Pregled bibliografske jedinice broj: 1188812
Borderline and depression: A thin EEG line
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
Profili:
Damir Mulc
(autor)
Jakša Vukojević
(autor)
Mario Cifrek
(autor)
Aleksandar Savić
(autor)
Eda Jovičić
(autor)
Domagoj Vidović
(autor)
Krešimir Friganović
(autor)
Citiraj ovu publikaciju:
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