Publications citing MIMIC-III Clinical Database Demo v1.4

Explainable Machine Learning for Prediction of Future High-Severity States Using Longitudinal APACHE-II Trajectories: Internal Validation and Cross-Cohort Portability Assessment
İrem Akpolat, Fatma Çelik. Diagnostics, 2026. Cites: paper

Healthcare bias estimation with XAI model for clinical workflow
Vijay R Sonawane, Ved Prakash Mishra, Bhushankumar Narayan Shinde et al. Intelligence-Based Medicine, 2026. Cites: paper

Personalised Drug Recommender Systems based on Electronic Health Records: Reproducibility and External Validity
Archie Carpenter, Dietmar Jannach. ACM Conference on Recommender Systems (RecSys), 2026. Cites: paper

Joint effect of triglyceride-glucose index and low-density lipoprotein cholesterol on mortality and days alive out of hospital in acute stroke: a multi-center machine learning-based cohort study
Wen-Liang Shuai, Li-Xuan Fang, Jia-Jun Qiu et al. Diabetes Research and Clinical Practice, 2026. Cites: paper

Performance evaluation of ARIMA, VAR, ANN, GRU, and LSTM for multivariate healthcare time-series prediction: a rigorous, reproducible benchmarking study with ablation analysis on MIMIC-III and eICU
Md. Tazul Islam, Muhammad Hanif, Samuel Kim. Frontiers in Artificial Intelligence, 2026. Cites: paper

Automated Department Classification of Clinical Discharge Summaries Using Ensemble Transformer and Classical Machine Learning Models: A Cross-Validated Study on MIMIC-III
Shital Sudhakar Wagh. Journal of Intelligent Decision Making and Information Science, 2026. Cites: paper

Do Clinical Notes Improve ICU Mortality Prediction? A Controlled Comparison of Structured and Multimodal EHR Fusion Strategies
Ashish Katyal. Research Square, 2026. Cites: paper

Integração de Sensoriamento e Predição de Risco Clínico em Sistema IoMT
Arianny Leão, Luiz Silva, Lucas Lins et al. 2026. Cites: paper

Leveraging Large Language Models for Temporal PHI De-identification in Real-World Clinical Notes
Xiaomeng Wang, Liwei Wang, Andrew Wen et al. medRxiv, 2026. Cites: paper

RTSANet: learning sequential-attentive hybrid networks for drug information-enhanced medication recommendation
Yuanyuan Zhang, Zhennuo Wang, Shuang Du et al. Computer Methods in Biomechanics & Biomedical Engineering, 2026. Cites: paper

Toward Clinically Interpretable Perioperative Decision Support: Explainable Machine Learning for 30-Day Postoperative Mortality Prediction
Mubashir Farooq, Asif Ali Banka. The American Surgeon, 2026. Cites: paper

From discrete visits to latent health state modeling for medication recommendation
Xiaobo Li, Yijia Zhang. Information Processing & Management, 2026. Cites: paper

From transformer to large language models for automated generation of hospital discharge summaries: a systematic review
Bhuvaneswari Sivagnanam, Saranya Rajiakodi, Rizwan Suliankatchi Abdulkader et al. Network Modeling Analysis in Health Informatics and Bioinformatics, 2026. Cites: paper

Improving Machine Learning and Deep Learning Models for 30-Day ICU Readmission Prediction Using Ensemble Bayesian Model Averaging
Emanuele Koumantakis, Konstantina Remoundou, Carmen Fava et al. Epidemiology Biostatistics and Public Health, 2026. Cites: paper

A Dual-Loop Task-Orthogonal Framework for Sequential Multitask Learning in Echo State Networks
Syeda Shamaila Zareen, Junsong Wang, Hong Wang et al. International Journal of Neural Systems, 2026. Cites: paper

Análise Estatística e Comparativa de Algoritmos de Machine Learning para Predição de Mortalidade em Unidades de Terapia Intensiva
Regisson Cesar Pereira de Aguiar, Roberta Fagundes. Revista de Engenharia e Pesquisa Aplicada, 2026. Cites: paper

