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Topic Review
Immunological Features of Allergic Rhinitis
Inflammation of the upper respiratory tract in patients with allergic rhinitis (AR) may contribute to lower respiratory airways’ inflammation. T-helper 17 (Th17) cells and related cytokines are also involved in the immunological mechanism of AR along with the classical Th2 cells. It is hypothesized that upon Th2 pressure, the inflammatory response in the lungs may lead to Th17-induced neutrophilic inflammation. However, the findings for interleukin-17 (IL-17) are bidirectional. Furthermore, the role of Th17 cells and their counterpart—T regulatory cells—remains unclear in AR patients. It was also shown that a regulator of inflammation might be the individual circulating specific non-coding microRNAs (miRNAs), which were distinctively expressed in AR and bronchial asthma (BA) patients. 
  • 885
  • 08 Apr 2021
Topic Review
Biocatalytic Syntheses of Antiplatelet Metabolites
Antithrombotic thienopyridines, such as clopidogrel and prasugrel, are prodrugs that undergo a metabolic two-step bioactivation for their pharmacological efficacy. In the first step, a thiolactone is formed, which is then converted by cytochrome P450-dependent oxidation via sulfenic acids to the active thiol metabolites. These metabolites are the active compounds that inhibit the platelet P2Y12 receptor and thereby prevent atherothrombotic events. 
  • 884
  • 27 Oct 2021
Topic Review
Public Perceptions around mHealth Applications
This study aimed to use Twitter to understand public perceptions around the use of six Saudi mHealth apps used during the COVID-19 pandemic: “Sehha”, “Mawid”, “Sehhaty”, “Tetamman”, “Tawakkalna”, and “Tabaud”. The specific objectives of this study are: (1) to examine the difference in communication network structure across the networks generated among the six mHealth apps included in our study; (2) to analyze the sentiment surrounding the six mHealth apps conversations; and (3) to evaluate the performance of a sentiment classifier using machine learning approaches.
  • 884
  • 10 Jan 2022
Topic Review
The Implementation of Artificial Intelligence Technologies in Cardiology
Artificial Intelligence (AI) technologies have been increasingly used in cardiology to improve the accuracy and efficiency of diagnosis, treatment, and management of cardiovascular diseases. AI-based image analysis algorithms can quickly and accurately detect abnormalities in medical images, and predictive models can analyze vast amounts of patient data to identify patterns and predict the likelihood of developing certain cardiovascular diseases.
  • 863
  • 23 May 2023
Topic Review
Application of Artificial Intelligence in Idiopathic Pulmonary Fibrosis
Machine Learning (ML) is an algorithm based on big data, which learns patterns from the previously observed data through classifying, predicting, and optimizing to accomplish specific tasks.  ML can have good performance and is a great potential tool, especially in the imaging diagnosis of interstitial lung disease.  Idiopathic pulmonary fibrosis (IPF) is a major problem in the treatment of respiratory diseases, due to the abnormal proliferation of fibroblasts, leading to lung tissue destruction. The diagnosis mainly depends on the early detection of imaging and early treatment, which can effectively prolong the life of patients. 
  • 845
  • 07 Mar 2023
Topic Review
Foot-Detection Approach Based on Seven-Foot Dimensions
Unsuitable shoe shapes and sizes are a critical reason for unhealthy feet, may severely contribute to chronic injuries such as foot ulcers in susceptible people (e.g., diabetes patients), and thus need accurate measurements in the manner of expert-based procedures.
  • 833
  • 25 Jun 2023
Topic Review
Automated Dose Dispensed Medicine in Home Care
Automated dose dispensing (ADD) systems are today used around the world but little is known about how patients react to  receiving the daily doses of medicine from a machine rather than from a human. This entry reveals a general satisfaction towards ADD robots as an intervention.
  • 832
  • 06 Dec 2021
Topic Review
Renal Cancer Management with AI and Digital Pathology
Renal cancer is a heterogeneous group of tumors with different histology, molecular characteristics, clinical outcomes and responses to treatment. The most common types are clear cell (ccRCC), papillary (pRCC) and chromophobe RCC (chRCC).
  • 793
  • 31 Oct 2023
Topic Review
Prompt Engineering in Medical Education
Prompt engineering is a systematic approach to effectively communicating with generative language models (GLMs) to achieve the desired results. Well-crafted prompts yield good responses from the generative language models (GLMs), while poorly constructed prompts will lead to unsatisfactory responses. Besides the challenges of prompt engineering, significant concerns are associated with using GLMs in medical education, including ensuring accuracy, mitigating bias, maintaining privacy, and avoiding excessive reliance on technology.
