Ethics

LSWNet: A physics-informed neural network for ultrasonic wavefield prediction and elastic constant inversion in unidirectional CFRP.

Accurate determination of elastic constants is crucial for reliable ultrasonic defect detection in carbon fiber reinforced plastic (CFRP). However, non-destructive in-situ characterization of these constants, particularly via full-waveform inversion techniques, is hindered by the computational cost of wavefield simulations. Based on physics-informed neural networks (PINNs), a novel longitudinal an...

Physics-informed deep learning enables fast ultrahigh-resolution nuclear magnetic resonance spectroscopy.

Pure shift NMR spectroscopy has found extensive applications in exploring the structure, function, and interactions of molecules in an ultrahigh-resolution manner. However, time-consuming data acquisition resulting from additional time dimension for pure shift evolution impedes its further applications. In this study, a general and robust AI-assisted NMR methodology combining non-uniform chunk sam...

Artificial Intelligence-based investigation of filler selection strategies.

OBJECTIVE: Lineup construction relies on matching fillers to the suspect's appearance or to the eyewitness's description of the perpetrator (match to ...

A hybrid federated learning framework with generative AI for privacy-preserving and sustainable security in IOT-enabled smart environments.

The dramatic increase in IoT devices in a smart ecosystem like smart cities, transportation systems, and healthcare and industrial automation has grea...

Awareness, trust, and expectations of AI for glaucoma care among Bulgarian ophthalmologists: Role of demographic factors.

Artificial intelligence (AI) holds promise for enhancing glaucoma screening and management, yet its adoption depends on clinician perceptions, particu...

Validation of histopathology-based deep learning algorithms for detection of actionable non-small cell lung cancer biomarkers.

Non-small cell lung cancer (NSCLC) patient management relies on molecular analysis to determine eligibility for targeted therapy. Furthermore, neoadju...

Resolving energy transfer dynamics in Eu²⁺-activated multi-site phosphors via metaheuristic optimization and physics-informed neural networks.

Multi-exponential fitting has long been the standard approach for luminescence decay analysis, not because it is physically meaningful but because it ...

Quantum-enhanced throughput pathways: Integrating Rodgers' TPM with quantum ethical frameworks for AI-driven cybersecurity.

This integrative conceptual review synthesizes psychological, ethical, and quantum-information perspectives to advance Quantum-Enhanced Throughput Mod...

Charting exposomethics: a roadmap for the ethical foundations of the human exposome project.

BACKGROUND: The Human Exposome Project (HEP) aims to chart lifelong environmental exposures and their biological consequences, furnishing the environm...

Preserving scientific integrity in academic publishing: Navigating artificial intelligence, journal policies and the impact factor as a quality indicator.

The integration of artificial intelligence (AI), the rise of mega-journals, and the manipulation of impact factors present challenges to scientific in...

[Responsible use of AI and robotics in medicine : Opportunities, challenges and perspectives for otorhinolaryngology].

Artificial intelligence (AI) and robotics are transforming the foundations of medical practice. Their integration creates new opportunities for precis...

Preserving scientific integrity in academic publishing: Navigating artificial intelligence, journal policies, and the impact factor as a quality indicator.

UNLABELLED: The integration of artificial intelligence (AI), the rise of mega-journals, and the manipulation of impact factors present challenges to s...

Predicting curcumin release kinetics from nanocarriers using a physics-informed machine learning framework.

BACKGROUND: Curcumin nanoformulations display highly heterogeneous release behaviors, yet the field lacks an integrated framework capable of predictin...

Evaluation of a Problem-Based Learning Program's Effect on Artificial Intelligence Ethics Among Japanese Medical Students: Mixed Methods Study.

BACKGROUND: The rapid advancement of artificial intelligence (AI) has had a substantial impact on medicine, necessitating the integration of AI educat...

Coronary artery segmentation in non-contrast cardiac CT using anatomy-informed contrastive learning and synthetic data.

Non-contrast cardiac CT (NCCT) offers a low-dose, cost-effective alternative to coronary CT angiography (CCTA) for large-scale coronary artery disease...

Attitudes and readiness of nursing students practising in surgical units towards artificial intelligence: a cross-sectional study.

BACKGROUND: In surgical fields at the forefront of technological advancement with both virtual and physical artificial intelligence applications, nurs...

Ethical Considerations for the Use of Artificial Intelligence Tools in Surgery.

Artificial intelligence (AI) is rapidly transforming surgical care, offering unprecedented capabilities in diagnostics, planning, and intraoperative g...

Urban waste management inequities in New York city: a case study on spatial patterns of controlled and uncontrolled street waste and their associated factors.

Comprehensive urban waste management systems, addressing municipal waste collection and construction waste disposal, are essential for maintaining liv...

Characteristics and determinants of artificial intelligence (AI) literacy in Chinese nursing students: A cross-sectional study.

BACKGROUND: Artificial intelligence literacy is essential for nursing students to become competent in navigating contemporary healthcare complexities ...

Defect-parameterized physics-informed neural network for forward and inverse modeling of laser ultrasonic wavefield.

Accurate and efficient non-destructive evaluation (NDE) techniques are essential for ensuring the structural integrity of metallic components, where s...