retrospective cohort study based on the MIMIC-IV and MIMIC-III databases
Bingkui Ren, Gang Zhou, Haiyan Xue et al. Journal of Intensive Care, 2026. Cites: paper

Artificial intelligence-assisted phenotyping of sepsis: Research progress, clinical challenges, and translational prospects
Hang Ruan, Jing-Kun Lee, Jie Xiong et al. Digital Health, 2026. Cites: paper

Contextualized clinical anomaly detection with explainable AI and patient modeling
Amel Elketroussi, Bachir Djebbar, Ibtissem Bekkouche. Indonesian Journal of Electrical Engineering and Computer Science, 2026. Cites: paper

Explainable AI for mortality prediction: a comparative study using the MIMIC-III dataset
Niusha Shafiabady, Dave Akume, Mohammadreza Haghighat et al. BMJ Health & Care Informatics, 2026. Cites: paper

Federated learning for heterogeneous electronic health record systems with cost effective participant selection
Junsu Kim, Junsu Kim, Kyunghoon Hur et al. Scientific Reports, 2026. Cites: paper

Semantic analysis of SNOMED CT concept co-occurrences in clinical documentation using MIMIC-IV
Ali Noori, Prashanti Manda. Digital Health, 2026. Cites: paper

Transformers for Graph-based Recommender Systems: A Survey
Lorenzo Zangari, Sílvio Raso, Andrea Tagarelli. Machine Intelligence Research, 2026. Cites: paper

Conflux: A High-Performance Keyword Private Retrieval System for Dynamic Datasets
Zehao Chen, Zhaoyan Shen, Qian Wei et al. IEEE International Symposium on High-Performance Computer Architecture (HPCA), 2026. Cites: paper

KATMed: a knowledge-augmented transformer model for contraindication-aware medication recommendation in comorbidities
Ziqian Qiao, Shaofu Lin, Jiatong Fan et al. Journal of Biomedical Informatics, 2026. Cites: paper

CLOVER: A framework for benchmarking synthetic data generation methods balancing utility and privacy in healthcare
Yue Qi, Lorrie Herbault, Hadrien Lautraite et al. Artificial Intelligence in the Life Sciences, 2026. Cites: paper

Multimodal spatiotemporal graph convolutional attention network for dynamic risk stratification and intervention strategy generation in rare disease rehabilitation nursing
Siwen Zhao, Min Hu, Shan Fang. Scientific Reports, 2026. Cites: paper

Revisiting NLP applications using MIMIC data: A systematic literature review toward advancing clinical processes and workflows in the Era of LLMs
Jiawei Wu, Nazmus Sakib, Fahim Islam Anik et al. Smart Health, 2026. Cites: paper

A survey On large language models for medical time series
Xingyue Liu, Feizhong Zhou, Hanguang Xiao et al. Expert Systems with Applications, 2026. Cites: paper

Liver Infection Detection Using Machine Learning
Sulekh Kumar, Momita Kundu, Kamla Kumari et al. International Conference on Recent Trends in Computer Science and Technology (ICRTCST), 2026. Cites: paper

Large language models for clinical artificial intelligence in healthcare a systematic review
Rawan Ghnemat, Amro Saleh. Discover Artificial Intelligence, 2026. Cites: paper

PPG-AFNet: a lightweight and intelligible network for atrial fibrillation identification using photoplethysmography signals
Preeti P. Ghasad, Bhupendra Tiwari, Vipin Milind Kamble et al. Biomedical Engineering Letters, 2026. Cites: paper

Cyber-Medical Systems for AI-Driven Precision and Preventive Healthcare
Keshab Chandra Nath. 2026. Cites: paper

Interdisciplinary expertise to advance human-centered explainable AI
Chloe R. Bennett, Heather J. Cole-Lewis, Stephanie Ann Farquhar et al. Social Science & Medicine, 2026. Cites: paper

Multi-Model Fusion for 28-Day Mortality Prediction in ICU Patients: A Comprehensive Retrospective Cohort Study with Subgroup Validation and Clinical Risk Stratification
Zhanzhi Long, Shijun Tong. Shock, 2026. Cites: paper

Exploring the association between dexmedetomidine and all-cause mortality in mechanically ventilated patients with sepsis through propensity score matching analysis and machine learning algorithms: a MIMIC-IV retrospective study
Yanxia Wei, Minghui Li, Peng Wang et al. Frontiers in Cellular and Infection Microbiology, 2026. Cites: paper

Optimizing ED patient disposition predictions through clinical narratives with advanced pre-trained language models
Mei-Hui Lee, Ting-Yun Huang, Pei-Ying Yang et al. Health Information Science and Systems, 2026. Cites: paper

The next frontier in sepsis: connected ICU data for real-world clinical decision making
Ricardo Simón Carbajo, Julia Palma, Ignacio Martín‐Loeches. Intensive Care Medicine, 2026. Cites: paper

KRAM: Knowledge-driven robust training against label noise for medication recommendation
Yuan Jin, Zhen Zhang. Expert Systems with Applications, 2026. Cites: paper

Developing a multi-domain EHR foundation model for predicting Hepatitis B liver disease: a clinical perspective
Caroline Weis, Filippo Grazioli, Giovanni Visonà et al. medRxiv, 2026. Cites: paper

IKDP: Implicit Knowledge Enhanced Disease Prediction via heterogeneous admission sequence graphs
Zongbao Yang, Yuchen Lin, Yichen He et al. Artificial Intelligence in Medicine, 2026. Cites: paper

Optimizing atrial fibrillation detection through ECG feature selection using Extra-Trees and statistical association measures
Γεώργιος Πετμεζάς, Vasileios Ε. Papageorgiou, ROD S. PASSMAN et al. Journal of Electrocardiology, 2026. Cites: paper

