This dataset comprises a comprehensive collection of PubMed abstracts and associated metadata focusing on the topic of multiple sclerosis (MS) in relation to social determinants and environmental factors, spanning publications from January 1, 2018, to November 15, 2024.
C-SRR Radiation Patterns. The pixels from the radiation pattern generated by positioning the C-SRR over the phantom model with and without cancerous tissue were extracted using various window shapes and sizes to form the dataset. For this, pixel sampling operations such as average, minimum, maximum, and median are performed. Pixel reconfiguration to triangle, square, symmetric and asymmetric is also performed. In average pixel sampling, the average value of the pixel color is divided by the total number of pixels.
Abstract— Pluripotent cell types retain several characteristics that make them optimal cell source material for applications in drug development, disease modeling, and therapeutic applications. Human induced pluripotent stem cells (hiPSCs) are currently the most accessible cell source material to cultivate and derive cell-based therapeutic solutions at scale. However, a disconnect exists between quality characteristics of phenotype in the pluripotent state, and downstream metrics for efficacy.
We develope a novel TCM hallucination detection dataset, Hallu-TCM, sine no prior work has attempted this task in TM. We selected 1,260 TCM exam questions including 16 TCM subjects, input them into GPT-4, and collected their feedback. In the first level, we utilize Qwen-Max interface to annotate feedback multiple times with the binary label. If Qwen-Max consistently provided the same label across annotations, we adopted that label. For contentious cases, we recruited higher-degree research students who can understand and solve complex questions, including three Ph.D.
This video demonstrates the real-time data acquisition and noise reduction capabilities of a CMOS capacitive sensor array (CSA) implemented on an FPGA. The system captures the evaporation process of a deionized water droplet placed on the sensor array, using multiple sampling (MS) and pixel-wise accumulation (PWA) techniques to enhance signal quality and reduce random noise. The system efficiently processes and transmits the data, showcasing the gradual reduction in the droplet's size as it evaporates.
SynGen6 is a synthetic genomic dataset that encompasses six distinct populations. We utilized Principal Component Analysis (PCA) and ϵ-local differential privacy (LDP) to generate synthetic samples. We then simulated phenotype vectors associated with significant SNPs, mirroring real-world gene-disease associations. We also generated synthetic SNPs to watermark the dataset enabling verification of outsourced computations. Lastly, synthetic relatives were created to support research on kinship inference and family-based genomic analyses.
To download this dataset without purchasing an IEEE Dataport subscription, please visit: https://zenodo.org/records/13896353
Please cite the following paper when using this dataset:
This dataset webpage contains datasets and models
This dataset is used in my LAST Invited, keynote Speaker and 1st Special Session, AAE-2025*.
This is part of our external validation set, which contains 40 volunteers and about 80 hematological examination items. Among them, Cl, BHB, AG, RBP, HCO3, FT3, aTPO, CYSC, FT4, Folate, UA and aTG contribute more to the prediction. Because the data involves personal privacy and research confidentiality, it cannot be fully public. However, you can still make predictions by using our ML model and get a high accuracy on the external dataset. You can get our model at https://github.com/Masie1125/IDA-Predict-ML-Model. Of course, you can also use this dataset for new research.
A flexible pressure sensing system built with a flexible pressure sensor collected footprint image video of mice in a dark environment and open field, including footprint data of Parkinson's mice and normal mice at 6 months and 9 months old. Among them, 804, 811, 812 and 825 were normal mice; Mice 1, 2, 3, 4, 653, 682 were normal mice, and the rest were PD mice.
