Hospital Length of Stay Prediction Based on Multi-modal Data towards Trustworthy Human-AI Collaboration in Radiomics

03/17/2023
by   Hubert Baniecki, et al.
0

To what extent can the patient's length of stay in a hospital be predicted using only an X-ray image? We answer this question by comparing the performance of machine learning survival models on a novel multi-modal dataset created from 1235 images with textual radiology reports annotated by humans. Although black-box models predict better on average than interpretable ones, like Cox proportional hazards, they are not inherently understandable. To overcome this trust issue, we introduce time-dependent model explanations into the human-AI decision making process. Explaining models built on both: human-annotated and algorithm-extracted radiomics features provides valuable insights for physicians working in a hospital. We believe the presented approach to be general and widely applicable to other time-to-event medical use cases. For reproducibility, we open-source code and the TLOS dataset at https://github.com/mi2datalab/xlungs-trustworthy-los-prediction.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
08/23/2022

SurvSHAP(t): Time-dependent explanations of machine learning survival models

Machine and deep learning survival models demonstrate similar or even im...
research
06/15/2023

Med-MMHL: A Multi-Modal Dataset for Detecting Human- and LLM-Generated Misinformation in the Medical Domain

The pervasive influence of misinformation has far-reaching and detriment...
research
07/10/2023

Multi-modal Graph Learning over UMLS Knowledge Graphs

Clinicians are increasingly looking towards machine learning to gain ins...
research
09/01/2021

Developing and validating multi-modal models for mortality prediction in COVID-19 patients: a multi-center retrospective study

The unprecedented global crisis brought about by the COVID-19 pandemic h...
research
03/11/2022

REX: Reasoning-aware and Grounded Explanation

Effectiveness and interpretability are two essential properties for trus...
research
07/14/2022

MedFuse: Multi-modal fusion with clinical time-series data and chest X-ray images

Multi-modal fusion approaches aim to integrate information from differen...
research
08/26/2021

Network Module Detection from Multi-Modal Node Features with a Greedy Decision Forest for Actionable Explainable AI

Network-based algorithms are used in most domains of research and indust...

Please sign up or login with your details

Forgot password? Click here to reset