Results 81 to 90 of about 117,002 (264)

Adaptive Data Augmentation for Thompson Sampling

CoRR
In linear contextual bandits, the objective is to select actions that maximize cumulative rewards, modeled as a linear function with unknown parameters. Although Thompson Sampling performs well empirically, it does not achieve optimal regret bounds.
openaire   +2 more sources

Integrated PANoptosis Profiling Identifies Immunosuppressive Subtypes and a Prognostic Signature With Functional Validation of MLKL in Glioblastoma

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective The prognosis of glioblastoma (GBM) remains highly unfavorable, largely due to high tumor heterogeneity and an immunosuppressive microenvironment. However, the functional role of PANoptosis in this context is poorly understood. Methods Patients were stratified via K‐means clustering. A risk score model was constructed using prognosis‐
Langfei Tian, Minghui Zhao, Yuanbo Hu, Kaiyue Wang, Haiguang Liu, Zetong Bai, Kebin Zheng   +6 more
wiley   +1 more source

Parkinson’s Disease Detection Based on Spectrogram-Deep Convolutional Generative Adversarial Network Sample Augmentation

IEEE Access, 2020
As an essential biological feature of human beings, voiceprint is increasingly used in medical research and diagnosis, especially in identifying Parkinson's Disease (PD). This paper proposes a Spectrogram Deep Convolutional Generative Adversarial Network
Zhi-Jing Xu, Rong-Fei Wang, Juan Wang, Da-Hai Yu   +3 more
doaj   +1 more source

Safety and Efficacy of GLP‐1 Receptor Agonists in Adults With Epilepsy, Obesity, and Type 2 Diabetes

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Managing obesity in patients with epilepsy is complicated by the weight‐gaining properties of essential antiseizure medications (ASMs) such as valproate and pregabalin. We evaluated the safety and efficacy of initiating glucagon‐like peptide‐1 receptor agonists (GLP‐1 RAs) in this population.
Hyoshin Son, Inyoung Hwang, Sang Won Lee, Yun Kim   +3 more
wiley   +1 more source

Artificial Intelligence in Systemic Sclerosis: Clinical Applications, Challenges, and Future Directions

Arthritis Care &Research, EarlyView.
Systemic sclerosis (SSc) is a rare autoimmune disease defined by immune dysregulation, vasculopathy, and progressive fibrosis of the skin and internal organs. Despite advances in care, major complications such as interstitial lung disease (ILD) and myocardial involvement remain the leading causes of morbidity and mortality.
Cristiana Sieiro Santos, José Miguel Sequí‐Sabater, Diego Benavent   +2 more
wiley   +1 more source

Facial cosmetic therapy use amongst patients with systemic sclerosis: an Australian cohort study

Arthritis Care &Research, Accepted Article.
Objective Systemic sclerosis (SSc) is associated with numerous facial manifestations for which patients may engage in cosmetic therapies. It is unclear how patients with SSc use these therapies. This study sought to characterise patient engagement and experiences with cosmetic therapies for SSc‐related and non‐SSc‐related facial changes.
Zachary Warren, Diane Apostolopoulos, Gene‐Siew Ngian, Amanda M Saracino, Laura Ross, Nava Ferdowsi, Jennifer Walker, Cindy Hall, Kim Griggs, Susanna Proudman, Wendy Stevens, Joanne Sahhar   +11 more
wiley   +1 more source

Soil sampling with drones and augmented reality in precision agriculture

Computers and Electronics in Agriculture, 2018
Abstract Soil sampling is an important tool to gather information for making proper decisions regarding the fertilization of fields. Depending on the national regulations, the minimum frequency may be once per five years and spatially every ten hectares. For precision farming purposes, this is not sufficient. In precision farming, the challenge is to
Oksanen, Timo, Huuskonen, Janna
openaire   +3 more sources

Observer‐Based Adaptive Event‐Triggered Tracking Control for Fuzzy TS Systems With Premise Mismatch

International Journal of Adaptive Control and Signal Processing, EarlyView.
This paper presents an adaptive logistic event‐triggered observer‐based tracking controller for Takagi‐Sugeno fuzzy systems under constrained inputs and network delays. Leveraging a hybrid LMI and Secretary Bird Optimization approach, this strategy significantly minimizes communication overhead and computational burden while ensuring optimal reference ...
Oussama Djadane, Salama Makni, Mourad Kchaou, Ahmed El Hajjaji   +3 more
wiley   +1 more source

Image Data Augmentation for SAR Sensor via Generative Adversarial Nets

IEEE Access, 2019
As a mission-critical sensor, SAR has been applied in environmental monitoring and battlefield surveillance; moreover, SAR target recognition is one of the most important applications of SAR technology.
Zongyong Cui, Mingrui Zhang, Zongjie Cao, Changjie Cao   +3 more
doaj   +1 more source

dynoGP: Deep Gaussian Processes for Dynamic System Identification

International Journal of Adaptive Control and Signal Processing, EarlyView.
This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli, Marco Forgione, Dario Piga   +2 more
wiley   +1 more source