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Profil bibliographique

Nebojsa D. Zdravkovic

Informations fournies par OpenAlex. Research Africa ne déduit ni nationalité, ni poste, ni coordonnées personnelles.

114Publications signalées
570Citations signalées
1Affiliations récentes

Les institutions déclarées

Les domaines associés

Inflammatory Bowel DiseaseCOVID-19 Clinical Research StudiesLong-Term Effects of COVID-19COVID-19 and Mental HealthCoronary Interventions and Diagnostics

Les publications récentes

Accès ouvert 2026 article OpenAlex

A GIS–AHP Framework for Spatial Assessment of Urban Stress Using Wearable Sensor Data: A Pilot Study in Kragujevac

Nebojsa D. Zdravkovic, Mateja Zdravkovic, Dalibor Nikolić, Aleksandar Peulić

Urban traffic environments can elevate physiological stress, yet most existing studies assess this indirectly through infrastructural or traffic-related proxies rather than direct physiological measurement. This pilot study proposes a geographic information system (GIS)–Analytical Hierarchy Process (AHP) framework that integrates wearable heart-rate sensing …

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0 citations Urban Science
Accès ouvert 2026 article OpenAlex

Assessment of Quality of Life in Patients Following Lower Limb Amputation

Katarina Manojlovic, Ana Divjak, Igor Simanic, K Krstić et autres

Abstract According to the World Health Organization, part of the quality of life is the perception of one's body concerning the culture and values of each individual. Limb amputation affects the quality of life through several defined aspects. Observing the available statistical …

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0 citations EABR. Experimental and Applied Biomedical Research
Accès ouvert 2026 review OpenAlex

The Next Phase of 3D Bioprinting: AI-Native Systems—A Narrative Review

Nebojsa D. Zdravkovic, Mateja Zdravkovic, Marko Živanović

Three-dimensional (3D) bioprinting has reached a complexity limit where empirical, parameter-by-parameter optimization no longer scales. The dominant mode of artificial intelligence (AI) integration remains AI-augmented, where AI is treated as an analytical addition to a conventional pipeline. We argue that the field …

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0 citations Journal of Functional Biomaterials
Accès ouvert 2026 article OpenAlex

Computational Investigation of Friction Stir Processing of Ti-6Al-4V Alloy for Biomedical Applications Using FEM and Taguchi Design

Nebojsa D. Zdravkovic, Dragan Džunić, Živana Jovanović Pešić, Dalibor Nikolić

Friction stir processing (FSP) is an advanced solid-state surface modification technique for biomedical titanium alloys. This study presents a computational investigation of FSP applied to Ti-6Al-4V alloy through three-dimensional finite element modeling and Taguchi-based statistical optimization. A Taguchi L9 orthogonal array evaluated …

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0 citations Computation
Accès ouvert 2026 article OpenAlex

Biological Activity of Copper(II) and Palladium(II) Complexes with a Tetradentate S,O-Donor Ligand

Anita Šarić, Marina M. Mitrović, Ana Barjaktarević, Snežana Jovanović et autres

New copper(II) (C1) and palladium(II) (C2) complexes with S,O-tetradentate ligand (L) derived from thiosalicylic and thiopropionic acids were synthesized. In cell-based assays, (C1) exhibited the most pronounced activity within the tested compound series and was therefore advanced for mechanistic evaluation in 4T1 …

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0 citations International Journal of Molecular Sciences
Accès ouvert 2026 conference-paper OpenAlex

Differentiating Suspected and Confirmed Heart Failure Using Machine Learning and Refined Vocal Features

Lazar Dašić, Ognjen Pavić, Tijana Geroski, Anđela Blagojević et autres

Voice characteristics are an emerging, non-invasive biomarker for heart failure. This study develops a machine learning pipeline to differentiate patients with suspected heart failure from those with a confirmed diagnosis using vocal features alone, drawing on 240 patients (50 suspected, 190 confirmed) …

rs, ru, gb, nl, us, au, it, es (code pays fourni par la source)

