Ensemble deep learning and EfficientNet for accurate diagnosis of diabetic retinopathy.

Diabetic Retinopathy (DR) stands as a significant global cause of vision impairment, underscoring the critical importance of early detection in mitigating its impact. Addressing this challenge head-on, this study introduces an innovative deep learning framework tailored for DR diagnosis. The proposed framework utilizes the EfficientNetB0 architecture to classify diabetic retinopathy severity levels from retinal images.

Advance drought prediction through rainfall forecasting with hybrid deep learning model.

Drought is a natural disaster that can affect a larger area over time. Damage caused by the drought can only be reduced through its accurate prediction. In this context, we proposed a hybrid stacked model for rainfall prediction, which is crucial for effective drought forecasting and management.

Mapping the Health and Medical Research Excellence in Nepal: A Study of High-Cited Papers During 1994-2023.

Background: A bibliometric analysis was performed to map the current status and development trends in medical research in Nepal. It aims to visualize research hotspots within this field and provide effective guidance for future research directions.

Methods: A systematic search of the Scopus database was performed to identify high-cited papers (HCPs) on medical research in Nepal between January 1, 1994, and December 31, 2023.

Scholarly trends in global orthopedics research published through the journal of orthopaedics: A bibliometric analysis from 2013 to 2024.

Background And Aims: We provide an overview and data visualization trends of orthopaedic research published by the Journal of Orthopedics (JOO) from 2013 to 2024.

Methods: We used Scopus database to retrieve all articles published by the JOO from 2013 to 2024, as of 15.7.

Scientometric analysis of global research on delayed and nonunion of fractures (2004-2023): Insights from the Web of Science core collections.

Background And Aims: Nonunion of fractures continue to be the most challenging complication. The increased interest in this area has been anecdotally recognized through published research. The study aimed to conduct a comprehensive bibliometric analysis of global research on nonunion and delayed union of fractures to identify key trends, hotspots, and potential areas for future research development.

Scientometric analysis of global publications on prediabetes and osteoporosis: 1994-2023.

Background And Aims: Prediabetes and osteoporosis are two commonly prevalent diseases that can have interconnected implications for overall well-being. There is a paucity of literature on "prediabetes and osteoporosis". We aimed to assess the current state of cross-sectional studies involving osteoporosis and prediabetes as well as their bibliometric features.

Indias Publications on Rheumatoid Arthritis: A Bibliometric Analysis of Research Output from 1994 to 2023 A.D.

Background: Over the years, several studies have been conducted by utilizing bibliometric techniques to reveal research trends in various sub-fields of medical sciences, including arthritis research. Although no bibliometric study has been conducted Methods:In this study, we examined the publications of Indian scholars on Rheumatoid Arthritis (RA) in the last three decades, using various quantitative and qualitative bibliometric indicators. The publications on RA (from 1994-2023) in the Scopus database were identified, analysed and evaluated using a pre-defined search strategy, and specialised software.

Privacy-Centric AI and IoT Solutions for Smart Rural Farm Monitoring and Control.

The integration of artificial intelligence (AI) and the Internet of Things (IoT) in agriculture has significantly transformed rural farming. However, the adoption of these technologies has also introduced privacy and security concerns, particularly unauthorized breaches and cyber-attacks on data collected from IoT devices and sensitive information. The present study addresses these concerns by developing a comprehensive framework that provides practical, privacy-centric AI and IoT solutions for monitoring smart rural farms.

Global Stem Cell Research in Orthopaedics: A Bibliometric Study from 1995 to 2020.

Background: The research field of stem cell-based therapies in orthopaedics has witnessed significant growth in the recent past. We aimed to identify and analyze the bibliometric characteristics of the global highly cited papers (HCPs) in stem cell research in orthopaedics.

Methods: This study relied on secondary data extracted from Scopus, Elsevier's abstract and citation database.

Global Research on Osteoarthritis During 1994-2023: A Scientometric Assessment of Publications and Citations.

Introduction: This study presents a global research scenario in the broad domain of osteoarthritis (OA) research, using quantitative and qualitative publication and citation indicators.

Methods: The study is based on 45,368 global publications, sourced from the Scopus bibliographical database, covering three decades (1994-2023). We studied the performance of the top 12 developed and top 12 developing countries.

Global research output and highly-cited publications on prosthetic joint infections: A bibliometric analysis (2003-2022).

