Artificiell intelligens och thoraxkirurgisk vetenskap (AICTS)

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Forskning

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.

Beskrivning

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.

Ämnesklassifikation (UKÄ)

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FN:s Globala mål

År 2015 godkände FN:s medlemsstater 17 Globala mål för en hållbar utveckling, utrota fattigdomen, skydda planeten och garantera välstånd för alla. Vårt arbete relaterar till följande Globala mål:

  • SDG 3 – God hälsa och välbefinnande

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