Loading...
Loading...
Medical imaging (X-ray, CT, MRI), electronic health records, clinical trials, ECG/EEG, pathology
12,795 datasets
A meta-analysis of public 16S saliva data by Qixiang Yuan, published on figshare in April 2026, integrates 7,750 samples from 22 cohorts sourced from PubMed between 2016 and 2024. Bioinformatics analyses using QIIME2 and Wekemo revealed community characteristics, identified nine core microbes in healthy controls, and built multi-disease prediction models. The study validated the feasibility of establishing healthy baselines via saliva microbiota and using machine learning for non-invasive diagnosis.
A meta-analysis of 7,750 saliva samples from 22 cohorts published between 2016 and 2024. The dataset was compiled by Qixiang Yuan from PubMed and analyzed using bioinformatics tools like QIIME2 and Wekemo. It reveals gender differences, core microbiota, and molecular markers for disease prediction.
Qixiang Yuan's meta-analysis aggregates 22 public 16S rRNA saliva cohorts from PubMed (2016–2024), comprising 7,750 samples. The study identifies core microbiota and uses machine learning to build multi-disease prediction models. The dataset and findings were published on figshare in April 2026.
A meta-analysis of 22 public 16S rRNA saliva cohorts comprising 7,750 samples, collected from PubMed between 2016 and 2024. The study by Qixiang Yuan identifies core microbiota and constructs machine learning models for multi-disease prediction. It was last updated on 2026-04-15 and is shared under a CC-BY-4.0 license.
A meta-analysis of 7,750 saliva samples from 22 public cohorts (2016–2024) reveals gender differences and core microbiota. Qixiang Yuan used QIIME2 and Wekemo to analyze 16S rRNA data, identifying nine core microbes and constructing a multi-disease prediction model. The study validated the feasibility of using saliva microbiota and machine learning for non-invasive disease diagnosis.
A meta-analysis of 22 cohorts comprising 7,750 saliva samples collected from PubMed between 2016 and 2024. Bioinformatics analyses using QIIME2 and Wekemo revealed core microbiota and constructed multi-disease prediction models. The dataset was authored by Qixiang Yuan and published on figshare under a CC-BY-4.0 license.
A research paper from China presents a three-dimensional evaluation index system for outpatient healthcare quality in stomatological hospitals. The system was developed using a mixed-methods design, including a systematic literature review, focus groups, and a two-round Delphi expert consultation with 28 specialists. The final system comprises 3 first-level, 16 second-level, and 77 third-level indicators, with weights calculated via the Analytic Hierarchy Process.
10,010 hip images from 806 patients collected between 2018 and 2024. Xueyang Han authored this retrospective multicenter study using data from four Chinese hospitals to develop and validate a deep learning model for fracture classification. The dataset includes training, validation, and independent test sets used to benchmark model performance against 12 physicians.
563 patient reports from the FDA Adverse Event Reporting System (FAERS) spanning Q1 2004 to Q1 2025 were analyzed by Wei Yang in 2026. The dataset contains 2,241 adverse event records for the oncology drug pralatrexate, detailing patient demographics, event types, and outcomes. It was extracted and cleaned from the public FAERS database to study the drug's postmarketing safety profile.
2,241 adverse event reports from 563 patients treated with the anticancer drug pralatrexate were extracted from the FDA FAERS database. The analysis, authored by Wei Yang and updated in April 2026, identifies 84 safety signals and characterizes the drug's postmarketing safety profile, including median time to onset of adverse events.
2,241 adverse event reports from 563 patients prescribed the lymphoma drug pralatrexate were analyzed. The study, authored by Wei Yang and published in April 2026, systematically assessed the drug's postmarketing safety profile using FDA Adverse Event Reporting System data from 2004 to 2025.
FAERS data from 2004 to 2025 provides 2,241 adverse event reports for 563 patients treated with the anticancer drug pralatrexate. The dataset was created by Wei Yang in 2026 for a pharmacovigilance study analyzing the drug's postmarketing safety profile. It includes patient demographics, reported adverse events, signal detection results, and time-to-onset data.
Shuchao Wang's study on figshare presents a prognostic model for primary tracheal malignancy (PTM) patients. The dataset, last updated in April 2026, is derived from a retrospective review of 115 patients. It includes a radiomics score (Radscore) based on seven CT features and the clinical factor of longitudinal length, combined into a nomogram for survival prediction.
A controlled study of 14 pigs with Grade 4 tail-biting injuries compares a novel curcumin-berberine ointment against standard oxytetracycline therapy over 21 days. The dataset is a 7.0 MB PDF containing results from a translational porcine model authored by Paweł Biernat and published in April 2026. It reports primary outcomes like healing time and secondary metrics including thermographic temperatures and hematological parameters.
Jianqin Huang's 2026 figshare dataset contains supplementary figures and tables for a study on glycemic variability in elderly sepsis patients in the ICU. The 159.9 KB ZIP file includes propensity score matching results and associations between glycemic variability, delirium, and mortality. The dataset is licensed under CC-BY-4.0.
Nova Scotia's archived Community Counts data reports mental health conditions across district health authorities. The dataset is provided by the Government of Nova Scotia for archival purposes and covers the period from 2001 to 2007. Users seeking current information are directed to Statistics Canada's Census Program.
District of Workforce Shortage classifications for eight medical specialties in Australia, including Anaesthetics and Psychiatry. The dataset is produced by the Department of Health's Rural Distribution Section using population and Medicare billing data to calculate specialist-to-population ratios. The provided file reflects the annual update as of November 2023.
District of Workforce Shortage data classifies Australian geographical regions with insufficient non-GP specialist doctors. The dataset is produced by the Department of Health's Rural Distribution Section and was last updated in November 2023. It covers eight key medical specialties, including Anaesthetics and Psychiatry, across SA3 regions.
302,062 structured adverse event reports for neurology and central nervous system drugs from the FDA's FAERS database, covering the period 2020–2025. It includes serious adverse events such as hospitalization, life-threatening outcomes, and death. The dataset was created by RubyIntelligence and was last updated on Hugging Face in June 2026.
312,039 structured adverse event reports for cardiovascular drugs from the FDA's FAERS database, covering the period from 2020 to 2025. The dataset includes serious adverse events such as hospitalization, life-threatening outcomes, and death. It was created by RubyIntelligence and last updated on June 17, 2026.