Pretražite po imenu i prezimenu autora, mentora, urednika, prevoditelja

Napredna pretraga

Pregled bibliografske jedinice broj: 1188812

Borderline and depression: A thin EEG line


Vukojević, Jakša; Mulc, Damir; Kinder, Ivana; Jovičić, Eda; Friganović, Krešimir; Savić, Aleksandar; Cifrek, Mario; Vidović, Domagoj
Borderline and depression: A thin EEG line // Clinical eeg and neuroscience (2021) doi:10.1177/15500594211060830 (znanstveni, online first)


CROSBI ID: 1188812 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Borderline and depression: A thin EEG line

Autori
Vukojević, Jakša ; Mulc, Damir ; Kinder, Ivana ; Jovičić, Eda ; Friganović, Krešimir ; Savić, Aleksandar ; Cifrek, Mario ; Vidović, Domagoj

Vrsta, podvrsta
Radovi u časopisima, znanstveni

Izvornik
Clinical eeg and neuroscience (2021)

Status rada
Online first

Ključne riječi
EEG ; machine learning ; biomarker ; BPD ; MDD ; depression

Sažetak
In everyday clinical practice, there is an ongoing debate about the nature of major depressive disorder (MDD) in patients with borderline personality disorder (BPD). The underlying research does not give us a clear distinction between those 2 entities, although depression is among the most frequent comorbid diagnosis in borderline personality patients. The notion that depression can be a distinct disorder but also a symptom in other psychopathologies led our team to try and delineate those 2 entities using 146 EEG recordings and machine learning. The utilized algorithms, developed solely for this purpose, could not differentiate those 2 entities, meaning that patients suffering from MDD did not have significantly different EEG in terms of patients diagnosed with MDD and BPD respecting the given data and methods used. By increasing the data set and the spatiotemporal specificity, one could have a more sensitive diagnostic approach when using EEG recordings. To our knowledge, this is the first study that used EEG recordings and advanced machine learning techniques and further confirmed the close interrelationship between those 2 entities.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo, Kliničke medicinske znanosti, Kognitivna znanost (prirodne, tehničke, biomedicina i zdravstvo, društvene i humanističke znanosti)



POVEZANOST RADA


Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb,
Medicinski fakultet, Zagreb,
Klinika za psihijatriju Vrapče

Poveznice na cjeloviti tekst rada:

doi

Citiraj ovu publikaciju:

Vukojević, Jakša; Mulc, Damir; Kinder, Ivana; Jovičić, Eda; Friganović, Krešimir; Savić, Aleksandar; Cifrek, Mario; Vidović, Domagoj
Borderline and depression: A thin EEG line // Clinical eeg and neuroscience (2021) doi:10.1177/15500594211060830 (znanstveni, online first)
Vukojević, J., Mulc, D., Kinder, I., Jovičić, E., Friganović, K., Savić, A., Cifrek, M. & Vidović, D. (2021) Borderline and depression: A thin EEG line. Prihvaćen za objavljivanje u Clinical eeg and neuroscience. [Preprint] doi:10.1177/15500594211060830.
@unknown{unknown, author = {Vukojevi\'{c}, Jak\v{s}a and Mulc, Damir and Kinder, Ivana and Jovi\v{c}i\'{c}, Eda and Friganovi\'{c}, Kre\v{s}imir and Savi\'{c}, Aleksandar and Cifrek, Mario and Vidovi\'{c}, Domagoj}, year = {2021}, DOI = {10.1177/15500594211060830}, keywords = {EEG, machine learning, biomarker, BPD, MDD, depression}, journal = {Clinical eeg and neuroscience}, doi = {10.1177/15500594211060830}, title = {Borderline and depression: A thin EEG line}, keyword = {EEG, machine learning, biomarker, BPD, MDD, depression} }
@unknown{unknown, author = {Vukojevi\'{c}, Jak\v{s}a and Mulc, Damir and Kinder, Ivana and Jovi\v{c}i\'{c}, Eda and Friganovi\'{c}, Kre\v{s}imir and Savi\'{c}, Aleksandar and Cifrek, Mario and Vidovi\'{c}, Domagoj}, year = {2021}, DOI = {10.1177/15500594211060830}, keywords = {EEG, machine learning, biomarker, BPD, MDD, depression}, journal = {Clinical eeg and neuroscience}, doi = {10.1177/15500594211060830}, title = {Borderline and depression: A thin EEG line}, keyword = {EEG, machine learning, biomarker, BPD, MDD, depression} }

Časopis indeksira:


  • Current Contents Connect (CCC)
  • Web of Science Core Collection (WoSCC)
    • Science Citation Index Expanded (SCI-EXP)
    • SCI-EXP, SSCI i/ili A&HCI
  • Scopus
  • MEDLINE


Citati:





    Contrast
    Increase Font
    Decrease Font
    Dyslexic Font