Maria Markaki

• Computer Science Dept, UoC
• PostDoc Position at Foundation for Research and Technology Hellas

Purpose The HUNT Lung Cancer Model (HUNT LCM) predicts individualized 6-year lung cancer (LC) risk among individuals who ever smoked cigarettes with high precision based on eight clinical variables. Can the performance be improved by adding genetic information? Methods A polygenic model was developed in the prospective Norwegian HUNT2 study with c...

Introduction Blood biomarkers for early detection of lung cancer (LC) are in demand. There are few studies of the full microRNome in serum of asymptomatic subjects that later develop LC. Here we searched for novel microRNA biomarkers in blood from non-cancer, ever-smokers populations up to eight years before diagnosis. Methods Serum samples from 9...

8041 Background: With lung cancer incidence and mortality on the rise, blood biomarkers are increasingly in demand for early detection. The aim of this study is to discover and validate novel biomarkers based on next-generation sequencing performed on blood samples from non-cancer, ever-smokers up to eight years prior to diagnosis. Methods: Initial...

e20066 Background: As lung cancer incidence and mortality increase, methods of early diagnosis are needed to increase survival. The validated HUNT Lung Cancer Model (HUNT LCM) predicts individual 6-year risk of lung cancer in ever smokers with an AUC of 0.87 based on eight clinical variables: sex, age, BMI, pack-years, smoking intensity number of c...

Background Improving the method for selecting participants for lung cancer (LC) screening is an urgent need. Here, we compared the performance of the Helseundersøkelsen i Nord-Trøndelag (HUNT) Lung Cancer Model (HUNT LCM) versus the Dutch-Belgian lung cancer screening trial (Nederlands-Leuvens Longkanker Screenings Onderzoek (NELSON)) and 2021 Unit...

Lung cancer (LC) incidence is increasing globally and altered levels of microRNAs (miRNAs) in blood may contribute to identification of individuals with LC. We identified miRNAs differentially expressed in peripheral blood at LC diagnosis and evaluated, in pre-diagnostic blood specimens, how long before diagnosis expression changes of such candidat...

Platinum-based chemotherapy (CT) is a standard treatment for lung cancer, however a variety of chemoresistance mechanisms can impair its efficacy. MicroRNAs (miRNAs) represent potential biomarkers for the prediction of treatment efficacy in non-small cell lung cancer (NSCLC). We herein used a bioinformatics approach to identify differentially expre...

Hypothesis We hypothesise that the validated HUNT Lung Cancer Risk Model would perform better than the NLST (USA) and the NELSON (Dutch‐Belgian) criteria in the Danish Lung Cancer Screening Trial (DLCST). Methods The DLCST measured only five out of the seven variables included in validated HUNT Lung Cancer Model. Therefore a ‘Reduced’ model was re...

Background Aberrant miRNA expression has been associated with DNA damage response (DDR) pathways that modulate tumor response to platinum agents. We assessed the expression of miR-21, miR-128, mir-155 and miR-181 involved in DDR pathways, in the plasma of metastatic non- small cell lung cancer (mNSCLC) patients receiving 1st-line platinum-based che...

e20696 Background: A novel validated model for risk prediction of lung cancer, the HUNT Lung Cancer Model predicts 6- and 16-year risk of lung cancer with a C-index = 0.879 and 6-year AUC = 0.87. The model is valid for smokers and ex-smokers of any intensity and quit time and includes seven variables; age, BMI, pack-years, smoking intensity (cigare...

e20095 Background: The high incidence and high mortality rate of small-cell lung cancer (SCLC) calls for identification of methods for early diagnosis. Searching of cancer-related proteins and proteins signature in biofluids is an emerging approach in early diagnostic of malignancies. In the present study we have used proteomics-based profiling of...

Lung cancer causes >1·6 million deaths annually, with early diagnosis being paramount to effective treatment. Here we present a validated risk assessment model for lung cancer screening. The prospective HUNT2 population study in Norway examined 65,237 people aged >20 years in 1995–97. After a median of 15·2 years, 583 lung cancer cases had been dia...

More than a third of the cellular proteome is non-cytoplasmic. Most secretory proteins use the Sec system for export and are targeted to membranes using signal peptides and mature domains. To specifically analyze bacterial mature domain features, we developed MatureP, a classifier that predicts secretory sequences through features exclusively compu...

e23059 Background: The Cancer-Biomarkers in HUNTinitiative seeks to identify novel biomarkers for the early cancer diagnosis. For lung cancers and mesothelioma clinically useful early markers are not available. In the prospective HUNT study in Norway, pre-diagnostic samples ranging 0-20 years before diagnosis are available for research purposes. He...

This paper describes a system for discriminating innocent from pathologic systolic heart murmurs in children based on auscultation recordings. For sound signal analysis the use of reassigned spectrogram is suggested. Both dimensions and noise of the time-frequency representation were significantly reduced using higher order singular value decomposi...

Matched-Field Processing with a Genetic Algorithm is applied to the problem of bottom recognition with synthetic noise-free acoustic data. The data correspond to three classes of benchmark problems. Four alternative objective functions have been tested, all of them defined to be used with broadband data with either coherent or incoherent processing...

In this paper, we explore the information provided by a joint acoustic and modulation frequency representation, referred to as modulation spectrum, for detection and discrimination of voice disorders. The initial representation is first transformed to a lower dimensional domain using higher order singular value decomposition (HOSVD). From this dime...

We describe a content based speech discrimination algorithm in broadcast news based on the time-varying information provided by the modulation spectrum. Due to the varying degrees of re- dundancy and discriminative power of the acoustic and mod- ulation frequency subspaces, we first employ a generalizati on of SVD to tensors (Higher Order SVD) to r...

