Biomedical and Health Sciences

This dataset contains measured data from five sensor modules designed for monitoring the oxygen concentration in the air in a hospital environment, especially in rooms where oxygen therapy can potentially occurs. This data is crucial from a safety point of view, as a higher oxygen concentration can increase the risk of fire development.


Most promoters are derived from an arbitrary truncation of sequences upstream from the transcription start site of a gene, which is typically around 1,000 base pairs. Since the truncation is arbitrary, regulatory elements might be missing for transcription. Unfortunately, there exists no reasonable rationale for selecting a truncation threshold. Therefore, providing a reasonable rationale for truncation is crucial for obtaining the expected expression profiles of genes.


Cemented total hip arthroplasty (THA) demonstrates superior survival rates compared to uncemented procedures. Nevertheless, most younger patients opt for uncemented THA, as removing well-fixed bone cement in the femur during revisions is complex, particularly the distal cement plug. This removal procedure often increases the risk of femoral fracture or perforation, haemorrhage and weakening bone due to poor drill control and positioning. Aim of this study was to design a novel drill guide to improve drill positioning.


This dataset protocol details the acquisition of a surface electromyography (sEMG) dataset from the Tibialis Anterior (TA) and Gastrocnemius Lateralis (GL) muscles of 20 healthy adults, with an equal distribution of 10 male and 10 female participants. The data was collected using the Delsys Trigno wireless EMG system during a 30-second walking session. Proper electrode placement on the specified muscles was ensured for accurate signal capture. Ethical considerations were addressed, with approval from the Institutional Review Board and informed consent from participants.


Endoscopic images of patients with AIG, type B gastritis, and CNAG were collected between January 1st, 2019 and March 1st, 2023. All endoscopic images were acquired by Olympus Evis Lucera 260/290 (Tokyo, Japan) and FUJIFILM EC-760RV/M (Tokyo, Japan). This dataset includes 3576 endoscopic images. Poor image quality, images of the pharynx, images of the esophageal region, and images of the duodenal region were excluded.


During our research in generating or optimizing molecules to be drug candidates by extending deep reinforcement learning and graph neural networks algorithms, we used GEOM data [1], and we had an idea to make a dataset obtained from molecules from GEOM to predit the activity towards COVID and the drug linkeness. We calculated over 200 descriptors for the molecules using RDKit [2]. We hope you enjoy using it.




The pathology files of 194 colon cancer patients, 137 breast cancer patients, 124 gastric cancer patients, and 169 thyroid cancer patients who were referred to the healthcare facilities of Qazvin Province, Iran  were examined for age, sex, surgery type, and pathological information. We collected information between 2010 and 2020.


EEG Data Acquisition Using the Muse Device: Meditation and Rest Stages of Participants


This study aimed to investigate electroencephalogram (EEG) patterns during meditation to gain insights into the distinctions among practitioners with differing levels of experience. We analyzed EEG data from a cohort of seven participants with a unique background in Vipassana meditation, in order to discern how disparities in experience levels manifest in their neural activity. 


The Numerical Latin Letters (DNLL) dataset consists of Latin numeric letters organized into 26 distinct letter classes, corresponding to the Latin alphabet. Each class within this dataset encompasses multiple letter forms, resulting in a diverse and extensive collection. These letters vary in color, size, writing style, thickness, background, orientation, luminosity, and other attributes, making the dataset highly comprehensive and rich.


Cardiovascular diseases (CVD) are a leading global health concern. Comprehensive data on CVD and key biomarkers play a pivotal role in deciphering individual symptomatology. These biomarkers encompass a range of physiological indicators, such as cholesterol levels, blood pressure, and inflammatory markers like C-reactive protein.