Evidence

Inpatient Predictive Analytics

Septic Shock / Sepsis

Publication

Development and prospective implementation of a large language model based system for early sepsis prediction

Publication

Prediction of Readmission Following Sepsis Using Social Determinants of Health

Publication

The impact of laboratory data missingness on sepsis diagnosis timelines

Publication

Impact of a deep learning sepsis prediction model on quality of care and survival

Publication

Bringing the Promise of Artificial Intelligence to Critical Care: What the Experience With Sepsis Analytics Can Teach Us

Publication

DeepAISE – An interpretable and recurrent neural survival model for early prediction of sepsis

Publication

An Interpretable Machine Learning Model for Accurate Prediction of Sepsis in the ICU

Publication

Representation Learning and Spectral Clustering for the Development and External Validation of Dynamic Sepsis Phenotypes: Observational Cohort Study

Publication

Optimizing the Implementation of Clinical Predictive Models to Minimize National Costs: Sepsis Case Study

Publication

Inclusion of social determinants of health improves sepsis readmission prediction models

Publication

Early sepsis detection in critical care patients using multiscale blood pressure and heart rate dynamics

Publication

Multiscale network representation of physiological time series for early prediction of sepsis

Publication

Looking Into the Seeds of Time to Say Which Fevers Will Grow and Which Will Not

Publication

A FHIR-Enabled Streaming Sepsis Prediction System for ICUs

Publication

Early Prediction of Sepsis From Clinical Data: The PhysioNet/Computing in Cardiology Challenge 2019

Publication

AIDEx – An Open-source Platform for Real-Time Forecasting Sepsis and A Case Study on Taking ML Algorithms to Production

Publication

Contextual Embeddings from Clinical Notes Improves Prediction of Sepsis

Publication

A Locally Optimized Data-Driven Tool to Predict Sepsis-Associated Vasopressor Use in the ICU

Publication

Differentiation of Fungal, Viral, and Bacterial Sepsis using Multimodal Deep Learning

Publication

Challenges Facing Developers of Diagnostic Tests for Sepsis: A Report From Sepsis Alliance and the Infection Management and Sepsis Collaborative Community

Publication

A Prospective Comparison of Large Language Models for Early Prediction of Sepsis

Publication

The Effect of Severe Sepsis and Septic Shock Management Bundle (SEP-1) Compliance and Implementation on Mortality Among Patients With Sepsis: A Systematic Review

Publication

Quantifying Healthcare Provider Perceptions of a Novel Deep Learning Algorithm to Predict Sepsis: Electronic Survey

Publication

Mortality and antibiotic timing in deep learning-derived surviving sepsis campaign risk groups: a multicenter study

Publication

Rethinking sepsis prediction in the era of large language models

Publication

Dynamic sepsis endotypes: instability or expected signal of biological progression?

Publication

Operationalizing Sepsis Definitions With Artificial Intelligence: Toward Smarter Antibiotic Use

Publication

Integrating Precision Sepsis Risk Stratification Into Systems-Based Antimicrobial Stewardship

Publication

Improving sepsis best practice utility and clinical acceptance using an LLM-enhanced prediction system

Show More Research Areas ->

General Deterioration / Early Warning / Critical Illness Outcomes

Publication

Development and Validation of a Deep Learning Model for Prediction of Adult Physiological Deterioration

Publication

Serial Daily Organ Failure Assessment Beyond ICU Day 5 Does Not Independently Add Precision to ICU Risk-of-Death Prediction

Publication

Assessing Contribution of Higher Order Clinical Risk Factors to Prediction of Outcome in Aneurysmal Subarachnoid Hemorrhage Patients

Publication

DETERIO-LLM: enhancing traditional deterioration risk scores with clinical context and advanced reasoning

Respiratory Failure / Mechanical Ventilation

Publication

Development and Prospective Validation of a Deep Learning Algorithm for Predicting Need for Mechanical Ventilation

Publication

Prediction of Acute Respiratory Failure Requiring Advanced Respiratory Support in Advance of Interventions and Treatment: A Multivariable Prediction Model From Electronic Medical Record Data

Publication

Improving Prediction of Need for Mechanical Ventilation using Cross-Attention

Publication

Development, deployment, and continuous monitoring of a machine learning model to predict respiratory failure in critically ill patients

Publication

Can we predict the future of respiratory failure prediction?

