Web learning

BACKGROUND: Artificial intelligence (AI) has garnered considerable attention in the context of sepsis research, particularly in personalized diagnosis and treatment. Conducting a bibliometric analysis of existing publications can offer a broad overview of the field and identify current research trends and future research directions. OBJECTIVE: The objective of this study is to leverage bibliometric data to provide a comprehensive overview of the application of AI in sepsis...

The COVID-19 pandemic disrupted regular global activities in every possible way. This pandemic, caused by the transmission of the infectious Coronavirus, is characterized by main symptoms such as fever, fatigue, cough, and loss of smell. A current key focus of the scientific community is to develop automated methods that can effectively identify COVID-19 patients and are also adaptable for foreseen future virus outbreaks. To classify COVID-19 suspects, it is required to use contactless automatic measurements of more than one symptom...

Recently, there has been a trend of designing neural data structures to go beyond handcrafted data structures by leveraging patterns of data distributions for better accuracy and adaptivity. Sketches are widely used data structures in real-time web analysis, network monitoring, and self-driving to estimate item frequencies of data streams within limited space. However, existing sketches have not fully exploited the patterns of the data stream distributions, making it challenging to tightly couple them with neural networks that excel at memorizing pattern information...

Urban environments, characterized by bustling mass transit systems and high population density, host a complex web of microorganisms that impact microbial interactions. These urban microbiomes, influenced by diverse demographics and constant human movement, are vital for understanding microbial dynamics. We explore urban metagenomics, utilizing an extensive dataset from the Metagenomics & Metadesign of Subways & Urban Biomes (MetaSUB) consortium, and investigate antimicrobial resistance (AMR) patterns...

OBJECTIVES: Combination therapy of lenvatinib and immune checkpoint inhibitors (CLICI) has emerged as a promising approach for managing unresectable hepatocellular carcinoma (HCC). However, the response to such treatment is observed in only a subset of patients, underscoring the pressing need for reliable methods to identify potential responders. MATERIALS & METHODS: This was a retrospective analysis involving 120 patients with unresectable HCC. They were divided into training (n = 72) and validation (n = 48) cohorts...

SUMMARY: Massively parallel reporter assay (MPRA) is an important technology to evaluate the impact of genetic variants on gene regulation. Here, we present MPRAVarDB, an online database and web server, for exploring regulatory effects of genetic variants. MPRAVarDB harbors 18 MPRA experiments designed to assess the regulatory effects of genetic variants associated with GWAS loci, eQTLs and various genomic features, resulting in a total of 242,818 variants tested across more than 30 cell lines and 30 human diseases or traits...

BACKGROUNDS: With the advent of the big data era, hospital information systems and mobile care systems, among others, generate massive amounts of medical data. Data mining, as a powerful information processing technology, can discover non-obvious information by processing large-scale data and analyzing them in multiple dimensions. How to find the effective information hidden in the database and apply it to nursing clinical practice has received more and more attention from nursing researchers...

This paper introduces a single-cell atlas for pivotal developmental stages in Xenopus, encompassing gastrulation, neurulation, and early tailbud. Notably surpassing its predecessors, the new atlas enhances gene mapping, read counts, and gene/cell type nomenclature. Leveraging the latest Xenopus tropicalis genome version, alongside advanced alignment pipelines and machine learning for cell type assignment, this release maintains consistency with previous cell type annotations while rectifying nomenclature issues...

BACKGROUND: Cutaneous melanoma remains an increasing global public health burden, particularly in fair-skinned populations. Advancing technologies, particularly artificial intelligence (AI), may provide an additional tool for clinicians to help detect malignancies with a more accurate success rate. This systematic review aimed to report the performance metrics of commercially available convolutional neural networks (CNNs) tasked with detecting MM. METHODS: A systematic literature search was performed using CINAHL, Medline, Scopus, ScienceDirect and Web of Science databases...

Background: Exercise has shown beneficial effects on neuronal neuroplasticity; therefore, we want to analyze the influence of high-intensity interval training (HIIT) on neuroplasticity markers in post-stroke patients. Methods: A systematic review of RCTs including studies with stroke participants was conducted using the following databases (PubMed, LILACS, ProQuest, PEDro, Web of Science). Searches lasted till (20/11/2023). Studies that used a HIIT protocol as the main treatment or as a coadjutant treatment whose outcomes were neural plasticity markers were used and compared with other exercise protocols, controls or other kinds of treatment...

