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Deformable detection transformers for domain adaptable ultrasound localization microscopy with robustness to point spread function variations

Author(s): Gharamaleki SK; Helfield B; Rivaz H;

Super-resolution imaging has emerged as a rapidly advancing field in diagnostic ultrasound. Ultrasound Localization Microscopy (ULM) achieves sub-wavelength precision in microvasculature imaging by tracking gas microbubbles (MBs) flowing through blood vessels. However, MB localization faces challenges due to dynamic point spread functions (PSFs) caused by ...

Article GUID: 40640235


Inferring concussion history in athletes using pose and ground reaction force estimation and stability analysis of plyometric exercise videos

Author(s): Alves W; Babouras A; Martineau PA; Schutt D; Robbins S; Fevens T;

Concussions present a significant risk to athletes, with females exhibiting higher rates and prolonged recovery times than males. Current sideline concussion detection methods, such as the King-Devick test commonly used as a rapid screening tool designed to evaluate eye movement, attention, language, and cognitive processing abilities suffer from validity ...

Article GUID: 40632382


Statistical or Embodied? Comparing Colorseeing, Colorblind, Painters, and Large Language Models in Their Processing of Color Metaphors

Author(s): Nadler EO; Guilbeault D; Ringold SM; Williamson TR; Bellemare-Pepin A; Com?a IM; Jerbi K; Narayanan S; Aziz-Zadeh L;

Can metaphorical reasoning involving embodied experience-such as color perception-be learned from the statistics of language alone? Recent work finds that colorblind individuals robustly understand and reason abstractly about color, implying that color associations in everyday language might cont ...

Article GUID: 40621800


Application of machine learning for predicting the incubation period of water droplet erosion in metals

Author(s): AlHammad K; Medraj M; Tembely M;

Water droplet erosion (WDE) is a critical degradation phenomenon that significantly affects component lifespan and performance in power generation, aerospace, and wind energy industries. The incubation period-the initial phase before visible material loss occurs-is particularly crucial for maintenance planning and material selection yet remains challengin ...

Article GUID: 40612685


Comprehensive review of reinforcement learning for medical ultrasound imaging

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

Medical Ultrasound (US) imaging has seen increasing demands over the past years, becoming one of the most preferred imaging modalities in clinical practice due to its affordability, portability, and real-time capabilities. However, it faces several challenges that limit its applicability, such as ...

Article GUID: 40567264


Machine learning innovations in CPR: a comprehensive survey on enhanced resuscitation techniques

Author(s): Islam S; Rjoub G; Elmekki H; Bentahar J; Pedrycz W; Cohen R;

This survey paper explores the transformative role of Machine Learning (ML) and Artificial Intelligence (AI) in Cardiopulmonary Resuscitation (CPR), marking a paradigm shift from conventional, manually driven resuscitation practices to intelligent, data-driven interventions. It examines the evolution of CPR through the lens of predictive modeling, AI-enha ...

Article GUID: 40336660


CASCADE-FSL: Few-shot learning for collateral evaluation in ischemic stroke

Author(s): Aktar M; Tampieri D; Xiao Y; Rivaz H; Kersten-Oertel M;

Assessing collateral circulation is essential in determining the best treatment for ischemic stroke patients as good collaterals lead to different treatment options, i.e., thrombectomy, whereas poor collaterals can adversely affect the treatment by leading to excess bleeding and eventually death. To reduce inter- and intra-rater variability and save time ...

Article GUID: 40250214


Clustering and Interpretability of Residential Electricity Demand Profiles

Author(s): Kallel S; Amayri M; Bouguila N;

Efficient energy management relies on uncovering meaningful consumption patterns from large-scale electricity load demand profiles. With the widespread adoption of sensor technologies such as smart meters and IoT-based monitoring systems, granular and real-time electricity usage data have become available, enabling deeper insights into consumption behavio ...

Article GUID: 40218540


Large language models deconstruct the clinical intuition behind diagnosing autism

Author(s): Stanley J; Rabot E; Reddy S; Belilovsky E; Mottron L; Bzdok D;

Efforts to use genome-wide assays or brain scans to diagnose autism have seen diminishing returns. Yet the clinical intuition of healthcare professionals, based on longstanding first-hand experience, remains the gold standard for diagnosis of autism. We leveraged deep learning to deconstruct and interrogate the logic of expert clinician intuition from cli ...

Article GUID: 40147442


Integrating past experiences

Author(s): Leir TMW; Gardner MPH;

New results help address a longstanding debate regarding which learning strategies allow animals to anticipate negative events based on past associations between sensory stimuli.

Article GUID: 40146623


CACTUS: An open dataset and framework for automated Cardiac Assessment and Classification of Ultrasound images using deep transfer learning

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


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