Mattias Ohlsson
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- 2023
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Mark
Deep learning prediction models based on EHR trajectories : A systematic review
(
- Contribution to journal › Scientific review
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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
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
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
- 2022
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Mark
Deterministic annealing with Potts neurons for multi-robot routing
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- Contribution to journal › Article
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Mark
The NILS Study Protocol : A Retrospective Validation Study of an Artificial Neural Network Based Preoperative Decision-Making Tool for Noninvasive Lymph Node Staging in Women with Primary Breast Cancer (ISRCTN14341750)
(
- Contribution to journal › Article
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Mark
Delayed traumatic intracranial haemorrhage : The prevalence is very low in patients on oral anticoagulation
2022) Swedish Emergency Medicine Talks 2022(
- Contribution to conference › Poster
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Mark
Characteristics and severe outcomes of patients presenting to the Emergency Department with dizziness
2022) Swedish Emergency Medicine Talks 2022(
- Contribution to conference › Poster
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Mark
Predicting Sensitivity to Adverse Lifestyle Risk Factors for Cardiometabolic Morbidity and Mortality
(
- Contribution to journal › Article
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Mark
The implementation of a noninvasive lymph node staging (NILS) preoperative prediction model is cost effective in primary breast cancer
(
- Contribution to journal › Article