Konstantina Kourou

Konstantina Kourou
University of Ioannina | UOI · Department of Biological Applications and Technologies

MSc

About

34
Publications
8,309
Reads
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2,145
Citations
Citations since 2016
28 Research Items
2123 Citations
20162017201820192020202120220100200300400500
20162017201820192020202120220100200300400500
20162017201820192020202120220100200300400500
20162017201820192020202120220100200300400500
Additional affiliations
October 2013 - October 2015
University of Ioannina
Position
  • PhD Student

Publications

Publications (34)
Conference Paper
A meta-analysis study was conducted to compare high-throughput technologies in the classification of Adult-Onset Still's Disease patients, using differentially expressed genes from independent profiling experiments. We exploited two publicly available datasets from the Gene Expression Omnibus and performed a separate differential expression analysi...
Conference Paper
Being diagnosed with breast cancer (BC) can be a traumatic experience for patients who may experience symptoms of depression. In order to facilitate the prevention of such symptoms, it is crucial to understand how and why depressive symptoms emerge and evolve for each individual, from diagnosis through treatment and recovery. In the present work, d...
Article
Full-text available
For many decades, the clinical unmet needs of primary Sjögren’s Syndrome (pSS) have been left unresolved due to the rareness of the disease and the complexity of the underlying pathogenic mechanisms, including the pSS-associated lymphomagenesis process. Here, we present the HarmonicSS cloud-computing exemplar which offers beyond the state-of-the-ar...
Article
Full-text available
Background: Although several studies have been launched towards the prediction of risk factors for mortality and admission in the intensive care unit (ICU) in COVID-19, none of them focuses on the development of explainable AI models to define an ICU scoring index using dynamically associated biological markers. Methods: We propose a multimodal...
Article
Full-text available
The coronavirus disease 2019 (COVID-19) which is caused by severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) is consistently causing profound wounds in the global healthcare system due to its increased transmissibility. Currently, there is an urgent unmet need to identify the underlying dynamic associations among COVID-19 patients a...
Conference Paper
Breast cancer diagnosis has been associated with poor mental health, with significant impairment of quality of life. In order to ensure support for successful adaptation to this illness, it is of paramount importance to identify the most prominent factors affecting well-being that allow for accurate prediction of mental health status across time. H...
Article
Full-text available
Artificial Intelligence (AI) has recently altered the landscape of cancer research and medical oncology using traditional Machine Learning (ML) algorithms and cutting-edge Deep Learning (DL) architectures. In this review article we focus on the ML aspect of AI applications in cancer research and present the most indicative studies with respect to t...
Article
Displaying resilience following a diagnosis of breast cancer is crucial for successful adaptation to illness, well-being, and health outcomes. Several theoretical and computational models have been proposed toward understanding the complex process of illness adaptation, involving a large variety of patient sociodemographic, lifestyle, medical, and...
Conference Paper
Full-text available
In this study, we propose a dynamic Bayesian network (DBN)-based approach to behavioral modelling of community dwelling older adults at risk for falls during the daily sessions of a hologram-enabled vestibular rehabilitation therapy programme. The component of human behavior being modelled is the level of frustration experienced by the user at each...
Article
Full-text available
Goal: To present a framework for data sharing, curation, harmonization and federated data analytics to solve open issues in healthcare, such as, the development of robust disease prediction models. Methods: Data curation is applied to remove data inconsistencies. Lexical and semantic matching methods are used to align the structure of the heterogen...
Article
Full-text available
Lymphoma development constitutes one of the most serious clinico-pathological manifestations of patients with Sjögren's Syndrome (SS). Over the last decades the risk for lymphomagenesis in SS patients has been studied aiming to identify novel biomarkers and risk factors predicting lymphoma development in this patient population. Objective: The curr...
Article
Genomic profiling of cancer studies has generated comprehensive gene expression patterns for diverse phenotypes. Computational methods which employ transcriptomics datasets have been proposed to model gene expression data. Dynamic Bayesian Networks (DBNs) have been used for modeling time series datasets and for the inference of regulatory networks....
Chapter
Full-text available
In the current study, a model-based system for predicting resilience in silico, as part of personalizing precision medicine, to better understand the needs for improved therapeutic protocols of each patient is proposed. The computational environment, which is currently under implementation within the BOUNCE EU project (“Predicting Effective Adaptat...
Chapter
In this work, we highlight the need of a supervised learning framework for disease predictive modeling across distributed clinical data to overcome the privacy limitations that are introduced by centralized analysis. Towards this direction, a computational framework is proposed, consisting of six incremental learning algorithms that are based on St...
Conference Paper
Balance disorders are expressed with main symptoms of vertigo, dizziness instability and disorientation. Most of them are caused by inner ear pathologies, but neurological, medical and psychological factors are also responsible. Balance disorders overwhelmingly affect daily activities and cause psychological and emotional hardship. They are also th...
