ABSTRACT
OBJECTIVE: This scoping review aims to assess the current research landscape of the application and use of large language models (LLMs) and generative Artificial Intelligence (AI), through tools such as ChatGPT in telehealth. Additionally, the review seeks to identify key areas for future research, with a particular focus on AI ethics considerations for responsible use and ensuring trustworthy AI. MATERIALS AND METHODS: Following the scoping review methodological framework, a search strategy was conducted across 6 databases. To structure our review, we employed AI ethics guidelines and principles, constructing a concept matrix for investigating the responsible use of AI in telehealth. Using the concept matrix in our review enabled the identification of gaps in the literature and informed future research directions. RESULTS: Twenty studies were included in the review. Among the included studies, 5 were empirical, and 15 were reviews and perspectives focusing on different telehealth applications and healthcare contexts. Benefit and reliability concepts were frequently discussed in these studies. Privacy, security, and accountability were peripheral themes, with transparency, explainability, human agency, and contestability lacking conceptual or empirical exploration. CONCLUSION: The findings emphasized the potential of LLMs, especially ChatGPT, in telehealth. They provide insights into understanding the use of LLMs, enhancing telehealth services, and taking ethical considerations into account. By proposing three future research directions with a focus on responsible use, this review further contributes to the advancement of this emerging phenomenon of healthcare AI.
ABSTRACT
With the construction and deployment of seafloor observatories around the world, massive amounts of oceanographic measurement data were gathered and transmitted to data centers. The increase in the amount of observed data not only provides support for marine scientific research but also raises the requirements for data quality control, as scientists must ensure that their research outcomes come from high-quality data. In this paper, we first analyzed and defined data quality problems occurring in the East China Sea Seafloor Observatory System (ECSSOS). We then proposed a method to detect and repair the data quality problems of seafloor observatories. Incorporating data statistics and expert knowledge from domain specialists, the proposed method consists of three parts: a general pretest to preprocess data and provide a router for further processing, data outlier detection methods to label suspect data points, and a data interpolation method to fill up missing and suspect data. The autoregressive integrated moving average (ARIMA) model was improved and applied to seafloor observatory data quality control by using a sliding window and cleaning the input modeling data. Furthermore, a quality control flag system was also proposed and applied to describe data quality control results and processing procedure information. The real observed data in ECSSOS were used to implement and test the proposed method. The results demonstrated that the proposed method performed effectively at detecting and repairing data quality problems for seafloor observatory data.
ABSTRACT
The utilization and impact of parallel synthesis on lead exploration around initial hit oxindole (1) are described. The emergent SAR, analogue design and functional impact will also be detailed.
Subject(s)
Adjuvants, Immunologic/chemistry , Protein-Tyrosine Kinases/chemistry , Protein-Tyrosine Kinases/immunology , Animals , Binding Sites , Cell Division/drug effects , Drug Design , Edema/drug therapy , Enzyme Inhibitors/chemistry , Indoles/chemistry , Inhibitory Concentration 50 , Interleukin-2/pharmacology , Janus Kinase 3 , Mice , Oxyquinoline/chemistry , Phosphorylation/drug effects , Protein Binding , Protein Structure, Tertiary , Protein-Tyrosine Kinases/metabolism , Signal Transduction/drug effects , Structure-Activity RelationshipABSTRACT
A series of oxindoles demonstrating inhibition of the phosphorylation of biotinylated substrates of Syk and IgE/Fc epsilon RI triggered basophil cell degranulation has been identified. A study of the SAR around sulfonamide 31 (IC(50)=5 nM, EC(50)=1400 nM) is discussed. The modest cellular activity representative of the sulfonamide series was overcome when the Polar Surface Area was lowered to <110 A(2), leading to the identification of amide 32 (IC(50)=145 nM, EC(50)=100 nM).