Artificial Intelligence and Deep Learning-Based Methods and Devices for Measuring Vital Signs: A Systematic Review
César Castrejón-Peralta, Jesús Yaljá Montiel-Pérez, Saulo Abraham Gante-Díaz et al. Applied Sciences, 2026. Cites: paper

The role of artificial intelligence in predicting COPD exacerbations using multimodal data: a systematic review
Christelos Kapatais, Theofanie Karaoulani, Anastasia Papanikolaou et al. ERJ Open Research, 2026. Cites: paper

A comparative evaluation of handling missing data points and modalities in electronic health records
Aashish Bhandari, Sonika Tyagi. International Journal of Medical Informatics, 2026. Cites: paper

A gradual coarse-to-fine framework for irregularly sampled multivariate time series analysis
Jiexi Liu, Meng Cao, Songcan Chen. Science China Information Sciences, 2026. Cites: paper

Generalized Label-Free Artefact Cleaning for Real-Time Medical Pulsatile Time Series
Xuhang Chen, Ihsane Olakorede, Stefan Yu Bögli et al. IEEE Transactions on Biomedical Engineering, 2026. Cites: paper

Hybrid deep learning framework for accurate classification of high dimensional genomic data
Manas Kumar Swain, Narendra Kumar Kamila, Lambodar Jena et al. Scientific Reports, 2026. Cites: paper

Large Language Models in Radiologic Numerical Tasks: A Thorough Evaluation and Error Analysis
Ali Nowroozi, Masha Bondarenko, Adrian Serapio et al. Journal of Imaging Informatics in Medicine, 2026. Cites: paper

Perspective Chapter: Quality Assurance in Unstructured Data – Challenges, Methods, and Practical Frameworks
Dinh Tuan Tran. IntechOpen eBooks, 2026. Cites: paper

Analysis of the Correlation Between Perioperative Temperature Trajectory and All-Cause Mortality in Elderly Cardiac Patients
Yujie Fan, Hao Yuan, Zefeng Yang et al. Research Square, 2026. Cites: paper

HeteroMed: a heterogeneous graph knowledge-enhanced model for medication recommendation
Xuelei Yin, Mengzhu Liu, Zaiquan Dong et al. Health Information Science and Systems, 2026. Cites: paper

Modernizing Data Quality: Evolving Dimensions for Unstructured Text Data in Big Data, AI and Ethical Contexts
Ning Wang, Seong-Gyun Leem. IntechOpen eBooks, 2026. Cites: paper

Clinician preferences for explainable AI in critical care: a comparative study of interpretable models and visualizations for intubation decision support
Tiantian Xian, Nikolay Mehandjiev, Panos Constantinides et al. International Journal of Medical Informatics, 2026. Cites: paper

Electrocardiography Meets Artificial Intelligence: Shaping the Future of Heart Failure Prediction A Comprehensive Review
Faiza Hadid Blaiech, Jamel Hattay, Mohsen Machhout. Research Square, 2026. Cites: paper

RETRACTED ARTICLE: DynaGraph: interpretable dynamic graph learning for temporal electronic health records
Munib Mesinovic, Soheila Molaei, Peter Watkinson et al. npj Digital Medicine, 2026. Cites: paper

Bioinformatics in anaesthesia: A new era of personalised and predictive perioperative care
Alfairose Jahangeerbasha, Rupika Ekambaram, M. R. Suchitra et al. Indian Journal of Clinical Anaesthesia, 2026. Cites: paper

Enhancing Clinical Note Generation with ICD-10, Clinical Ontology Knowledge Graphs, and Chain-of-Thought Prompting Using GPT-4
Ivan Makohon, Mohamad Najafi, Jian Feng Wu et al. Journal of Computational Biology, 2026. Cites: paper

Integrating knowledge graph embeddings with clinical data: A case study on Acute Kidney Injury prediction
Samuele Buosi, Mohan Timilsina, Conor S. Judge et al. Informatics in Medicine Unlocked, 2026. Cites: paper

Towards active participant centric vertical federated learning: Some representations may be all you need
Jon Irureta, Jon Imaz, Aizea Lojo et al. Knowledge-Based Systems, 2026. Cites: paper

Development of Machine Learning Models to Predict 28-Day Mortality in Patients with Sepsis-Associated Liver Injury
Yupeng Li, Junyi Fan, Kamiar Alaei et al. BioMedInformatics, 2026. Cites: paper

Real-time prediction of ventilator-associated pneumonia onset in ICU: development of a dynamic machine learning model
Simone Zappalá, Lucrezia Rovati, Francesca Alfieri et al. Journal of Anesthesia Analgesia and Critical Care, 2026. Cites: paper

RFDR: a retransmission-free data reconstruction framework for emergency response networks
Yayong Shi, Weidang Lu, Nan Zhao et al. Science China Information Sciences, 2026. Cites: paper

AI-driven integration of imaging and radiology language improves stroke mortality prediction
Albara Alotaibi, Abdalla Sayed Abdelrakib Moustafa, Laith Abualloush. Frontiers in Neurology, 2026. Cites: paper

Biomedical text summarization with large language models: methodologies, challenges, and future directions
Shafiya Mushtaq, K. Veningston. International Journal of Data Science and Analytics, 2026. Cites: paper

Unraveling Spatio-Temporal Foundation Models via the Pipeline Lens: A Comprehensive Review
Yu Fang, Hao Miao, Yuxuan Liang et al. IEEE Transactions on Knowledge and Data Engineering, 2026. Cites: paper

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