Author(s): Ranipa K; Zhu WP; Swamy MNS;

Vision Transformers (ViTs), inspired by their success in natural language processing, have recently gained attention for heart sound classification (HSC). However, most of the existing studies on HSC rely on single-stream architectures, overlooking the advantages of multi-resolution features. While multi-stream architectures employing early or late fusion ...

Article GUID: 41155032

Author(s): Khademi S; Heidarian S; Afshar P; Mohammadi A; Sidiqi A; Nguyen ET; Ganeshan B; Oikonomou A;

In this study, we propose a novel hybrid framework for assessing the invasiveness of an in-house dataset of 114 pathologically proven lung adenocarcinomas presenting as subsolid nodules on Computed Tomography (CT). Nodules were classified into group 1 (G1), which included atypical adenomatous hyp ...

Article GUID: 41150036

Author(s): Lahmiri S; Bekiros S;

Background/Objectives: Cardiac arrhythmia (ARR) and congestive heart failure (CHF) are heart diseases that can cause dysfunction of other body organs and possibly death. This paper describes a fast and accurate detection system to distinguish between ARR and normal sinus (NS), and between CHF and NS. Methods: the proposed automatic detection system uses t ...

Article GUID: 40218199

Author(s): Elmekki H; Alagha A; Sami H; Spilkin A; Zanuttini AM; Zakeri E; Bentahar J; Kadem L; Xie WF; Pibarot P; Mizouni R; Otrok H; Singh S; Mourad A;

Cardiac ultrasound (US) scanning is one of the most commonly used techniques in cardiology to diagnose the health of the heart and its proper functioning. During a typical US scan, medical professionals take several images of the heart to be classified based on the cardiac views they contain, wit ...

Article GUID: 40107020

Author(s): Hrtonova V; Nejedly P; Travnicek V; Cimbalnik J; Matouskova B; Pail M; Peter-Derex L; Grova C; Gotman J; Halamek J; Jurak P; Brazdil M; Klimes P; Frauscher B;

Introduction: Precise localization of the epileptogenic zone is critical for successful epilepsy surgery. However, imbalanced datasets in terms of epileptic vs. normal electrode contacts and a lack of standardized evaluation guidelines hinder the consistent evaluation of automatic machine learnin ...

Article GUID: 39608298

Author(s): Islam M; Zunair H; Mohammed N;

Crafting effective deep learning models for medical image analysis is a complex task, particularly in cases where the medical image dataset lacks significant inter-class variation. This challenge is further aggravated when employing such datasets to generate synthetic images using generative adversarial networks (GANs), as the output of GANs heavily relie ...

Article GUID: 38492455

Author(s): Lahmiri S; Boukadoum M; Di Ieva A;

Several natural phenomena can be described by studying their statistical scaling patterns, hence leading to simple geometrical interpretation. In this regard, fractal geometry is a powerful tool to describe the irregular or fragmented shape of natural features, using spatial or time-domain statistical scaling laws (power-law behavior) to characterize real ...

Article GUID: 38468046

Author(s): Belasso CJ; Cai Z; Bezgin G; Pascoal T; Stevenson J; Rahmouni N; Tissot C; Lussier F; Rosa-Neto P; Soucy JP; Rivaz H; Benali H;

Background: Alzheimer's disease (AD) diagnosis in its early stages remains difficult with current diagnostic approaches. Though tau neurofibrillary tangles (NFTs) generally follow the stereotypical pattern described by the Braak staging scheme, the network degeneration hypothesis (NDH) has su ...

Article GUID: 37920382

Author(s): Thölke P; Mantilla-Ramos YJ; Abdelhedi H; Maschke C; Dehgan A; Harel Y; Kemtur A; Mekki Berrada L; Sahraoui M; Young T; Bellemare Pépin A; El Khantour C; Landry M; Pascarella A; Hadid V; Combrisson E; O' Byrne J; Jerbi K;

Machine learning (ML) is increasingly used in cognitive, computational and clinical neuroscience. The reliable and efficient application of ML requires a sound understanding of its subtleties and limitations. Training ML models on datasets with imbalanced classes is a particularly common problem, ...

Article GUID: 37385392

Author(s): Shamshiri MA; Krzyzak A; Kowal M; Korbicz J;

Microscopic analysis of breast cancer images is the primary task in diagnosing cancer malignancy. Recent attempts to automate this task have employed deep learning models whose success has depended on large volumes of data, while acquiring annotated data in biomedical domains is time-consuming and may not always be feasible. A typical strategy to address ...

Article GUID: 36758326

Author(s): Luo Z; Amayri M; Fan W; Bouguila N;

Cross-collection topic models extend previous single-collection topic models, such as Latent Dirichlet Allocation (LDA), to multiple collections. The purpose of cross-collection topic modeling is to model document-topic representations and reveal similarities between each topic and differences among groups. However, the restriction of Dirichlet prior and ...

Article GUID: 36685642