Use of deep learning to develop continuous-risk models for adverse event prediction from electronic health records

Early prediction of circulatory failure in the intensive care unit using machine learning

(2020) Stephanie L. Hyland et al.   NATURE MEDICINE

Calculating the sample size required for developing a clinical prediction model

(2020) Richard D Riley et al.   BMJ-British Medical Journal

Developing specific reporting guidelines for diagnostic accuracy studies assessing AI interventions: The STARD-AI Steering Group

(2020) Viknesh Sounderajah et al.   NATURE MEDICINE

Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension

(2020) Xiaoxuan Liu et al.   NATURE MEDICINE

Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extension

(2020) Samantha Cruz Rivera et al.   NATURE MEDICINE

DeepSOFA: A Continuous Acuity Score for Critically Ill Patients using Clinically Interpretable Deep Learning

(2019) Benjamin Shickel et al.   Scientific Reports

Reporting of artificial intelligence prediction models

(2019) Gary S Collins et al.   LANCET

How to develop machine learning models for healthcare

(2019) Po-Hsuan Cameron Chen et al.   NATURE MATERIALS

A clinically applicable approach to continuous prediction of future acute kidney injury

(2019) Nenad Tomašev et al.   NATURE

Combining patient visual timelines with deep learning to predict mortality

(2019) Anoop Mayampurath et al.   PLoS One

Multitask learning and benchmarking with clinical time series data

(2019) Hrayr Harutyunyan et al.   Scientific Data

Deep-learning model for predicting 30-day postoperative mortality

(2019) Bradley A. Fritz et al.   BRITISH JOURNAL OF ANAESTHESIA

Do no harm: a roadmap for responsible machine learning for health care

(2019) Jenna Wiens et al.   NATURE MEDICINE

Key challenges for delivering clinical impact with artificial intelligence

(2019) Christopher J. Kelly et al.   BMC Medicine

A Long Short-Term Memory Ensemble Approach for Improving the Outcome Prediction in Intensive Care Unit

(2019) Jing Xia et al.   Computational and Mathematical Methods in Medicine

How to Read Articles That Use Machine Learning

(2019) Yun Liu et al.   JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION

ISeeU: Visually interpretable deep learning for mortality prediction inside the ICU

(2019) William Caicedo-Torres et al.   JOURNAL OF BIOMEDICAL INFORMATICS

LiSep LSTM: A Machine Learning Algorithm for Early Detection of Septic Shock

(2019) Josef Fagerström et al.   Scientific Reports

Dynamic-DeepHit: A Deep Learning Approach for Dynamic Survival Analysis With Competing Risks Based on Longitudinal Data

(2019) Changhee Lee et al.   IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING

A Comparative Analysis of Sepsis Identification Methods in an Electronic Database*

(2018) Alistair E. W. Johnson et al.   CRITICAL CARE MEDICINE

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

(2018) Shamim Nemati et al.   CRITICAL CARE MEDICINE

Benchmarking deep learning models on large healthcare datasets

(2018) Sanjay Purushotham et al.   JOURNAL OF BIOMEDICAL INFORMATICS

Opportunities and challenges in developing deep learning models using electronic health records data: a systematic review

(2018) Cao Xiao et al.   JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION

Recurrent Neural Networks for Multivariate Time Series with Missing Values

(2018) Zhengping Che et al.   Scientific Reports

Clinically applicable deep learning for diagnosis and referral in retinal disease

(2018) Jeffrey De Fauw et al.   NATURE MEDICINE

Ensuring Fairness in Machine Learning to Advance Health Equity

(2018) Alvin Rajkomar et al.   ANNALS OF INTERNAL MEDICINE

Improving palliative care with deep learning

(2018) Anand Avati et al.   BMC Medical Informatics and Decision Making

A guide to deep learning in healthcare

(2018) Andre Esteva et al.   NATURE MEDICINE

Creating an automated trigger for sepsis clinical decision support at emergency department triage using machine learning

(2017) Steven Horng et al.   PLoS One

Predicting all-cause risk of 30-day hospital readmission using artificial neural networks

(2017) Mehdi Jamei et al.   PLoS One

Hybrid computing using a neural network with dynamic external memory

(2016) Alex Graves et al.   NATURE

Accuracy and Calibration of Computational Approaches for Inpatient Mortality Predictive Modeling

(2016) Christos T. Nakas et al.   PLoS One

MIMIC-III, a freely accessible critical care database

(2016) Alistair E.W. Johnson et al.   Scientific Data

Deep Patient: An Unsupervised Representation to Predict the Future of Patients from the Electronic Health Records

(2016) Riccardo Miotto et al.   Scientific Reports

Real-time prediction of inpatient length of stay for discharge prioritization

(2015) Sean Barnes et al.   JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION

A targeted real-time early warning score (TREWScore) for septic shock

(2015) Katharine E. Henry et al.   Science Translational Medicine

The Precision-Recall Plot Is More Informative than the ROC Plot When Evaluating Binary Classifiers on Imbalanced Datasets

(2015) Takaya Saito et al.   PLoS One

Clinical Decision Support for Early Recognition of Sepsis

(2014) Robert C. Amland et al.   AMERICAN JOURNAL OF MEDICAL QUALITY

Big Data In Health Care: Using Analytics To Identify And Manage High-Risk And High-Cost Patients

(2014) David W. Bates et al.   HEALTH AFFAIRS

Comparison of Regression Methods for Modeling Intensive Care Length of Stay

(2014) Ilona W. M. Verburg et al.   PLoS One

Derivation and validation of an index to predict early death or unplanned readmission after discharge from hospital to the community

(2010) C. van Walraven et al.   CANADIAN MEDICAL ASSOCIATION JOURNAL