Klementy Shchetynsky

Klementy Shchetynsky

Forskningsspecialist
Besöksadress: L8:05, CMM Karolinska Universitetssjukhuset Solna, 17176 Stockholm
Postadress: K8 Klinisk neurovetenskap, K8 Neuro Kockum, 171 77 Stockholm
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Artiklar

Alla övriga publikationer

Forskningsbidrag

  • Improving prediction of multiple sclerosis, algorithmic approaches and biomarkers
    Region Stockholm ALF Medicin
    1 January 2026 - 31 December 2028
    Multiple Sclerosis (MS), a complex autoimmune disorder affecting mainly young adults, with a higher prevalence in women. Its diverse symptoms and inherent progression complexity hinder early detection and personalized prognostic evaluations. This proposal aspires to enhance health outcomes, elucidate MS’s intricate mechanisms, and reduce neurological disabilities through innovative, transformative methodologies. The objective is to develop advanced predictive models by harnessing extensive multimodal data, facilitating early detection, and personalized interventions. The project is organized in 4 different but interconnected tasks and will run for 3 years. We will integrate clinical, lifestyle, and 'omics' data. By targeting the prodromal phase of MS, we aspire to devise impactful intervention strategies and project disease progression, with Artificial Intelligence (AI) serving as the cornerstone for analyzing data. We will test the MS prediction among first degree relatives. We will also identify biomarkers for MS risk. A special focus will be on role of sex hormones. Employing advanced analytical techniques, network theories, autoencoders and deep learning, we will probe the multifaceted nature of MS using one of the world’s leading MS-specific databases. This will contribute to earlier diagnosis of MS and opening up for reduction of the disease by personalized changes in lifestyle and possibly preventative treatments in the future.
  • Swedish Research Council
    1 January 2025 - 31 December 2028
    Multiple Sclerosis (MS), a complex autoimmune disorder affecting mainly young adults, with a higher prevalence in women. Its diverse symptoms and inherent progression complexity hinder early detection and personalized prognostic evaluations. This proposal aspires to enhance health outcomes, elucidate MS’s intricate mechanisms, and reduce neurological disabilities through innovative, transformative methodologies.The objective is to develop advanced predictive models by harnessing extensive multimodal data, facilitating early detection, and personalized interventions. The project is organized in 6 different but interconnected tasks and will run for 5 years. We will integrate clinical, lifestyle, and ´omics´ data. By targeting the prodromal phase of MS, we aspire to devise impactful intervention strategies and project disease progression, with Artificial Intelligence (AI) serving as the cornerstone for analyzing data. We will test the MS prediction among first degree relatives. We will also identify biomarkers for MS risk and severity and genetic factors associated with MS severity. A special focus will be on role of sex hormones.Employing advanced analytical techniques, network theories, autoencoders and deep learning, we will probe the multifaceted nature of MS using one of the world’s leading MS-specific databases. This will contribute to more comprehensive and individualized MS treatment approaches.
  • Swedish Research Council
    1 January 2021 - 31 December 2024

Anställningar

  • Forskningsspecialist, Klinisk neurovetenskap, Karolinska Institutet, 2021-

Examina och utbildning

  • Medicine Doktorsexamen, Institutionen för medicin, Solna, Karolinska Institutet, 2015
  • Medicine Masterexamen Med Huvudområdet, Karolinska Institutet, 2009

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