PET CT indicating colorectal cancer with mets to the liver, lung and nodes throughout the body.
Colorectal cancer with mets to the Liver, Lung or Nodes. PET/CT can aid in accurately detecting metastasis of cancer to all parts of the body and also can help in staging of initial cancer diagnosis. The liver is the most common place for colorectal cancer to metastasize to. The lung and Lymph nodes are also very common for metastasis of colorectal cancer. Each organ that is involved in the spread of cancer determines which stage of cancer the patient is at. The earlier each stage is found the higher chance of successful treatment.
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This listing uses a single pricing dimension called Product Access (Units). It grants you access to the product at no cost. There are no tiers, instance sizes, or usage add-ons to compare. You subscribe under one flat option that unlocks the de-identified medical imaging dataset. The dataset is a free published sample covering colorectal cancer PET CT imaging. Because only one dimension exists, pricing does not scale with usage or quantity. You simply gain access to the data for the subscription period.
Top-of-mind questions for buyers
What does one unit of Product Access grant me?
One unit unlocks access to the de-identified medical imaging dataset for colorectal cancer PET CT imaging. It grants entry to this free published sample so you can review the data during your subscription period. There are no separate per-record or per-user charges to combine.
How long does my access last, and does cost change with usage?
The published datasets are offered free with a one-month subscription. Because a single flat dimension applies, your cost does not scale with the number of records viewed or downloaded. You gain access for the subscription period at no charge.
What type of data is included in this free published dataset?
You receive de-identified real-world medical imaging data for colorectal cancer PET CT. It is a published sample dataset hosted on AWS Marketplace, meant to let you experience the data before pursuing a larger curated cohort request.
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