The constant monitoring and control of various health, infrastructure, and natural factors have led to the design and development of technological devices in a wide range of fields. This has resulted in the creation of different types of sensors that can be used to monitor and control different environments, such as fire, water, temperature, and movement, among others. These sensors detect anomalies in the input data to the system, allowing alerts to be generated for early risk detection. The advancement of artificial intelligence has led to improved sensor systems and networks, resulting in devices with better performance and more precise results by incorporating various features...

OBJECTIVE: As an experimental biological science, physiology has been taught as an integral component of medical curricula for a long time in China. The teaching effectiveness of physiology courses will directly affect students' learning of other medical disciplines. The purpose of this study is to investigate the current situation and changes in physiology teaching over 30 years in Chinese medical schools. METHODS: National survey was conducted online on the platform SoJump via WeChat and the web...

Protein toxins are defense mechanisms and adaptations found in various organisms and microorganisms, and their use in scientific research as therapeutic candidates is gaining relevance due to their effectiveness and specificity against cellular targets. However, discovering these toxins is time-consuming and expensive. In silico tools, particularly those based on machine learning and deep learning, have emerged as valuable resources to address this challenge. Existing tools primarily focus on binary classification, determining whether a protein is a toxin or not, and occasionally identifying specific types of toxins...

The evidence on the impacts of climate change on mental health and wellbeing is growing rapidly. The objective of this scoping review is to understand the extent and type of existing mental health and psychosocial interventions aimed at addressing the mental health and psychosocial impacts of climate change. A scoping review methodology was followed. MEDLINE, PsycINFO, and Web of Science databases were searched from inception to May 2022. Comprehensive gray literature search, including expert consultation, was conducted to identify interventions for which peer-reviewed academic literature may not yet be available...

Digital trace data and machine learning techniques are increasingly being adopted to predict suicide-related outcomes at the individual level; however, there is also considerable public health need for timely data about suicide trends at the population level. Although significant geographic variation in suicide rates exist by state within the United States, national systems for reporting state suicide trends typically lag by one or more years. We developed and validated a deep learning based approach to utilize real-time, state-level online (Mental Health America web-based depression screenings; Google and YouTube Search Trends), social media (Twitter), and health administrative data (National Syndromic Surveillance Program emergency department visits) to estimate weekly suicide counts in four participating states...

BACKGROUND: There is increased awareness about the need for quality improvement (QI) education for trainees within clinical training programs. However, formal integration of a QI curriculum into graduate medical education (GME) remains a work-in-progress. We describe the creation and implementation of a novel, virtual QI curriculum complemented by virtual-based workshops. OBJECTIVE: To determine the impact of a GME QI curriculum on 1) trainee QI knowledge; 2) Quality of QI projects...

OBJECTIVES: To review the available evidence on the use and effectiveness of mobile applications to assist nursing students in comprehending, utilising, and applying specialised language and knowledge terminologies when learning the language of biosciences. DESIGN: A scoping review. DATA SOURCES: The databases CINAHL Complete, ERIC, EMCare, MEDLINE, PubMed, the OVID scholarly interface and the web search engine Google Scholar were searched...

BACKGROUND AND OBJECTIVES: Lifestyle-related diseases (LSDs) impose a substantial economic burden on patients and health care services. LSDs are chronic in nature and can directly affect the heart and lungs. Therapeutic interventions only based on symptoms can be crucial for prompt treatment initiation in LSDs, as symptoms are the first information available to clinicians. So, this work aims to apply unsupervised machine learning (ML) techniques for developing models to predict drugs from symptoms for LSDs, with a specific focus on pulmonary and heart diseases...

Mistreatment in medical education encompasses various forms of abusive behavior, often indicating a disregard for students' dignity and interfering with the learning process. This review paper aims to investigate the prevalence, patterns, and correlates of medical student mistreatment in Nigerian medical education and shed light on its impact on students' well-being. A literature search was conducted in August 2023 using Medline, Google Scholar, and Web of Science databases to identify relevant studies on the mistreatment of Nigerian medical students...

BACKGROUND: Radiomics has shown great potential in the clinical field of colorectal cancer (CRC). However, few bibliometric studies have systematically analyzed existing research in this field. The purpose of this study is to understand the current research status and future development directions of CRC. METHODS: Search the English documents on the application of radiomics in the field of CRC research included in the Web of Science Core Collection from its establishment to October 2023...