Pancreatic cancer is a malignant disease that develops in the pancreas, a gland located behind the stomach. It is one of the most aggressive and lethal types of cancer. The exact cause of pancreatic cancer is unknown, but several risk factors have been identified.
Pancreatic cancer often doesn't cause symptoms in the early stages. When symptoms do occur, they can be vague and similar to other conditions. It is important to continue to improve early detection for pancreatic cancer.
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This listing uses a single pricing dimension called Product Access (Units). It grants you access to the de-identified medical imaging dataset for pancreatic cancer CT scans. The product is free, so no charges apply for this access. The dataset is offered as a sample, published on AWS Marketplace with a one-month subscription. There are no tiers, instance sizes, or usage-based add-ons to choose from. You simply subscribe to gain access to the dataset under this one flat dimension.
Top-of-mind questions for buyers
What does one unit of Product Access include for this dataset?
One unit grants you access to the de-identified Pancreatic Cancer CT imaging dataset. This is a published sample cohort of medical imaging data. You get the dataset itself, not a per-image or per-patient charge. Access covers the sample data offered under this listing.
Does my cost change if I use the dataset more heavily or over a longer period?
No. The product is free, so no charges accrue regardless of how much you access or analyze the data. There are no usage meters, overage fees, or tier thresholds. The dataset is offered as a sample with a one-month subscription and no cost.
Is this static data or does it update continuously during my subscription?
This listing provides a published sample dataset, which is a fixed cohort of de-identified imaging data. It is not a continuous or longitudinal data stream. Real-time, updating cohorts are handled through separate arrangements, so contact the vendor for details on ongoing data access beyond this sample.
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This study generated a collection of patient-derived pancreatic normal and cancer organoids and it was sequenced using Whole Genome Sequencing (WGS), Whole Exome Sequencing (WXS) and RNA-Seq as well as matched tumor and normal tissue if available. The study provides a valuable resource for pancreatic cancer researchers.
The dataset contains open RNA-Seq Gene Expression Quantification data and controlled WGS/WXS/RNA-Seq Aligned Reads, WXS Annotated Somatic Mutation, WXS Raw Somatic Mutation, and RNA-Seq Splice Junction Quantification.