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Divergent creativity in humans and large language models

Author(s): Bellemare-Pepin A; Lespinasse F; Thölke P; Harel Y; Mathewson K; Olson JA; Bengio Y; Jerbi K;

The recent surge of Large Language Models (LLMs) has led to claims that they are approaching a level of creativity akin to human capabilities. This idea has sparked a blend of excitement and apprehension. However, a critical piece that has been missing in this discourse is a systematic evaluation ...

Article GUID: 41565675


Towards smart PFAS management: Integrating artificial intelligence in water and wastewater systems

Author(s): Yaghoobian S; An J; Jeong DW; Hwang JH;

Artificial intelligence (AI) and machine learning (ML) are increasingly integrated into Per- and polyfluoroalkyl substances (PFAS) research; however, the field remains fragmented with substantial variation in modeling objectives. This review provides one of the most comprehensive and detailed syntheses to date of AI/ML methods across the PFAS contaminatio ...

Article GUID: 41483514


Strengthening community-based fisheries monitoring programs with Indigenous perspectives

Author(s): Dewan K; Mulrennan ME; Georgekish E;

Community-based monitoring (CBM) programs are increasingly recognized as essential for adaptive environmental stewardship. Yet, the CBM literature often highlights successful cases and privileges evaluations by external experts over those of community members themselves. To address this gap, we drew on insights from 23 semistructured interviews with Cree ...

Article GUID: 41332192


Automated abdominal aortic calcification and trabecular bone score independently predict incident fracture during routine osteoporosis screening

Author(s): Gebre AK; Sim M; Gilani SZ; Saleem A; Smith C; Hans D; Reid S; Monchka BA; Kimelman D; Jozani MJ; Schousboe JT; Lewis JR; Leslie WD;

Abdominal aortic calcification (AAC), a marker of subclinical cardiovascular disease, has previously shown to be associated with low bone mineral density (BMD) and fracture. However, it remains unclear whether AAC is associated with trabecular bone score (TBS), a gray-level textural measure, or w ...

Article GUID: 41071096


An examination of the quinic acid utilization genes in Aspergillus niger reveals the involvement of two pH-dependent permeases

Author(s): Sgro M; Reid ID; Arentshorst M; Ram AFJ; Tsang A;

Many microorganisms are able to use plant-derived aromatic and cyclic compounds like the common plant secondary metabolite quinic acid as carbon and energy sources. In fungi, three enzymatic steps convert quinic acid into the common intermediate protocatechuic acid, which is then further converted into TCA cycle intermediates. The genes encoding these thr ...

Article GUID: 40853219


Deep learning-based feature discovery for decoding phenotypic plasticity in pediatric high-grade gliomas single-cell transcriptomics

Author(s): Abicumaran Uthamacumaran

Advancements in AI-powered systems medicine have revolutionized biomarker discovery through emergent and explainable features. By use of complex network dynamics and graph-based machine learning, we identified critical determinants of lineage-specific plasticity across the single-cell transcriptomics of pediatric high-grade glioma (pHGGs) subtypes: IDHWT ...

Article GUID: 40848317


Evolution from the physical process-based approaches to machine learning approaches to predicting urban floods: a literature review

Author(s): Md Shike Bin Mazid Anik

Urban flooding has become a growing concern for many cities due to accelerating urbanisation, changing weather, and drainage system aging. Earlier studies of floods have taken primarily the traditional process-based approach to predicting urban floods, offering limited exploration of recent advancements in AI-driven, real-time, and community-integrated ap ...

Article GUID: 40692624


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


Protecting shorelines in Canadian Indigenous communities: Environmental challenges, policy interventions, and mitigation technologies

Author(s): Iravani R; Biagi M; Laforest S; Lee K; Isaacman L; Chen Z; An C;

There is growing concern regarding the environmental protection of shorelines in Canadian Indigenous communities, as these regions face increasing threats from pollution and environmental degradation. This review examines various types of pollution affecting coastal Indigenous communities, such as oil spills, plastic waste, industrial runoff, and other co ...

Article GUID: 40554913


Emerging Image-Guided Navigation Techniques for Cardiovascular Interventions: A Scoping Review

Author(s): Roshanfar M; Salimi M; Jang SJ; Sinusas AJ; Kim J; Mosadegh B;

Background: Image-guided navigation has revolutionized precision cardiac interventions, yet current technologies face critical limitations in real-time guidance and procedural accuracy. Method: Here, we comprehensively evaluate state-of-the-art imaging modalities, from conventional fluoroscopy to emerging hybrid systems, analyzing their applications acros ...

Article GUID: 40428106


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


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