Compression-Aware Vital-Sign Anomaly Detection: A Synthetic Data Ablation of Pruning, Quantization, and Knowledge Distillation, With A Protocol for Clinical and Edge-Hardware Extension
Pushpak Basak, Sureeti Sahu. 2026. Cites: paper

Privacy-Preserving NLP for a Low-Resource Language: Benchmarking LLM-Based Personally Identifiable Information Anonymization in Slovene
Nenad Jakovchevski, Matej Martinc. Lecture notes in computer science, 2026. Cites: paper

Break the Glass in OBDA
Divya Baura, Diego Calvanese. Lecture notes in computer science, 2026. Cites: paper

GENESIS-SHIELD: an interpretable ensemble for anomaly detection in CRISPR genomic-workflow security
C Prabakaran, R. Kannadasan. Frontiers in Artificial Intelligence, 2026. Cites: paper

Machine Learning and High-Fidelity Data in Medicine and Surgery
Rohit S. Loomba, Saul Flores, Izzet Turkalp Akbasli et al. IntechOpen eBooks, 2026. Cites: paper

Natural language processing for drug discovery
Pankaj Tyagi, Ankish Arya, Prabhat Tripathi et al. Elsevier eBooks, 2026. Cites: paper

Physiologically-aware data generation: A differentiable HMM and frequency-domain Transformer GAN approach
Arbia Boudaoud, Salheddine Kabou. Biomedical Signal Processing and Control, 2026. Cites: paper

Significance of a Classification Scheme for Assessing Evidence Quality in AI Systems
Silvio Andrae. IGI Global eBooks, 2026. Cites: paper

Unsupervised state-learning for multivariate time series data: a survey and practical guidelines
Phillip Johann Overlöper, C. Coelho, Oliver Niggemann. Artificial Intelligence Review, 2026. Cites: paper

Cue-Based Narrative Defect Detection for Medical Record Quality Control: A Monte Carlo Simulation Study Comparing Cue Rules, TF-IDF Baselines and a Learned Classifier (Preprint)
Xiaoming Xu. 2026. Cites: paper

Deterministic and stochastic interventions in reducing drug–drug interactions in inappropriate prescribing: A systematic review
Muhammad Fahmi Ahmad Zuber, Nur Aishah Che Roos, Ruzanna Mat Jusoh et al. PLoS ONE, 2026. Cites: paper

Disease Spectrum-aware and Time-evolving Dependency Learning for Medication Recommendation
Yishuo Li, Cong Wang, Shoujin Wang et al. ACM Transactions on Information Systems, 2026. Cites: paper

ProMem-agent: Procedural memory-augmented large language model agents for clinical trajectory reasoning
Qianying He, Xuan Liu, Jingquan Liu et al. International Journal of Medical Informatics, 2026. Cites: paper

Responsible AI for Acute Stroke Management
Joanna Lin, Mumu Aktar, Hakim Baazaoui et al. Stroke, 2026. Cites: paper

Non‐Contact Photoplethysmography for In‐Vehicle Health Monitoring With Seamlessly Integrated Photodetector Array and Hardware‐Accelerated AI
Yaqi Zhao, Haolan Xu, Xin Wang et al. Small, 2026. Cites: paper

From the Sophimatics Framework to a Complex-Time Multi-Agent System for Neural–Symbolic Cognitive Analysis
Gerardo Iovane, Carmine Ziccardi, Alessio Rosati et al. Information, 2026. Cites: paper

LLM-CSER: Large language model-driven causal reasoning with synergistic experts for medication recommendation
Yan Kang, Xueqing Luo, Hanyuan Wang et al. Expert Systems with Applications, 2026. Cites: paper

A Deep Reinforcement Learning-Based Adaptive Model for Sepsis Treatment in ICU
DEEPAK YADAV, Millie Pant, Kusum Deep. Lecture notes in computer science, 2026. Cites: paper