  • 789
  • 11 Sep 2023
Topic Review
Large Language Models and Application in Nephrology
Large language models (LLMs), such as GPT-4, are an emergent technology that uses machine learning to process and analyze human language. Initially designed to improve natural language understanding and generation, LLMs have begun to extend their applicability beyond text-based tasks like translation, summarization, or conversational agents. Chain-of-thought prompting can enhance the problem-solving capabilities of AI models, particularly in complex and nuanced fields like medicine. 
  • 766
  • 17 Jan 2024
Topic Review
Duration and Side Effects of Tramadol
Tramadol is a painkiller that can stay in your body for different amounts of time depending on factors like your metabolism, age, and dosage. This article explains how long Tramadol stays in your system, what side effects you might experience, and important health issues to think about. We’ll cover how Tramadol can help with pain relief but also discuss the potential risks, including common side effects like dizziness or nausea, and the dangers of misuse or addiction. Understanding these points can help you use Tramadol safely and effectively.
  • 738
  • 31 Oct 2024
Topic Review
The Metabolomics
Metabolomics is a combined set of strategies to identify and quantify cellular metabolites using advanced analytical tools. This is typically achieved through the use of liquid or gas chromatography, which allows for the detection of individual metabolites through their specific mass-to-charge ratio (m/z) and their fragmentation in a mass spectrometer. By matching detected metabolites against databases of known metabolites, it is possible to identify the specific metabolites altered by exercise in a biological sample.
  • 736
  • 19 Jun 2023
Topic Review
Deep Learning-Based Data-Centric Approach for ASD Diagnosis
Autism spectrum disorder (ASD) is a neurological disorder that severely impairs the communication skills necessary for regular living. Most people with autism have mild difficulties but occasionally severe ones that necessitate specialized care. The accurate and early diagnosis of ASD is crucial for facilitating timely intervention and providing individualized care for affected individuals. Rapid advances in deep learning techniques have ushered in a new era of medical image analysis, particularly in the context of ASD detection using facial images.
  • 727
  • 22 Sep 2023
Topic Review
Bioinformatics Analysis and Genetic Technologies for Glioblastoma Multiforme
As the most malignant primary brain tumor in adults, a diagnosis of glioblastoma multiforme (GBM) continues to carry a poor prognosis. GBM is characterized by cytoprotective homeostatic processes such as the activation of autophagy, capability to confer therapeutic resistance, evasion of apoptosis, and survival strategy even in the hypoxic and nutrient-deprived tumor microenvironment. The gold standard of therapy, which involves radiotherapy and concomitant and adjuvant chemotherapy with temozolomide (TMZ), has been a game-changer for patients with GBM, relatively improving both overall survival (OS) and progression-free survival (PFS); however, TMZ is now well-known to upregulate undesirable cytoprotective autophagy, limiting its therapeutic efficacy for induction of apoptosis in GBM cells. The identification of targets utilizing bioinformatics-driven approaches, advancement of modern molecular biology technologies such as clustered regularly interspaced short palindromic repeats (CRISPR)—CRISPR-associated protein (Cas9) or CRISPR-Cas9 genome editing, and usage of microRNA (miRNA)-mediated regulation of gene expression led to the selection of many novel targets for new therapeutic development and the creation of promising combination therapies.
  • 669
  • 07 Apr 2023
Topic Review
Types of Breast Cancer Imaging
Cancer is an incurable disease based on unregulated cell division. Breast cancer is the most prevalent cancer in women worldwide, and early detection can lower death rates. Medical images can be used to find important information for locating and diagnosing breast cancer. The best information for identifying and diagnosing breast cancer comes from medical pictures.
  • 638
  • 09 Aug 2023
Topic Review
Role of Metabolic Connectome in Complex Diseases
The interconnectivity of advanced biological systems is essential for their proper functioning. In modern connectomics, biological entities such as proteins, genes, RNA, DNA, and metabolites are often represented as nodes, while the physical, biochemical, or functional interactions between them are represented as edges. Among these entities, metabolites are particularly significant as they exhibit a closer relationship to an organism’s phenotype compared to genes or proteins. Moreover, the metabolome has the ability to amplify small proteomic and transcriptomic changes, even those from minor genomic changes. Metabolic networks, which consist of complex systems comprising hundreds of metabolites and their interactions, play a critical role in biological research by mediating energy conversion and chemical reactions within cells. 
