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No Black Box Anymore: Demystifying Clinical Predictive Modeling with Temporal-Feature Cross Attention Mechanism
v1v2 (latest)

No Black Box Anymore: Demystifying Clinical Predictive Modeling with Temporal-Feature Cross Attention Mechanism

25 March 2025
Yubo Li
Xinyu Yao
R. Padman
    FAttAI4TS
ArXiv (abs)PDFHTML

Papers citing "No Black Box Anymore: Demystifying Clinical Predictive Modeling with Temporal-Feature Cross Attention Mechanism"

13 / 13 papers shown
Title
Enhancing End Stage Renal Disease Outcome Prediction: A Multi-Sourced Data-Driven Approach
Enhancing End Stage Renal Disease Outcome Prediction: A Multi-Sourced Data-Driven Approach
Yubo Li
R. Padman
116
2
0
02 Oct 2024
Towards Interpretable End-Stage Renal Disease (ESRD) Prediction:
  Utilizing Administrative Claims Data with Explainable AI Techniques
Towards Interpretable End-Stage Renal Disease (ESRD) Prediction: Utilizing Administrative Claims Data with Explainable AI Techniques
Yubo Li
Saba A. Al-Sayouri
R. Padman
70
2
0
18 Sep 2024
Does the Whole Exceed its Parts? The Effect of AI Explanations on
  Complementary Team Performance
Does the Whole Exceed its Parts? The Effect of AI Explanations on Complementary Team Performance
Gagan Bansal
Tongshuang Wu
Joyce Zhou
Raymond Fok
Besmira Nushi
Ece Kamar
Marco Tulio Ribeiro
Daniel S. Weld
144
607
0
26 Jun 2020
What Clinicians Want: Contextualizing Explainable Machine Learning for
  Clinical End Use
What Clinicians Want: Contextualizing Explainable Machine Learning for Clinical End Use
S. Tonekaboni
Shalmali Joshi
M. Mccradden
Anna Goldenberg
100
403
0
13 May 2019
MiME: Multilevel Medical Embedding of Electronic Health Records for
  Predictive Healthcare
MiME: Multilevel Medical Embedding of Electronic Health Records for Predictive Healthcare
Edward Choi
Cao Xiao
Walter F. Stewart
Jimeng Sun
158
237
0
22 Oct 2018
Scalable and accurate deep learning for electronic health records
Scalable and accurate deep learning for electronic health records
A. Rajkomar
Eyal Oren
Kai Chen
Andrew M. Dai
Nissan Hajaj
...
A. Butte
M. Howell
Claire Cui
Greg S. Corrado
Jeffrey Dean
OODBDL
203
2,163
0
24 Jan 2018
Attend and Diagnose: Clinical Time Series Analysis using Attention
  Models
Attend and Diagnose: Clinical Time Series Analysis using Attention Models
Huan-Zhi Song
Deepta Rajan
Jayaraman J. Thiagarajan
A. Spanias
MLAU
112
456
0
10 Nov 2017
Dipole: Diagnosis Prediction in Healthcare via Attention-based
  Bidirectional Recurrent Neural Networks
Dipole: Diagnosis Prediction in Healthcare via Attention-based Bidirectional Recurrent Neural Networks
Fenglong Ma
Radha Chitta
Jing Zhou
Quanzeng You
Tong Sun
Jing Gao
74
559
0
19 Jun 2017
Attention Is All You Need
Attention Is All You Need
Ashish Vaswani
Noam M. Shazeer
Niki Parmar
Jakob Uszkoreit
Llion Jones
Aidan Gomez
Lukasz Kaiser
Illia Polosukhin
3DV
986
133,557
0
12 Jun 2017
A Unified Approach to Interpreting Model Predictions
A Unified Approach to Interpreting Model Predictions
Scott M. Lundberg
Su-In Lee
FAtt
1.3K
22,379
0
22 May 2017
GRAM: Graph-based Attention Model for Healthcare Representation Learning
GRAM: Graph-based Attention Model for Healthcare Representation Learning
Edward Choi
M. T. Bahadori
Le Song
Walter F. Stewart
Jimeng Sun
GNN
97
678
0
21 Nov 2016
RETAIN: An Interpretable Predictive Model for Healthcare using Reverse
  Time Attention Mechanism
RETAIN: An Interpretable Predictive Model for Healthcare using Reverse Time Attention Mechanism
Edward Choi
M. T. Bahadori
Joshua A. Kulas
A. Schuetz
Walter F. Stewart
Jimeng Sun
AI4TS
135
1,254
0
19 Aug 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
Marco Tulio Ribeiro
Sameer Singh
Carlos Guestrin
FAttFaML
1.3K
17,237
0
16 Feb 2016
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