Mattias Ohlsson
- Computational Biology and Biological Physics - Has been reorganised
- Department of Astronomy and Theoretical Physics - Has been reorganised
- Artificial Intelligence in CardioThoracic Sciences (AICTS)
- eSSENCE: The e-Science Collaboration
- Faculty Office
- LU Profile Area: Natural and Artificial Cognition
- Centre for Environmental and Climate Science (CEC)
- Computational Science for Health and Environment
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- 2024
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Mark
Prior electrocardiograms not useful for machine learning predictions of major adverse cardiac events in emergency department chest pain patients
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- Contribution to journal › Article
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Mark
Retrospective validation study of an artificial neural network-based preoperative decision-support tool for noninvasive lymph node staging (NILS) in women with primary breast cancer (ISRCTN14341750)
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- Contribution to journal › Article
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Mark
The Concordance Index decomposition : A measure for a deeper understanding of survival prediction models
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- Contribution to journal › Article
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Mark
How does an AI diagnose dyspnoea in ED triage without human guidance?
2024) Swedish Emergency Medicine Talks - SWEETS24(
- Contribution to conference › Poster
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Mark
The skåne emergency medicine (SEM) cohort
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- Contribution to journal › Article
- 2023
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Mark
Towards Explaining Satellite Based Poverty Predictions with Convolutional Neural Networks
2023) 10th IEEE International Conference on Data Science and Advanced Analytics, DSAA 2023 In 2023 IEEE 10th International Conference on Data Science and Advanced Analytics, DSAA 2023 - Proceedings(
- Chapter in Book/Report/Conference proceeding › Paper in conference proceeding
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Mark
Interpretable AI diagnostics for dyspnea in the emergency department by deep learning and a massive regional health care dataset
2023) Swedish Emergency Medicine Talks - SWEETS23(
- Contribution to conference › Poster
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Mark
Design of an AI Support for Diagnosis of Dyspneic Adults at Time of Triage in the Emergency Department
2023) European Emergency Medicine Congress 2023(
- Contribution to conference › Poster
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Mark
A Masked Language Model for Multi-Source EHR Trajectories Contextual Representation Learning
2023) 33rd Medical Informatics Europe Conference: Caring is Sharing - Exploiting the Value in Data for Health and Innovation, MIE2023 In Studies in Health Technology and Informatics 302. p.609-610(
- Chapter in Book/Report/Conference proceeding › Paper in conference proceeding
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Mark
A machine learning model for prediction of 30-day primary graft failure after heart transplantation
(
- Contribution to journal › Article