This work presents a novel approach for the automatic detection of pathological voices based on fusing the information extracted by means of mel-frequency cepstral coefficients (MFCC) and features derived from the modulation spectra (MS). The system proposed uses a two-stepped classification scheme. First, the MFCC and MS features were used to feed...

In this paper, we combine modulation spectral features with mel-frequency cepstral coefficients for automatic detection of dysphonia. For classification purposes, dimensions of the original modulation spectra are reduced using higher order singular value decomposition (HOSVD). Most relevant features are selected based on their mutual information to...

In this paper, we employ normalized modulation spectral features for objective voice quality assessment regarding grade (hoarseness). Modulation spectra usually produce a high-dimensionality space. For classification purposes, the size of the original space is reduced using Higher Order Singular Value Decomposition (SVD). Further, we select most re...

In this paper, we employ normalized modulation spectral anal- ysis for voice pathology detection. Such normalization is im- portant when there is a mismatch between training and testing conditions, or in other words, employing the detection system in real (testing) conditions. Modulation spectra usually pro duce a high-dimensionality space. For cla...

In this paper, we consider the use of Modulation Spectra for voice pathology detection and classification. To reduce the high-dimensionality space generated by Modulation spectra we suggest the use of Higher Order Singular Value Decomposition (SVD) and we propose a feature selection algorithm based on the Mutual Information between subjective voice...

In this paper, we suggest the use of mutual information to ex- plore the information provided by the modulation spectrum for speaker verification and identification purposes. The in i- tial representation is first transformed to a lower-dimensi onal domain using Higher Order SVD and then, the mutual infor- mation between speaker identity and featur...

We describe a dimensionality reduction method for modulation spectral features, which keeps the time-varying information of interest to the classification task. Due to the varying degre es of redundancy and discriminative power of the acoustic and mod- ulation frequency subspaces, we first employ a generalizati on of SVD to tensors (Higher Order SV...

In this work, we adopt an information theoretic approach - the Information Bottleneck method - to extract the relevant spectro- temporal modulations for the task of speech / non-speech dis- crimination - non-speech events include music, noise and an- imal vocalizations. A compact representation (a "cluster pro- totype") is built for each class cons...

In this work, we adopt an information theoretic approach - the Information Bottleneck method to extract the relevant modulation frequencies across both dimensions of a spectrogram, for speech / non-speech discrimination (music, animal vocalizations, environmental noises). A compact representation is built for each sound ensemble, consisting of the...

In this work, we adopt an information theoretic approach -the Information Bottleneck method -to extract the relevant modulation frequencies across both dimensions of a spectro-gram, for speech / non-speech discrimination (music, animal vocalizations, environmental noises). A compact representa-tion is built for each sound ensemble, consisting of th...

A hybrid speech/non-speech detector is proposed for the pre-processing of broadcast news. During the first stage speech/non-speech classification of uniform overlapping segments is performed. The accuracy in the detection of boundaries is determined by the degree of overlap of the audio segments and it is 250 ms in our case. Extracted speech segmen...

We use a multi-compartmental model of a CA1 pyramidal cell to study changes in hippocampal excitability that result from aging-induced alterations in calcium-dependent membrane mechanisms. The model incorporates N- and L-type calcium channels which are respectively coupled to fast and slow afterhyperpolarization potassium channels. Model parameters...

The paper deals with an inversion approach based on modal travel time measurements for the estimation of water column and bottom properties in shallow water, by acoustic means. The modal structure of the acoustic field measured at a single hydrophone is defined on the basis of group velocity predictions at the central frequency of a broadband signa...

The sensitivity of a Bartlett processor used as an objective function in a matched-field approach to bottom recognition in a shallow-water environment is investigated. The study addresses the varying response of the processor to changes in the values of geoacoustic parameters, in different frequencies and ranges from the source. It is shown that ce...

A matched?field processing method for the simultaneous estimation of ocean current velocity structure and sound speed profiles, based on reciprocal transmissions of cw or broadband acoustic signals between two locations in the water column, is presented and discussed. For each transmission, a single source and a vertical array of hydrophones are us...

Various object functions for broadband inversions of noisy data using matched?field processing for bottom recognition are studied. The study is based on the inversion results obtained by processing synthetic ??noisy?? data that have been available at a follow?up stage of a benchmark exercise for bottom geoacoustic inversions that was carried out in...

Matched-Field Processing with a Genetic Algorithm is applied to the problem of bottom recognition with synthetic noise-free acoustic data. The data correspond to three classes of benchmark problems. Four alternative objective functions have been tested, all of them denned to be used with broadband data with either coherent or incoherent processing...

Matched-field processing and a hybrid scheme for vertical slice tomography are studied in characteristic cases of range-independent and range-dependent ocean environments using simulated data obtained at discrete points in the sound field along a vertical Line, representing a vertical array of hydrophones. The matched-field processing is associated...

One subject of Underwater Acoustics that is currently receiving much attention, is the solution of inverse problems, in which some (or all) of the ocean-acoustic parameters characterizing a channel (e.g., the sound speed profile in the water column, and the subbottom structure) are determined from measurements of the sound field at several points i...

In this paper, a feature set derived from modulation spectra is applied to the task of detecting singing voice in historical and recent recordings of Greek Rembetiko. A generalization of SVD to tensors, Higher Order SVD (HOSVD), is applied to reduce the dimensions of the feature vectors. Projection onto the "significant" principal axes of the acous...

This modeling study focuses on the investigation of the functional alterations in hippocampus, which underlie the long-term episodic memory decrements during aging. Although aged subjects may have intact memory for individual features of an event, they have a difficulty to perform associations between them. The feature binding deficit probably aris...