Uncertainty-quantified time–frequency neural operator (UQ-TF-NO) for discretization-invariant heart failure risk prediction from ECG signals
Victor Adeyi Odeh, Zhang XiaoLing, Clement Agaba et al. Applied Soft Computing, 2026. Cites: paper

Early recognition of sepsis-associated acute kidney injury based on BioBERT-BPNN multimodal clinical data analysis
Yufeng Chen, Hongyang Bian, Yuye Li. PLoS ONE, 2026. Cites: paper

Explainable machine learning for breast cancer prediction in resource-constrained settings: A multi-algorithmic framework integrating shap-based transparency with clinical decision support
Oluwaseun Adebayo Bamodu, Sumaiya Nezam, Chen‐Chih Chung. PLOS Digital Health, 2026. Cites: paper

Identifying cohorts at elevated risk of cancers using generative modeling of patient health states
Asif Khan, Duncan T. Forster, Moshir Harsh et al. medRxiv, 2026. Cites: paper

Pre-operative albumin outperforms NHANES-derived composite nutritional-immune-inflammatory indices for predicting adverse outcomes in pediatric congenital heart surgery: a single-center study with internal validation
Xin Chai, Liangping Cheng. Research Square, 2026. Cites: paper

Calibration-Based Cuffless Blood Pressure Estimation Using a Dilated-Residual Attention U-Net
Thomas Stogiannopoulos, Nikolaos Mitianoudis. Information, 2026. Cites: paper

CDTS2: Causal Downstreamer with Causally Disentangled Trend and Seasonality Time-Series Representations
Juhyun Lyu, Junghee Kim, Sangmin Lee et al. Applied Sciences, 2026. Cites: paper

Evaluating the generalisability of LiSep LSTM for early prediction of septic shock across US and european cohorts
Hong K. Tan, Logan Froese, Daniel Wilhelms et al. Scientific Reports, 2026. Cites: paper

Vascular waveform analysis using Bayesian pulse deconvolution
Parker S. Ruth, Tommy DeBenedetti, Lily O'Brien et al. npj Digital Medicine, 2026. Cites: paper

АЛГОРИТМІЧНА КОРЕКЦІЯ «ЕФЕКТУ БАТЧУ» В ETL-КОНВЕЄРІ ІНТЕЛЕКТУАЛЬНОЇ ПЛАТФОРМИ ОПРАЦЮВАННЯ ГЕТЕРОГЕННИХ БІОМЕДИЧНИХ ДАНИХ
Вадим Анатолійович Мацієвський, Тетяна Миколаївна Нікітчук. Measuring and computing devices in technological processes, 2026. Cites: paper

A multi-scale hypergraph approach of interpretable probabilistic forecasting for irregular time series
Jiahui Yan, Yaling Xun, Haifeng Yang et al. Expert Systems with Applications, 2026. Cites: paper

MedFuseNet: A cross-modality attention network for predicting emergencies in smart hospital beds using fog computing
Jones Daniel, Sundar Rajan R. Franklin Open, 2026. Cites: paper

MMAC-Net: A Multi-Modal Multi-Label Attention-Based Deep Learning Approach for Automated ICD-9 Coding of Rare Disease Admissions from Electronic Health Records
Adnan Ferdous Ashrafi, Reda Alhajj, Jon George Rokne. Applied Sciences, 2026. Cites: paper

Numeric versus embedding pipelines for optimized clinical risk prediction
Aaron Ge, Jialong Wu, Xueyao Wu et al. JAMIA Open, 2026. Cites: paper

Query-CNAT: Uma Ferramenta de Busca Semântica Híbrida para Bancos de Dados Relacionais Médicos
Denilson José do Bom Jesus Silva de Lima, Rui Nóbrega de Pontes Filho, Allan Miller Silva Lima et al. Simpósio Brasileiro de Bancos de Dados (SBBD), 2026. Cites: paper

AI-assisted multimodal data integration for precision oncology
Alexandra Chera, Ana-Maria Chirilaș, Amada El-Sabeh et al. Frontiers in Artificial Intelligence, 2026. Cites: paper

Cited by