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Št. zadetkov: 5
Izvirni znanstveni članek
Oznake: depresija;suicidalna ideacija;nespečnost;strojno učenje;presejalni test;preprečevanje samomorilnosti;mehanizmi spoprijemanja s težavami;depression;suicidal ideation;insomnia;machine learning;indirect screening;suicide prevention;coping mechanisms;
Background Insomnia is a significant independent risk factor for depression and suicidality. However, these conditions often go undetected, particularly in individuals presenting with sleep complaints. This study aimed to develop and validate machine learning (ML) models for the indirect screening ...
Leto: 2025 Vir: Fakulteta za računalništvo in informatiko (UL FRI)
Izvirni znanstveni članek
Oznake: Parkinson’s disease;serotonin/noradrenaline reuptake inhibitors;depression;
Background: Depression often co-occurs with Parkinson’s disease (PD) and is effectively treated with selective serotonin reuptake inhibitors (SSRI) and serotonin and noradrenaline reuptake inhibitors (SNRI), but their effect on motor symptoms has not yet been conclusively demonstrated. Objective: To ...
Leto: 2024 Vir: Digitalni repozitorij raziskovalnih organizacij Slovenije
Izvirni znanstveni članek
Oznake: depression;anxiety;COVID-19;
The spread of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) causing coronavirus disease 2019 (COVID-19) pandemic has led to numerous negative consequences on the mental health of the population throughout the world. The main aim of our study was to compare the risk for depression, anx ...
Leto: 2022 Vir: Fakulteta za računalništvo in informatiko (UL FRI)
Izvirni znanstveni članek
Oznake: analiza ritmičnosti;ritmi;integrativne analize;rhythmicity analysis;rhythms;integrative analyses;
Background. The severity of both the COVID-19 clinical picture and confinement measures in Slovenia was higher during the initial phase of the pandemic in 2020 than during the Omicron wave in 2022. This could lead us to expect a higher level of distress during the initial phase. On the other hand, p ...
Leto: 2023 Vir: Fakulteta za računalništvo in informatiko (UL FRI)
Objavljeni znanstveni prispevek na konferenci
Oznake: nenadzorovano učenje;senzorski podatki;Parkinsonova bolezen;unsupervised learning;sensor data;Parkinson's disease;
Unsupervised learning from motion sensor data to assess the condition of patients with Parkinson's disease
Leto: 2019 Vir: Univerza na Primorskem (UP)
Št. zadetkov: 5
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