Results 281 to 290 of about 3,424,284 (379)

Applications of Artificial Intelligence in Neurological Voice Disorders

World Journal of Otorhinolaryngology - Head and Neck Surgery, EarlyView.
ABSTRACT Neurological voice disorders, such as Parkinson's disease, laryngeal dystonia, and stroke‐induced dysarthria, significantly impact speech production and communication. Traditional diagnostic methods rely on subjective assessment, whereas artificial intelligence (AI) offers objective, noninvasive, and scalable solutions for voice analysis. This
Dongren Yao, Aki Koivu, Kristina Simonyan   +2 more
wiley   +1 more source

Correction to: Semantic units: organizing knowledge graphs into semantically meaningful units of representation. [PDF]

J Biomed Semantics
Vogt L, Kuhn T, Hoehndorf R.
europepmc   +1 more source

A novel voice in head actor critic reinforcement learning with human feedback framework for enhanced robot navigation. [PDF]

Sci Rep
Sharma A, Balasundaram A, Shaik A, Vaithilingam CA.   +3 more
europepmc   +1 more source

Syntax and Semantics of Passive and Related Constructions in Korean: A Computational Implementation

, 2008
Jong‐Bok Kim, 양재형
openalex   +1 more source

A common framework for semantic memory and semantic composition

Law RM, Hauk O, Lambon Ralph MA.
europepmc   +1 more source

Consistent semantic representation learning for out-of-distribution molecular property prediction. [PDF]

Brief Bioinform
Wen X, Liu H, Long W, Wei S, Zhu R.
europepmc   +1 more source

Unitary-circuit semantics for measurement-based computations

, 2009
Niel de Beaudrap
openalex   +2 more sources

AML‐Net: Attention‐based multi‐scale lightweight model for brain tumour segmentation in internet of medical things

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract Brain tumour segmentation employing MRI images is important for disease diagnosis, monitoring, and treatment planning. Till now, many encoder‐decoder architectures have been developed for this purpose, with U‐Net being the most extensively utilised. However, these architectures require a lot of parameters to train and have a semantic gap. Some
Muhammad Zeeshan Aslam, Basit Raza, Muhammad Faheem, Aadil Raza   +3 more
wiley   +1 more source

A bibliometric analysis of metonymy in SSCI-indexed research (2000-2023): retrospect and prospect. [PDF]

Front Psychol
Sun Y, Lin M.
europepmc   +1 more source

Review on enhancing clinical decision support system using machine learning

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract Clinical decision‐making is a complex patient‐centred process. For an informed clinical decision, the input data is very thorough ranging from detailed family history, environmental history, social history, health‐risk assessments, and prior relevant medical cases.
Anum Masood, Usman Naseem, Junaid Rashid, Jungeun Kim, Imran Razzak   +4 more
wiley   +1 more source