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Reflections on the Potential and Risks of AI for Scientific Article Writing after the AI Endorsement by Some Scientific Publishers: Focusing on Scopus AI.
Actas Esp Psiquiatr
March 2025
Department of Internal Medicine, Dermatology and Psychiatry and Instituto Universitario de Neurociencia (IUNE), Universidad de La Laguna, 38071 San Cristobal de La Laguna, Spain.
The introduction of ChatGPT3 in 2023 disrupted the field of artificial intelligence (AI). ChatGPT uses large language models (LLMs) but has no access to copyrighted material including scientific articles and books. This review is limited by the lack of access to: (1) prior peer-reviewed articles and (2) proprietary information owned by the companies.
View Article and Find Full Text PDFImproved bounding box segmentation technique for crowd anomaly detection with optimal trained convolutional neural network.
Network
March 2025
Department of Biomedical Engineering, Noorul Islam Centre for Higher Education, Kanyakumari, India.
A crucial role in many security and surveillance applications is crowd anomaly detection, where seeing unusual activity helps avert possible threats or interruptions. For precise anomaly identification, current models might not successfully incorporate spatial and temporal features. To overcome these drawbacks, a novel Crowd Anomaly Detection based on Opposition Behavior Learning updated Chimp Optimization Algorithm (CAD-OBLChoA) is proposed in this research to enhance the detection of abnormal crowd behaviours in dynamic environments.
View Article and Find Full Text PDFJLeNeT: Jaccard LeNet for Parkinson's disease detection and severity level classification using voice signal in IoT environment.
Network
March 2025
Department of Computer Science and Engineering, Karpagam College of Engineering, Coimbatore, India.
The neurodegenerative disorder called Parkinson's disease (PD) is one of the most common diseases now a day. In this research, PD is detected and severity classification is done using the proposed Jaccard LeNet (JLeNet) with the help of voice signal in the IoT environment. Here, the IoT simulation is done.
View Article and Find Full Text PDFDevelopment and validation of an interpretable machine learning model for predicting the risk of hepatocellular carcinoma in patients with chronic hepatitis B: a case-control study.
BMC Gastroenterol
March 2025
Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, Guangxi, 530021, China.
Background: The aim of this study was to develop and internally validate an interpretable machine learning (ML) model for predicting the risk of hepatocellular carcinoma (HCC) in patients with chronic hepatitis B (CHB) infection.
Methods: We retrospectively collected clinical data from patients with HCC and CHB treated at the Fourth Affiliated Hospital of Guangxi Medical University from January 2022 to December 2022, including demographics, comorbidities, and laboratory parameters. The datasets were randomly divided into a training set (361 cases) and a validation set (155 cases) in a 7:3 ratio.
A semi-supervised learning approach to classify drug attributes in a pharmacy management database: A STROBE-compliant study.
Medicine (Baltimore)
March 2025
College of Pharmacy, Nanchang Medical College, Nanchang, Jiangxi, China.
With the development of information and communication technology, it has become possible to improve pharmacy management system (PMS) using these technologies. Our study aims to enhance the accuracy of drug attribute classification and recommend appropriate medications to improve patient compliance and treatment outcomes through the use of a semi-supervised learning method combined with artificial intelligence (AI) technology. This study proposed a semi-supervised learning method that integrates various technologies such as PMS, electronic prescriptions, and inventory management with AI to process and analyzed drug data, which enabled dynamic inventory updates and precise drug distribution.
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