Publication

Enhancing predictive modeling for respiratory support with LLM-driven guideline adherence

Publication

Comparing high-flow nasal cannula and non-invasive ventilation in critical care: insights from deep counterfactual inference

Publication

Physician Gestalt Compared With Artificial Intelligence Model to Predict Intubation in Critically Ill Patients

Publication

Deep learning for time-series segmentation of mechanical ventilator waveforms

Infection Detection (Non-Sepsis-Specific)

Publication

Predicting Mortality in Critical Care Patients with Fungemia Using Structured and Unstructured Data

Publication

Predicting presumed serious infection among hospitalized children on central venous lines with machine learning

Publication

Deep Learning Model to Predict Serious Infection Among Children With Central Venous Lines

Publication

LLM-Powered Automated Infection Detection in Cirrhosis: Achieving Expert-Level Accuracy from Clinical Documents

Publication

Achieving Expert-Level Clinical Infection Detection with LLMs from Clinical Documents: Validation in Complex Patient Cases with Cirrhosis

Precision Dosing / Pharmacokinetics

Publication

Optimal medication dosing from suboptimal clinical examples: a deep reinforcement learning approach

Publication

A Deep Deterministic Policy Gradient Approach to Medication Dosing and Surveillance in the ICU

Publication

AI-Driven Tacrolimus Dosing in Transplant Care: Cohort Study

Pediatric Inflammatory Disease (Kawasaki Disease / MIS-C)

Publication

A machine-learning algorithm for diagnosis of multisystem inflammatory syndrome in children and Kawasaki disease in the USA: a retrospective model development and validation study

Publication

A deep convolutional neural network for Kawasaki disease diagnosis

Publication

Implementation of KIDMATCH: A Clinical Decision Support Tool for Diagnosing Pediatric Patients with Multisystem Inflammatory Syndrome and Kawasaki Disease

Publication

A Deep Learning Framework for Image-Based Screening of Kawasaki Disease

Publication

Intravenous immunoglobulin resistance in Kawasaki disease patients: prediction using clinical data

Publication

Validation of Kawasaki MATCH on a Latin American cohort: application to the REKAMLATINA network

Platform Infrastructure & Data Ingestion

Publication

Leveraging clinical data across healthcare institutions for continual learning of predictive risk models

Publication

Unsupervised Detection and Correction of Model Calibration Shift at Test-Time

Publication

Assessing Barriers to Implementation of Machine Learning and Artificial Intelligence-Based Tools in Critical Care: Web-Based Survey Study

Publication

Development & Deployment of a Real-time Healthcare Predictive Analytics Platform

Acute Kidney Injury / Renal / CKD

Publication

It Is About Time: Extinguishing the Fire of Acute Kidney Injury

Publication

Development and validation of a deep learning algorithm for the prediction of serum creatinine in critically ill patients

Publication

Machine Learning-Predicted Risk Trajectories for Incident Chronic Kidney Disease and Associations with Post-CKD Outcomes

Publication

Temporal Recurrent Neural Networks for Predicting Acute Kidney Injury Recovery by Time of Discharge

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Peer-Reviewed Evidence

Inpatient Predictive Analytics

Septic Shock / Sepsis

Development and prospective implementation of a large language model based system for early sepsis prediction

Prediction of Readmission Following Sepsis Using Social Determinants of Health

The impact of laboratory data missingness on sepsis diagnosis timelines

Impact of a deep learning sepsis prediction model on quality of care and survival

Bringing the Promise of Artificial Intelligence to Critical Care: What the Experience With Sepsis Analytics Can Teach Us

DeepAISE – An interpretable and recurrent neural survival model for early prediction of sepsis

An Interpretable Machine Learning Model for Accurate Prediction of Sepsis in the ICU

Representation Learning and Spectral Clustering for the Development and External Validation of Dynamic Sepsis Phenotypes: Observational Cohort Study

Optimizing the Implementation of Clinical Predictive Models to Minimize National Costs: Sepsis Case Study

Inclusion of social determinants of health improves sepsis readmission prediction models

Early sepsis detection in critical care patients using multiscale blood pressure and heart rate dynamics

Multiscale network representation of physiological time series for early prediction of sepsis

Looking Into the Seeds of Time to Say Which Fevers Will Grow and Which Will Not

A FHIR-Enabled Streaming Sepsis Prediction System for ICUs

Early Prediction of Sepsis From Clinical Data: The PhysioNet/Computing in Cardiology Challenge 2019

AIDEx – An Open-source Platform for Real-Time Forecasting Sepsis and A Case Study on Taking ML Algorithms to Production

Contextual Embeddings from Clinical Notes Improves Prediction of Sepsis

A Locally Optimized Data-Driven Tool to Predict Sepsis-Associated Vasopressor Use in the ICU

Differentiation of Fungal, Viral, and Bacterial Sepsis using Multimodal Deep Learning

Challenges Facing Developers of Diagnostic Tests for Sepsis: A Report From Sepsis Alliance and the Infection Management and Sepsis Collaborative Community

A Prospective Comparison of Large Language Models for Early Prediction of Sepsis

The Effect of Severe Sepsis and Septic Shock Management Bundle (SEP-1) Compliance and Implementation on Mortality Among Patients With Sepsis: A Systematic Review

Quantifying Healthcare Provider Perceptions of a Novel Deep Learning Algorithm to Predict Sepsis: Electronic Survey

Mortality and antibiotic timing in deep learning-derived surviving sepsis campaign risk groups: a multicenter study

Rethinking sepsis prediction in the era of large language models

Dynamic sepsis endotypes: instability or expected signal of biological progression?

