Research output per year
Research output per year
Unit profile
Research
The general aim for our research group, using large and unique global medical databases, to bring the use of artificial neural networks (ANNs) and simulation techniques in risk stratification research a step further, in achieve a higher quality of treatment and improve the outcome for patients with cardiothoracic diseases.Description
Artificial Intelligence in Cardiothoracic Science was funded 2006. Traditionally, medical decisions are based on the combined strength of clinical facts and the experience of the clinician. A growing understanding of the molecular, genetic and biochemical basis of diseases have greatly increased the degree of complexity in medical decision-making. To identify risk factors in medical registers, a non-linear method such as artificial neural network (ANN) may better describe the correlations between different health risk factors. A research area with this high degree of complexity; to identify, optimize and simulate outcomes is strongly dependent on scientific computing using large scalable high-speed computing systems.UKÄ subject classification
- Surgery
UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. Our work contributes towards the following SDG(s):
Collaborations and top research areas from the last five years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
Profiles
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Bodil Andersson
- Surgery (Lund) - Associate professor, Supervisor
- Hepato-Pancreato-Biliary Surgery - Research project participant
- Artificial Intelligence in CardioThoracic Sciences (AICTS) - Research project participant
- eSSENCE: The e-Science Collaboration - Researcher
- LUCC: Lund University Cancer Centre - Principal investigator
Person
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Victoria Jernryd
- Artificial Intelligence in CardioThoracic Sciences (AICTS) - Research project participant
- Artificial Intelligence and Bioinformatics in Cardiothoracic Sciences (AIBCTS) - Doctoral student, Doctoral student
Person
Research output
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A machine learning model for prediction of 30-day primary graft failure after heart transplantation
Linse, B., Ohlsson, M., Stehlik, J., Lund, L. H., Andersson, B. & Nilsson, J., 2023 Mar, In: Heliyon. 9, 3, e14282.Research output: Contribution to journal › Article › peer-review
Open Access -
Delayed intracranial hemorrhage after head trauma seems rare and rarely needs intervention—even in antiplatelet or anticoagulation therapy
Bergenfeldt, H., Forberg, J. L., Lehtinen, R., Anefjäll, E. & Vedin, T., 2023 Dec, In: International Journal of Emergency Medicine. 16, 1, 54.Research output: Contribution to journal › Article › peer-review
Open Access -
Design of an AI Support for Diagnosis of Dyspneic Adults at Time of Triage in the Emergency Department
Tolestam Heyman, E., Ashfaq, A., Ekelund, U., Ohlsson, M., Björk, J., Khoshnood, A. M. & Lingman, M., 2023 Sept.Research output: Contribution to conference › Poster
Open AccessFile
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Pancreatic cancer - complications, survival and quality of life after surgical resection.
Bereza-Carlson, P., Andersson, B., Tingstedt, B. & Williamsson, C.
2021/06/01 → 2029/09/01
Project: Dissertation
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Resource Management in the Emergency Department by using Machine Learning
Tolestam Heyman, E., Khoshnood, A., Ekelund, U., Björk, J., Ohlsson, M., Lingman, M. & Dahlén Holmqvist, L.
2021/02/01 → …
Project: Dissertation
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PREPARE: Improved preparedness for future pandemics and other health crises through large-scale disease surveillance
Björk, J., Inghammar, M., Litins'ka, Y., Forsell, M., Ohlsson, M., Lingman, M., Wigren Byström, J., Almgren, M., Kahn, F., Rasmussen, M., Malmqvist, U., Mitchell, A., Neumann, A., Dietler, D., Bennet, L., Bonander, C., Eriksson, T., Björkelund, A., Vilhelmsson, A., Nilsson, A. & Wetterberg, H.
2021/01/01 → 2025/12/31
Project: Research
Activities
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Resource management in the emergency department by using machine learning
Ellen Tolestam Heyman (Presenter), Ardavan Khoshnood (Contributor), Ulf Ekelund (Contributor), Jonas Björk (Contributor), Mattias Ohlsson (Contributor), Markus Lingman (Contributor) & Lina Dahlén Holmqvist (Contributor)
2021 Nov 2Activity: Talk or presentation › Presentation
File -
Resource management in the emergency department by using machine learning
Ardavan Khoshnood (First/primary/lead supervisor), Ulf Ekelund (Second supervisor), Mattias Ohlsson (Joint second supervisor), Jonas Björk (Joint second supervisor) & Markus Lingman (Joint second supervisor)
2021 Feb 1 → …Activity: Examination and supervision › Supervision of PhD students
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Improved triage, diagnosis and prognosis at the emergency department by using machine learning on big health care data
Jonas Björk (First/primary/lead supervisor), Ulf Ekelund (Joint second supervisor), Jakob Lundager Forberg (Joint second supervisor) & Mattias Ohlsson (Joint second supervisor)
2021 → …Activity: Examination and supervision › Supervision of PhD students
Prizes and distinction
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Grant
Tolestam Heyman, Ellen (Recipient), Khoshnood, Ardavan (Recipient), Lingman, Markus (Recipient), Ekelund, Ulf (Recipient), Björk, Jonas (Recipient), Ohlsson, Mattias (Recipient) & Dahlén Holmqvist, Lina (Recipient), 2023 Oct 27
Prize: Other distinction
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Grant
Tolestam Heyman, Ellen (Recipient), Khoshnood, Ardavan (Recipient), Ekelund, Ulf (Recipient), Björk, Jonas (Recipient), Ohlsson, Mattias (Recipient), Lingman, Markus (Recipient) & Dahlén Holmqvist, Lina (Recipient), 2022 Dec 1
Prize: Other distinction
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Grant
Tolestam Heyman, Ellen (Recipient), Khoshnood, Ardavan (Recipient), Björk, Jonas (Recipient), Ekelund, Ulf (Recipient), Ohlsson, Mattias (Recipient), Lingman, Markus (Recipient) & Dahlén Holmqvist, Lina (Recipient), 2022 Oct 19
Prize: Other distinction