  • 638
  • 02 Feb 2024
Topic Review
Wearable Energy Harvesters
A rapidly expanding global population and a sizeable portion of it that is aging are the main causes of the significant increase in healthcare costs. Healthcare in terms of monitoring systems is undergoing radical changes, making it possible to gauge or monitor the health conditions of people constantly, while also removing some minor possibilities of going to the hospital. The development of automated devices that are either attached to organs or the skin, continually monitoring human activity, has been made feasible by advancements in sensor technologies, embedded systems, wireless communication technologies, nanotechnologies, and miniaturization being ultra-thin, lightweight, highly flexible, and stretchable. Wearable sensors track physiological signs together with other symptoms such as respiration, pulse, and gait pattern, etc., to spot unusual or unexpected events.
  • 632
  • 26 Jul 2023
Topic Review
Virtual Reality for Rehabilitation of Acquired Cognitive Disorders
Virtual Reality (VR) is presented as a transformative tool that immerses individuals in interactive environments, offering promising opportunities for enhancing cognitive functions and improving quality of life.
  • 582
  • 05 Jan 2024
Topic Review
Predicting the Outcome of Heart Failure against Ischemia
The article titled "Predicting the outcome of heart failure against chronic-ischemic heart disease in elderly population – Machine learning approach based on logistic regression, case to Villa Scassi hospital Genoa, Italy" discusses a study that uses machine learning, specifically logistic regression, to predict the outcomes of heart failure in elderly patients suffering from chronic ischemic heart disease. The research focuses on data collected from Villa Scassi Hospital in Genoa, Italy. The goal of the study is to improve prediction models for patient prognosis, thereby helping healthcare providers make more informed decisions about treatment and management for this vulnerable population. The use of logistic regression in this context aims to provide a reliable tool for assessing patient risk and outcomes, ultimately leading to better-targeted interventions for elderly patients with these heart conditions.
  • 422
  • 13 Feb 2025
Topic Review Peer Reviewed
Digital Health Transformation Through Telemedicine (2020–2025): Barriers, Facilitators, and Clinical Outcomes—A Systematic Review and Meta-Analysis
Background: Telemedicine expanded dramatically during the COVID-19 pandemic, transforming healthcare delivery worldwide. However, implementation faced challenges, and the impact on clinical outcomes, access, and quality remains under investigation. Objective: To systematically review the literature from 2020 to 2025 on telemedicine adoption, identifying key barriers and facilitators, and to evaluate clinical outcomes associated with telehealth use during this period. Methods: We followed PRISMA 2020 guidelines in conducting this review. Multiple databases were searched for studies on the implementation or evaluation of telemedicine/telehealth. Eligible studies included randomized trials and observational studies reporting telehealth-related outcomes, barriers, or facilitators. Two reviewers screened studies and extracted data on study characteristics, telemedicine interventions, barriers/facilitators, and clinical outcomes. Risk of bias was assessed using RoB2 for randomized controlled trials (RCTs) for qualitative or cross-sectional studies. Meta-analyses were performed where data were comparable, and qualitative synthesis was used to summarize barriers and facilitators. Results: Thirty-two studies (17 RCTs and 15 observational) were included. Telemedicine use surged in 2020 and remained elevated compared to baseline through August 2025. Reported barriers included insufficient broadband access, limited digital literacy, uncertain reimbursement policies, and workflow disruptions. Facilitators encompassed supportive policy waivers, the integration of telehealth into established care pathways, and strong acceptance from patients and providers. Clinical outcomes were generally comparable to in-person care. Telehealth enhanced chronic disease management (e.g., hypertension, diabetes) and decreased hospitalizations for heart failure, while ensuring safety in surgical follow-up and prenatal care. However, higher revisit rates were observed in some acute follow-up settings. Patient satisfaction consistently remained high, especially among rural and underserved populations reporting benefits, though disparities in digital access continued to exist. Conclusions: Telemedicine has become a sustainable component of healthcare, delivering clinical outcomes comparable to traditional care while offering convenience and resilience. Overcoming technology gaps, regulatory uncertainties, and equity issues is crucial for ongoing progress. Hybrid care models that combine telemedicine with in-person services, supported by strong policy frameworks, are recommended to maximize benefits and promote fair access in the post-pandemic era.
  • 141
  • 09 Dec 2025
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