Operationalizing Sepsis Definitions With Artificial Intelligence: Toward Smarter Antibiotic Use

Integrating Precision Sepsis Risk Stratification Into Systems-Based Antimicrobial Stewardship

Improving sepsis best practice utility and clinical acceptance using an LLM-enhanced prediction system

General Deterioration / Early Warning / Critical Illness Outcomes

Development and Validation of a Deep Learning Model for Prediction of Adult Physiological Deterioration

Serial Daily Organ Failure Assessment Beyond ICU Day 5 Does Not Independently Add Precision to ICU Risk-of-Death Prediction

Assessing Contribution of Higher Order Clinical Risk Factors to Prediction of Outcome in Aneurysmal Subarachnoid Hemorrhage Patients

DETERIO-LLM: enhancing traditional deterioration risk scores with clinical context and advanced reasoning

Respiratory Failure / Mechanical Ventilation

Development and Prospective Validation of a Deep Learning Algorithm for Predicting Need for Mechanical Ventilation

Prediction of Acute Respiratory Failure Requiring Advanced Respiratory Support in Advance of Interventions and Treatment: A Multivariable Prediction Model From Electronic Medical Record Data

Improving Prediction of Need for Mechanical Ventilation using Cross-Attention

Development, deployment, and continuous monitoring of a machine learning model to predict respiratory failure in critically ill patients

Can we predict the future of respiratory failure prediction?

Enhancing predictive modeling for respiratory support with LLM-driven guideline adherence

Comparing high-flow nasal cannula and non-invasive ventilation in critical care: insights from deep counterfactual inference

Physician Gestalt Compared With Artificial Intelligence Model to Predict Intubation in Critically Ill Patients

Deep learning for time-series segmentation of mechanical ventilator waveforms

Infection Detection (Non-Sepsis-Specific)

Predicting Mortality in Critical Care Patients with Fungemia Using Structured and Unstructured Data

Predicting presumed serious infection among hospitalized children on central venous lines with machine learning

Deep Learning Model to Predict Serious Infection Among Children With Central Venous Lines

LLM-Powered Automated Infection Detection in Cirrhosis: Achieving Expert-Level Accuracy from Clinical Documents

Achieving Expert-Level Clinical Infection Detection with LLMs from Clinical Documents: Validation in Complex Patient Cases with Cirrhosis

Precision Dosing / Pharmacokinetics

Optimal medication dosing from suboptimal clinical examples: a deep reinforcement learning approach

A Deep Deterministic Policy Gradient Approach to Medication Dosing and Surveillance in the ICU

AI-Driven Tacrolimus Dosing in Transplant Care: Cohort Study

Pediatric Inflammatory Disease (Kawasaki Disease / MIS-C)

A machine-learning algorithm for diagnosis of multisystem inflammatory syndrome in children and Kawasaki disease in the USA: a retrospective model development and validation study

A deep convolutional neural network for Kawasaki disease diagnosis

Implementation of KIDMATCH: A Clinical Decision Support Tool for Diagnosing Pediatric Patients with Multisystem Inflammatory Syndrome and Kawasaki Disease

A Deep Learning Framework for Image-Based Screening of Kawasaki Disease

Intravenous immunoglobulin resistance in Kawasaki disease patients: prediction using clinical data

Validation of Kawasaki MATCH on a Latin American cohort: application to the REKAMLATINA network

Platform Infrastructure & Data Ingestion

Leveraging clinical data across healthcare institutions for continual learning of predictive risk models

Unsupervised Detection and Correction of Model Calibration Shift at Test-Time

Assessing Barriers to Implementation of Machine Learning and Artificial Intelligence-Based Tools in Critical Care: Web-Based Survey Study

Development & Deployment of a Real-time Healthcare Predictive Analytics Platform

Acute Kidney Injury / Renal / CKD

It Is About Time: Extinguishing the Fire of Acute Kidney Injury

Development and validation of a deep learning algorithm for the prediction of serum creatinine in critically ill patients

Machine Learning-Predicted Risk Trajectories for Incident Chronic Kidney Disease and Associations with Post-CKD Outcomes

Temporal Recurrent Neural Networks for Predicting Acute Kidney Injury Recovery by Time of Discharge

Automated Quality Metric Abstraction & Reporting

Medical Record Abstraction for Quality Improvement in Sepsis Care Using Artificial Intelligence

Large Language Models for More Efficient Reporting of Hospital Quality Measures

Large Language Models for Summarizing Advance Care Planning Information From Goals of Care Notes in the EHR

Outpatient Multimodal Data Analysis from Smart Devices

Impact of wearable device data and multi-scale entropy analysis on improving hospital readmission prediction