Computational techniques have been adopted in medical and biological systems for a long time. There is no doubt that the development and application of computational methods will render great help in better understanding biomedical and biological functions. Large amounts of datasets have been produced by biomedical and biological experiments and simulations. In order for researchers to gain knowledge from original data, nontrivial transformation is necessary, which is regarded as a critical link in the chain of knowledge acquisition, sharing, and reuse. Challenges that have been encountered include: how to efficiently and effectively represent human knowledge in formal computing models, how to take advantage of semantic text mining techniques rather than traditional syntactic text mining, and how to handle security issues during the knowledge sharing and reuse. This paper summarizes the state-of-the-art in these research directions. We aim to provide readers with an introduction of major computing themes to be applied to the medical and biological research.
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http://dx.doi.org/10.4331/wjbc.v3.i2.27 | DOI Listing |
Adv Biotechnol (Singap)
August 2024
State Key Laboratory of Biocontrol, Guangdong Provincial Key Laboratory of Plant Stress Biology and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), School of Life Sciences, Sun Yat-Sen University, Guangzhou, 510275, PR China.
Extreme environments such as hyperarid, hypersaline, hyperthermal environments, and the deep sea harbor diverse microbial communities, which are specially adapted to extreme conditions and are known as extremophiles. These extremophilic organisms have developed unique survival strategies, making them ideal models for studying microbial diversity, evolution, and adaptation to adversity. They also play critical roles in biogeochemical cycles.
View Article and Find Full Text PDFFront Med (Lausanne)
January 2025
Department of Cardiology, Heart Center, First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Introduction: In recent years, the development of artificial intelligence (AI) technologies, including machine learning, deep learning, and large language models, has significantly supported clinical work. Concurrently, the integration of artificial intelligence with the medical field has garnered increasing attention from medical experts. This study undertakes a dynamic and longitudinal bibliometric analysis of AI publications within the healthcare sector over the past three decades to investigate the current status and trends of the fusion between medicine and artificial intelligence.
View Article and Find Full Text PDFHeliyon
January 2025
School of Engineering, Mining Engineering Department, Urmia University, Urmia, Iran.
The rapid impact assessment matrix (RIAM) is a widely utilized tool for evaluating environmental impacts in municipal solid waste management. However, the traditional RIAM (T-RIAM) method includes ambiguities in its scoring classification, which can hinder decision-making accuracy. This study introduces a modified RIAM approach, enhancing classification precision by refining impact categories, making it particularly valuable for projects constrained by time and resources.
View Article and Find Full Text PDFFront Pharmacol
January 2025
Shengli Clinical College of Fujian Medical University, Department of Pharmacy, Fujian Provincial Hospital, Fuzhou University Affiliated Provincial Hospital, Fuzhou, China.
Objective: Although there are certain drug categories associated with heart failure (HF), most of the associated risks are unclear. We investigated the top drugs associated with HF and acute HF (AHF) reported in the FDA Adverse Event Reporting System (FAERS).
Methods: We reviewed publicly available FAERS databases from 2004 to 2023.
J Occup Med Toxicol
January 2025
Indian Council of Medical Research-National Institute for Implementation Research on Non-Communicable Diseases, Jodhpur, 342005, India.
Background: Silicosis remains a major occupational health challenge in India. This review systematically examines the prevalence, risk factors, regional differences, and diagnostic tools specific to India's high-risk industries. Additionally, it assesses policy gaps and offers insights from diverse clinical and qualitative studies, aiming to inform targeted public health interventions and support the development of effective occupational health policies.
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