Backgroundand Aims: Prosthetic Joint Infection (PJI) is a serious clinical problem after Arthroplasty. The research field on PJI is emerging, but there is a paucity of information on the most impactful publications on it. This prompted us to conduct a bibliometric analysis of the global research output, from 2003 to 2022, to identify the growth of publications, the key players in this research field and to evaluate the characteristics of highly-cited publications (HCPs) on the PJI.

Liver Transplantation Research from India During the Last 25 Years: 1998-2022.

Background And Aims: Liver transplant surgery has been performed in India for the last 25 years. We aimed to analyse the trends, characteristics, and key elements in the field of liver transplantation research from India.

Methods: On April 23, 2023, we conducted a search of the Scopus database for the literature on liver transplantation research, using a well-defined search strategy.

Research on Non-alcoholic Fatty Liver Disease From Indian Subcontinent: A Bibliometric Analysis of Publications During 2001-2022.

Introduction: The non-alcoholic fatty liver disease (NAFLD) is common in the Indian Subcontinent. We aimed to examine the bibliometric characteristics of the publications arising from the countries of the Indian Subcontinent on NAFLD, over the last two decades.

Methods: Publications on NAFLD from Indian Subcontinent during the period of 2001-2022 were retrieved from the Scopus database.

Top 100 highly cited papers from India on COVID-19 research: A bibliometric analysis of the core literature.

Background And Aims: This study aimed to assess the current status of India's COVID-19 research from the top 100 most cited papers, using bibliometrics methods and indicators and suggest strengths and weaknesses.

Methodology: Publications on COVID-19 research from India between December 2019 and 22 August 2023 were retrieved from the Scopus database. From 37101 studies retrieved, the first top 100 Highly Cited Papers (HCPs) having received 270 to 2931 citations, were identified.

Co-Design Dedicated System for Efficient Object Tracking Using Swarm Intelligence-Oriented Search Strategies.

The template matching technique is one of the most applied methods to find patterns in images, in which a reduced-size image, called a target, is searched within another image that represents the overall environment. In this work, template matching is used via a co-design system. A hardware coprocessor is designed for the computationally demanding step of template matching, which is the calculation of the normalized cross-correlation coefficient.

Scientometric analysis of highly cited papers on avascular necrosis of the femoral head from 1991 to 2022.

Introduction: A highly cited paper (HCP) is considered a landmark that can influence both research and clinical practice. The characteristics of HCPs in avascular necrosis of the femoral head (AVNFH) were identified and the research status was explored in a scientometric analysis.

Methods: The present bibliometric analysis were based on the Scopus database from 1991 to 2021.

Analysis of retail sector research evolution and trends during COVID-19.

The purpose of this study is to analysis the evolution of the retail sector during the COVID-19 period and to identify future research issues. Scopus databases were searched for articles published in English between 2020 and 2022 to discover current trends and concerns in the retail industry. A total of 1071 empirical and nonempirical studies were compiled as a result of the evaluation process.

UBXN2A suppresses the Rictor-mTORC2 signaling pathway, an established tumorigenic pathway in human colorectal cancer.

The mTORC2 pathway plays a critical role in promoting tumor progression in human colorectal cancer (CRC). The regulatory mechanisms for this signaling pathway are only partially understood. We previously identified UBXN2A as a novel tumor suppressor protein in CRCs and hypothesized that UBXN2A suppresses the mTORC2 pathway, thereby inhibiting CRC growth and metastasis.

Enhancing Electrocardiogram Classification with Multiple Datasets and Distant Transfer Learning.

Electrocardiogram classification is crucial for various applications such as the medical diagnosis of cardiovascular diseases, the level of heart damage, and stress. One of the typical challenges of electrocardiogram classification problems is the small size of the datasets, which may lead to limitation in the performance of the classification models, particularly for models based on deep-learning algorithms. Transfer learning has demonstrated effectiveness in transferring knowledge from a source model with a similar domain and can enhance the performance of the target model.

Privacy protection framework for face recognition in edge-based Internet of Things.

Edge computing (EC) gets the Internet of Things (IoT)-based face recognition systems out of trouble caused by limited storage and computing resources of local or mobile terminals. However, data privacy leak remains a concerning problem. Previous studies only focused on some stages of face data processing, while this study focuses on the privacy protection of face data throughout its entire life cycle.