Chapter
We propose a computational approach for modeling the progression of Oral Squamous Cell Carcinoma (OSCC) through Dynamic Bayesian Network (DBN) models. RNA-Seq transcriptomics data, available from public functional genomics data repositories, are exploited to find genes related to disease progression (i.e. recurrence or no recurrence). Our primary a...
Article
Objectives: To address the need for automatically assessing the quality of clinical data in terms of accuracy, relevance, conformity, and completeness, through the concise development and application of an automated method which is able to automatically detect problematic fields and match clinical terms under a specific domain. Methods: The prop...
Article
Primary Sjögren's syndrome (pSS) is a chronic, systemic autoimmune disease with diverse clinical picture and outcome. The disease affects primarily middle-aged females and involves the exocrine glands leading to dry mouth and eyes. When the disease extends beyond the exocrine glands (systemic form), certain extraglandular manifestations involving l...
Article
Data quality assessment has gained attention in the recent years since more and more companies and medical centers are highlighting the importance of an automated framework to effectively manage the quality of their big data. Data cleaning, also known as data curation, lies in the heart of the data quality assessment and is a key aspect prior to th...
Article
In this review the critical parts and milestones for data harmonization, from the biomedical engineering perspective, are outlined. The need for data sharing between heterogeneous sources pave the way for cohort harmonization; thus, fostering data integration and interdisciplinary research. Unmet needs in chronic as well as in other diseases, can b...
Conference Paper
Pancreatic Cancer (PC) can be characterized as one of the most lethal cancers considering its poor diagnosis and symptoms in early stages. To assess the predictive value of regulatory molecules in terms of differentially expressed genes, we first performed a thorough search of gene expression profiling studies in pancreatic cohorts. We obtained the...
Conference Paper
We propose a meta-analysis scheme for identifying differentially expressed genes in Oral Squamous Cell Carcinoma (OSCC) from different microarray studies. We detect a subset of relevant features and further classify samples under two experimental conditions (i.e healthy and cancer samples) for better patient stratification. A well-established meta-...
Article
Oral Squamous Cell Carcinoma (OSCC) has been characterized as a complex disease which involves dynamic genomic changes at the molecular level. These changes indicate the worth to explore the interactions of the molecules and especially of differentially expressed genes that contribute to cancer progression. Moreover, based on this knowledge the ide...
Conference Paper
We propose a methodology for predicting oral cancer recurrence using Dynamic Bayesian Networks. The methodology takes into consideration time series gene expression data collected at the follow-up study of patients that had or had not suffered a disease relapse. Based on that knowledge, our aim is to infer the corresponding dynamic Bayesian network...
Conference Paper
Oral Cancer has been characterized as a complex disease and involves dynamic genomic changes. These changes reveal the ability to explore the interactions of the molecules and of differentially expressed genes that are involved in cancer progression. Moreover, based on this knowledge the identification of differentially expressed genes and pathways...
Article
Heart failure is one of the most common diseases worldwide. In recent years, Ventricular Assist Devices (VADs) have become a valuable option for patients with advanced HF. Although it has been shown that VADs improve patient survival rates, several complications persist during left VAD (LVAD) support. The stratification scores currently employed ar...
Article
Disordered proteins lack specific 3D structure in their native state and have been implicated with numerous cellular functions as well as with the induction of severe diseases, e.g., cardiovascular and neurodegenerative diseases as well as diabetes. Due to their conformational flexibility they are often found to interact with a multitude of protein...
Conference Paper
Oral cancer can arise in the head and neck region. Due to the aggressive nature of the disease, which often leads to poor prognosis, Oral Squamous Cell Carcinoma (OSCC) constitutes the 8(th) most common neoplasms in humans. In the present work we formulate gene interaction network from oral cancer genomic data using Dynamic Bayesian Networks (DBNs)...
Article
Full-text available
Acid ecto-phosphatase activity has been implicated in Leishmania donovani promastigote virulence. Here we report data contributing to the molecular/structural and functional characterization of the Leishmania donovani LdMAcP, member of the histidine acid phosphatase family. LdMAcP, is membrane anchored and shares high sequence identity with the maj...
Article
Full-text available
Computational modelling of diseases is an emerging field, proven valuable for the diagnosis, prognosis and treatment of the disease. Cancer is one of the diseases where computational modelling provides enormous advancements, allowing the medical professionals to perform in silico experiments and gain insights prior to any in vivo procedure. In this...
Article
Full-text available
Cancer has been characterized as a heterogeneous disease consisting of many different subtypes. The early diagnosis and prognosis of a cancer type have become a necessity in cancer research, as it can facilitate the subsequent clinical management of patients. The importance of classifying cancer patients into high or low risk groups has led many re...

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