Results 151 to 160 of about 21,872 (268)

Relationships Among Auditory Discrimination, Adaptive Vocal Learning, and Perilaryngeal Muscle Activation in People With and Without Hyperfunctional Voice Disorders. [PDF]

J Speech Lang Hear Res
Kapsner-Smith MR, Cádiz MD, Knutson M, Eadie TL, Stepp CE.   +4 more
europepmc   +1 more source

From Data to Discovery: Machine Learning–Enabled Intelligent Characterization of Two‐Dimensional Materials

Advanced Intelligent Discovery, EarlyView.
Machine learning serves as a central engine for the intelligent characterization of two‐dimensional materials by integrating multimodal techniques, including optical microscopy, spectroscopy, electron microscopy, and scanning probe microscopy (SPM). This unified framework enables automated, high‐throughput, and quantitative extraction of structural ...
Zhi‐Long Cao, Jia‐Xu Yan
wiley   +1 more source

Large Language Model‐Based Chatbots in Higher Education

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
The use of large language models (LLMs) in higher education can facilitate personalized learning experiences, advance asynchronized learning, and support instructors, students, and researchers across diverse fields. The development of regulations and guidelines that address ethical and legal issues is essential to ensure safe and responsible adaptation
Defne Yigci, Merve Eryilmaz, Ail K. Yetisen, Savas Tasoglu, Aydogan Ozcan   +4 more
wiley   +1 more source

Enhanced Contour-Deviant Mismatch Negativity and Mnemonic Representations in Older Musicians. [PDF]

Eur J Neurosci
Bugos JA, Chow R, Mo S, Rosenbaum RS, Alain C.   +4 more
europepmc   +1 more source

Calibration‐Free Electromyography Motor Intent Decoding Using Large‐Scale Supervised Pretraining

Advanced Intelligent Systems, EarlyView.
Calibration‐free electromyography motor intent decoding is enabled through large‐scale supervised pretraining across heterogeneous datasets. A Spatially Aware Feature‐learning Transformer processes variable channel counts and electrode geometries, allowing transfer across users and recording setups. On a held‐out benchmark, fine‐tuned cross‐user models
Alexander E. Olsson, Nebojša Maleševic, Anders Björkman, Christian Antfolk   +3 more
wiley   +1 more source

Receptive prosody adaptation to contextual feedback in autistic young adults. [PDF]

Front Psychol
Kurumada C, Rivera R, Layton C, Allen PD, Bennetto L.   +4 more
europepmc   +1 more source

Human‐in‐the‐Loop Object Segmentation for 3D Gaussian Splatting via Finger‐based VR Interface

Advanced Intelligent Systems, EarlyView.
This study introduces a human‐in‐the‐loop segmentation framework for 3D Gaussian Splatting that integrates real‐time optimization with intuitive VR‐based finger prompting. Compared with existing automatic, learning‐based methods, it achieves significantly higher accuracy and reduced segmentation time.
Yongseok Lee, Hyunreal Park, Hyunsu Kim, Harim Ji, Dongho Yee, Dongjun Lee   +5 more
wiley   +1 more source

Early Identification of DLD in Paediatric Practice: A Pilot Validation of the CLAP Screening Tool in Italian Outpatient Settings. [PDF]

Int J Lang Commun Disord
Ricotti A, Dimitri D, Nebbia F, Carpino A, Charrier L, Cillis G, Bonzo S, Actis M, Grosso E, Malorgio E, Gambotto S, Borsotti L, Gallo S, Marnetto F, Parodi E.   +14 more
europepmc   +1 more source

Retinal Vessel Segmentation: A Comprehensive Review From Classical Methods to Deep Learning Advances (1982–2025)

Advanced Intelligent Systems, EarlyView.
Four decades of retinal vessel segmentation research (1982–2025) are synthesized, spanning classical image processing, machine learning, and deep learning paradigms. A meta‐analysis of 428 studies establishes a unified taxonomy and highlights performance trends, generalization capabilities, and clinical relevance.
Avinash Bansal, Jan Kubíček, Jana Bahrová, Alice Varyšová, Martin Augustýnek, Marek Penhaker, Juraj Timkovič   +6 more
wiley   +1 more source

Validation of the Adaptive Danish Sentence Test (DAST): Normative Data from a Template-Based, Linguistically Rich Sentence-in-Noise Test. [PDF]

Audiol Res
Kressner AA, Jensen-Rico KM, Pedersen AK, Bramsløw L, Kirkwood B.   +4 more
europepmc   +1 more source