Blar i HVL Open på forfatter "Aminifar, Amin"

Viser treff 1-5 av 5

    • Challenges and possible solutions in cross-disciplinary and cross-sectorial research teams within the domain of e-mental health 

      Nordgreen, Tine; Rabbi, Fazle; Tørresen, Jim; Skar, Yngvar Sigmund; Guribye, Frode; Inal, Yavuz; Flobak, Eivind; Wake, Jo Dugstad; Mukhiya, Suresh Kumar; Aminifar, Amin; Myklebost, Sunniva Brurok; Lundervold, Astri J.; Kenter, Robin Maria Francisca; Hammar, Åsa Karin; Kahlon, Smiti; Nordby, Emilie; Sekse, Ragnhild Johanne Tveit; Griffin, Kristine Fonnes; Jakobsen, Petter; Pham, Hoang Minh; Côté-Allard, Ulysse Teller Masao; Noori, Farzan Majeed; Lamo, Yngve (Peer reviewed; Journal article, 2021)
      Purpose Mental illness presents a huge individual, societal and economic challenges, currently accounting for 20% of the worldwide burden of disease. There is a gap between the need for and access to services. Digital ...

    • Extremely Randomized Trees With Privacy Preservation for Distributed Structured Health Data 

      Aminifar, Amin; Matin, Shokri; Rabbi, Fazle; Pun, Violet Ka I; Lamo, Yngve (Peer reviewed; Journal article, 2022)
      Artificial intelligence and machine learning have recently attracted considerable attention in the healthcare domain. The data used by machine learning algorithms in healthcare applications is often distributed over multiple ...

    • A Practical Methodology for Anonymization of Structured Health Data 

      Aminifar, Amin; Lamo, Yngve; Pun, Ka I; Rabbi, Fazle (Peer reviewed; Journal article, 2019)
      Hospitals, as data custodians, have the need to share a version of the data in hand with external research institutes for analysis purposes. For preserving the privacy of the patients, anonymization methods are employed ...

    • Privacy-Preserving Machine Learning and Data Sharing in Healthcare Applications 

      Aminifar, Amin (Doctoral thesis, 2022)
      Artificial intelligence (AI) and automated decision-making have the potential to improve accuracy and efficiency in healthcare applications. In particular, AI is proved to outperform human experts in certain domains. ...

    • Towards Adaptive Technology in Routine Mental Healthcare 

      Lamo, Yngve; Mukhiya, Suresh Kumar; Rabbi, Fazle; Aminifar, Amin; Lillehaug, Svein Ivar; Tørresen, Jim; Pham, Minh H.; Côté-Allard, Ulysse Teller Masao; Noori, Farzan Majeed; Guribye, Frode; Inal, Yavuz; Flobak, Eivind; Wake, Jo Dugstad; Myklebost, Sunniva Brurok; Lundervold, Astri J.; Hammar, Åsa Karin; Nordby, Emilie Sektnan; Kahlon, Smiti; Kenter, Robin Maria Francisca; Sekse, Ragnhild Johanne Tveit; Griffin, Kristine Fonnes; Jakobsen, Petter; Ødegaard, Ketil Joachim; Skar, Yngvar Sigmund; Nordgreen, Tine (Peer reviewed; Journal article, 2022)
      This paper summarizes the information technology-related research findings after 5 years with the INTROducing Mental health through Adaptive Technology project. The aim was to improve mental healthcare by introducing new ...