Patient Outcome Prediction

Patient outcome prediction aims to forecast patient health trajectories using clinical data, improving healthcare decision-making and resource allocation. Current research heavily utilizes machine learning, employing diverse architectures like convolutional neural networks for image analysis, recurrent neural networks for time-series data, and graph neural networks to capture complex relationships between patient characteristics and outcomes. These models are increasingly incorporating multimodal data (e.g., imaging, genomics, clinical notes) and leveraging techniques like pre-training and data augmentation to enhance predictive accuracy and generalizability. Improved prediction accuracy has demonstrably led to better patient care, including reduced hospital stays and readmissions, highlighting the significant impact of this field on both clinical practice and healthcare systems.

Papers

October 29, 2024

Peri-AIIMS: Perioperative Artificial Intelligence Driven Integrated Modeling of Surgeries using Anesthetic, Physical and Cognitive Statuses for Predicting Hospital Outcomes
Sabyasachi Bandyopadhyay, Jiaqing Zhang, Ronald L. Ison, David J. Libon, Patrick Tighe, Catherine Price, Parisa Rashidi
Cognitive Impairment Open Surgery Patient Outcome Prediction Postoperative Complication

August 5, 2024

Machine Learning Applications in Medical Prognostics: A Comprehensive Review
Michael Fascia
Machine Learning Comprehensive Review Machine Learning Application Disease Prediction Sepsis Prediction Patient Outcome Prediction

August 24, 2023

Hypergraph Convolutional Networks for Fine-grained ICU Patient Similarity Analysis and Risk Prediction
Yuxi Liu, Zhenhao Zhang, Shaowen Qin, Flora D. Salim, Antonio Jimeno Yepes, Jun Shen, Jiang Bian
Fine Grained Risk Prediction Hypergraph Convolutional Network Patient Outcome Prediction Mortality Prediction Model

May 31, 2023

Diagnosis and Prognosis of Head and Neck Cancer Patients using Artificial Intelligence
Ikboljon Sobirov
Artificial Intelligence Tumor Segmentation Medical Diagnosis Human Head Prognosis Prediction Prognostic Model Neck Cancer Patient Outcome Prediction

May 25, 2023

Patient Outcome Predictions Improve Operations at a Large Hospital Network
Liangyuan Na, Kimberly Villalobos Carballo, Jean Pauphilet, Ali Haddad-Sisakht, Daniel Kombert, Melissa Boisjoli-Langlois, Andrew Castiglione, Maram Khalifa, Pooja Hebbal, Barry Stein, Dimitris Bertsimas
Economic Operation Discharge Summary Patient Outcome Prediction Patient Level Prediction

May 20, 2023

MediTab: Scaling Medical Tabular Data Predictors via Data Consolidation, Enrichment, and Refinement
Zifeng Wang, Chufan Gao, Cao Xiao, Jimeng Sun
Tabular Data Tabular Prediction Content Enrichment Patient Outcome Prediction Health Risk Prediction Mindfulness Meditation Text Consolidation

March 16, 2023

A Novel Autoencoders-LSTM Model for Stroke Outcome Prediction using Multimodal MRI Data
Nima Hatami, Laura Mechtouff, David Rousseau, Tae-Hee Cho, Omer Eker, Yves Berthezene, Carole Frindel
Long Short Term Memory Stroke Prediction Patient Outcome Prediction

December 22, 2022

Enhancing the prediction of disease outcomes using electronic health records and pretrained deep learning models
Zhichao Yang, Weisong Liu, Dan Berlowitz, Hong Yu
Deep Learning Model Human Prediction Electronic Health Record Sequence to Sequence Prognostic Prediction Health Outcome Clinical Outcome Patient Outcome Prediction

November 13, 2022

Textual Data Augmentation for Patient Outcomes Prediction
Qiuhao Lu, Dejing Dou, Thien Huu Nguyen
Data Augmentation Patient Outcome Prediction Text Data Augmentation Synthetic Clinical Note

October 25, 2022

Fusing Modalities by Multiplexed Graph Neural Networks for Outcome Prediction in Tuberculosis
Niharika S. D'Souza, Hongzhi Wang, Andrea Giovannini, Antonio Foncubierta-Rodriguez, Kristen L. Beck, Orest Boyko, Tanveer Syeda-Mahmood
Graph Neural Network Multi Modality Different Modality Outcome Prediction Tuberculosis Treatment Patient Outcome Prediction Multiplex Graph

July 21, 2022

Unsupervised pre-training of graph transformers on patient population graphs
Chantal Pellegrini, Nassir Navab, Anees Kazi
Pre Training Graph Transformer Unsupervised Pre Training Heterogeneous Clinical Patient Outcome Prediction Population Graph

March 23, 2022

Unsupervised Pre-Training on Patient Population Graphs for Patient-Level Predictions
Chantal Pellegrini, Anees Kazi, Nassir Navab
Pre Training Graph Transformer Unsupervised Pre Training Patient Outcome Prediction Population Graph Patient Level Prediction

November 16, 2021

Literature-Augmented Clinical Outcome Prediction
Aakanksha Naik, Sravanthi Parasa, Sergey Feldman, Lucy Lu Wang, Tom Hope
Clinical Note Clinical Text Patient Outcome Prediction Clinical Outcome Prediction

Patient Outcome Prediction

Papers

Peri-AIIMS: Perioperative Artificial Intelligence Driven Integrated Modeling of Surgeries using Anesthetic, Physical and Cognitive Statuses for Predicting Hospital Outcomes

Machine Learning Applications in Medical Prognostics: A Comprehensive Review

Hypergraph Convolutional Networks for Fine-grained ICU Patient Similarity Analysis and Risk Prediction

Diagnosis and Prognosis of Head and Neck Cancer Patients using Artificial Intelligence

Patient Outcome Predictions Improve Operations at a Large Hospital Network

MediTab: Scaling Medical Tabular Data Predictors via Data Consolidation, Enrichment, and Refinement

A Novel Autoencoders-LSTM Model for Stroke Outcome Prediction using Multimodal MRI Data

Enhancing the prediction of disease outcomes using electronic health records and pretrained deep learning models

Textual Data Augmentation for Patient Outcomes Prediction

Fusing Modalities by Multiplexed Graph Neural Networks for Outcome Prediction in Tuberculosis

Unsupervised pre-training of graph transformers on patient population graphs

Unsupervised Pre-Training on Patient Population Graphs for Patient-Level Predictions

Literature-Augmented Clinical Outcome Prediction