Bmcbioinformatics.biomedcentral.com
A score-based method of immune status evaluation for healthy
WEBWith the COVID-19 outbreak, an increasing number of individuals are concerned about their health, particularly their immune status. However, as of now, there is no available algorithm that effectively assesses the immune status of normal, healthy individuals. In response to this, a new score-based method is proposed that utilizes …
Actived: 9 days ago
URL: https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-023-05603-7
Current trend and development in bioinformatics research
WEBThese articles reflect current trend and development in bioinformatics research. The supplement to BMC Bioinformatics was proposed to launch during the BIOCOMP’19—The 2019 International Conference on Bioinformatics and Computational Biology held from July 29 to August 01, 2019 in Las Vegas, Nevada. In this congress, a …
Graph4Med: a web application and a graph database for …
WEBMedical databases normally contain large amounts of data in a variety of forms. Although they grant significant insights into diagnosis and treatment, implementing data exploration into current medical databases is challenging since these are often based on a relational schema and cannot be used to easily extract information for cohort …
Automatic disease prediction from human gut metagenomic data …
WEBThe human body is the habitat for trillions of diverse and complex microbes (microbiota or microbiome). These microbes reside in various body sites (skin, gut, ear, mouth, nose, stool etc.) and play a vital role in (a) shaping and controlling human health, (b) developing the human immune system and (c) affecting human metabolism [].The most …
Extracting cancer concepts from clinical notes using natural …
WEBOne of the significant public health concerns is cancer. According to the World Health Organization (WHO) report in 2019, this disease is the leading cause of death worldwide [].GLOBOCAN (The Global Cancer Observatory) estimated [] about 10 million deaths from cancer in 2020 (i.e., one in every six patients with cancer) [].The global …
Prediction of heart disease and classifiers’ sensitivity analysis
WEBHeart disease (HD) is one of the most common diseases nowadays, and an early diagnosis of such a disease is a crucial task for many health care providers to prevent their patients for such a disease and to save lives. In this paper, a comparative analysis of different classifiers was performed for the classification of the Heart Disease dataset in …
Machine learning to analyse omic-data for COVID-19 diagnosis …
WEBBackground With the global spread of COVID-19, the world has seen many patients, including many severe cases. The rapid development of machine learning (ML) has made significant disease diagnosis and prediction achievements. Current studies have confirmed that omics data at the host level can reflect the development process and …
Predicting blood pressure from physiological index data using the …
WEBBackground Blood pressure diseases have increasingly been identified as among the main factors threatening human health. How to accurately and conveniently measure blood pressure is the key to the implementation of effective prevention and control measures for blood pressure diseases. Traditional blood pressure measurement …
A new cross-platform architecture for epi-info software suite
WEBThe Epi-Info software suite, built and maintained by the Centers for Disease Control and Prevention (CDC), is widely used by epidemiologists and public health researchers to collect and analyze public health data, especially in the event of outbreaks such as Ebola and Zika. As it exists today, Epi-Info Desktop runs only on the Windows …
Semi-quantitative group testing for efficient and accurate qPCR
WEBPathogenic infections pose a significant threat to global health, affecting millions of people every year and presenting substantial challenges to healthcare systems worldwide. Efficient and timely testing plays a critical role in disease control and transmission prevention. Group testing is a well-established method for reducing the …
Twnbiome: a public database of the healthy Taiwanese gut …
WEBWith new advances in next generation sequencing (NGS) technology at reduced costs, research on bacterial genomes in the environment has become affordable. Compared to traditional methods, NGS provides high-throughput sequencing reads and the ability to identify many species in the microbiome that were previously unknown. …
Disease ontologies for knowledge graphs
WEBDisease ontologies are used for annotation, integration and analysis of biological data, and knowledge graph construction. The range and diversity of disease ontologies are high due to various specific areas they are used in, e.g. medical practice, rare disease domain, biological experiments and biobanks. To build a biomedical …
Advances and challenges in Bioinformatics and Biomedical …
WEBThis Supplement issue, presents five research articles which are distributed, mainly due to the subject they address, from the 8th International Work-Conference on Bioinformatics and Biomedical Engineering (IWBBIO 2020), which was held on line, during September, 30th–2nd October, 2020. These contributions have been chosen because of …
Biomedical named entity recognition using deep neural networks …
WEBBackground In biomedical text mining, named entity recognition (NER) is an important task used to extract information from biomedical articles. Previously proposed methods for NER are dictionary- or rule-based methods and machine learning approaches. However, these traditional approaches are heavily reliant on large-scale dictionaries, …
A machine learning-based data mining in medical examination …
WEBBiological age (BA) has been recognized as a more accurate indicator of aging than chronological age (CA). However, the current limitations include: insufficient attention to the incompleteness of medical data for constructing BA; Lack of machine learning-based BA (ML-BA) on the Chinese population; Neglect of the influence of …
Clinlabomics: leveraging clinical laboratory data by data mining
WEBThe technology of “omics” (genomics, proteomics, transcriptomics, metabolomics, etc.) is an emerging practice. We can more accurately predict and understand disease risks and formulate treatments for more specific and homogeneous populations by using big data, technologies, and methods [1, 2] (Fig. 1A).Since the …
Visually guided classification trees for analyzing chronic patients
WEBIn this section we present the results provided by the visually guided classification trees. We analyzed performance in terms of accuracy, F1-score and confusion matrices, and drew clinical conclusions regarding the features considered in each decision tree. Specifically, clinicians constructed five visually guided decision trees to
KnowLife: a versatile approach for constructing a large knowledge …
WEBBackground Biomedical knowledge bases (KB’s) have become important assets in life sciences. Prior work on KB construction has three major limitations. First, most biomedical KBs are manually built and curated, and cannot keep up with the rate at which new findings are published. Second, for automatic information extraction (IE), the text …
Computer vision digitization of smartphone images of anesthesia …
WEBBackground In low-middle income countries, healthcare providers primarily use paper health records for capturing data. Paper health records are utilized predominately due to the prohibitive cost of acquisition and maintenance of automated data capture devices and electronic medical records. Data recorded on paper health records …
Deep self-supervised machine learning algorithms with a novel …
WEBBlood test is extensively performed for screening, diagnoses and surveillance purposes. Although it is possible to automatically evaluate the raw blood test data with the advanced deep self-supervised machine learning approaches, it has not been profoundly investigated and implemented yet. This paper proposes deep machine learning …
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