0 citations Zenodo (CERN European Organization for Nuclear Research)
Accès ouvert 2026 conference-paper OpenAlex

Differentiating Suspected and Confirmed Heart Failure Using Machine Learning and Refined Vocal Features

Lazar Dašić, Ognjen Pavić, Tijana Geroski, Anđela Blagojević et autres

Voice characteristics are an emerging, non-invasive biomarker for heart failure. This study develops a machine learning pipeline to differentiate patients with suspected heart failure from those with a confirmed diagnosis using vocal features alone, drawing on 240 patients (50 suspected, 190 confirmed) …

rs, ru, gb, nl, us, au, it, es (code pays fourni par la source)

0 citations Zenodo (CERN European Organization for Nuclear Research)
Accès ouvert 2026 conference-paper OpenAlex

Differentiating Suspected and Confirmed Heart Failure Using Machine Learning and Refined Vocal Features

Lazar Dašić, Ognjen Pavić, Tijana Geroski, Anđela Blagojević et autres

Voice characteristics are an emerging, non-invasive biomarker for heart failure. This study develops a machine learning pipeline to differentiate patients with suspected heart failure from those with a confirmed diagnosis using vocal features alone, drawing on 240 patients (50 suspected, 190 confirmed) …

rs, ru, gb, nl, us, au, it, es (code pays fourni par la source)

0 citations Zenodo (CERN European Organization for Nuclear Research)
Accès ouvert 2026 conference-paper OpenAlex

Differentiating Suspected and Confirmed Heart Failure Using Machine Learning and Refined Vocal Features

Lazar Dašić, Ognjen Pavić, Tijana Geroski, Anđela Blagojević et autres

Voice characteristics are an emerging, non-invasive biomarker for heart failure. This study develops a machine learning pipeline to differentiate patients with suspected heart failure from those with a confirmed diagnosis using vocal features alone, drawing on 240 patients (50 suspected, 190 confirmed) …

rs, ru, gb, nl, us, au, it, es (code pays fourni par la source)

0 citations Zenodo (CERN European Organization for Nuclear Research)
Accès ouvert 2026 article OpenAlex

Lifestyle and Health Characteristics of the Adult Population of Serbia with Type 2 Diabetes Mellitus

Elijah Kiprono Toroitich, Olgica Mihaljević, Snezana Radovanovic, Ivana Simić-Vukomanović et autres

Background and Objectives: Diabetes is one of the most common chronic non-communicable diseases and represents a major public health problem. At the global level, the epidemic character of diabetes mellitus can be attributed to an extended life expectancy but also to lifestyle. …

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1 citation Medicina
Accès ouvert 2026 article OpenAlex

The IL-33/ST2 Axis Protects the Hippocampus from LPS-Induced Inflammation and Damage by Modulating Microglial Phenotype

Jelena Nedeljkovic, Jelena Milovanović, Vujica Marković, Natalia Solovjova et autres

Background/Objectives: Systemic inflammation is a known driver of neurodegenerative processes, with amyloid accumulation and neuronal loss. The Interleukin-33 (IL-33)/Suppression of Tumorigenicity 2 (ST2) signaling pathway has emerged as a critical immune regulator with dual roles in maintaining brain health. However, its role …

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0 citations Biomedicines
Accès ouvert 2026 article OpenAlex

Eating Disorders in School-Age Children During the COVID-19 Pandemic

Nataša Djorić, Ivan Vukosavljevic, Ivana Vukosavljević, Igor Sekulić et autres

(1) Background: Eating disorder risk factors in children are early maturation, body dissatisfaction, dieting, stress and physical inactivity. The COVID-19 pandemic has further exacerbated these factors due to isolation, online classes and reduced physical activity, all of which have increased children’s risk …

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0 citations Children

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