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No description yet: the sentence for this tag has not been written. 16 records carry it: 14 collections, 1 bottleneck, 1 idea.
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16 records
| Cancers | Other tags | ||||
|---|---|---|---|---|---|
| none | none | none | |||
Arc Virtual Cell Atlas Arc Institute Arc's growing library of cell data, the fuel for virtual cell models. | none | none | virtual-cell | ||
| none | none | source | |||
EMA news and CHMP meeting highlights European Medicines Agency The EMA's CHMP highlights show Europe's approval pipeline one month ahead of European Commission decisions. | none | none | source | ||
Evaluate Vantage Evaluate (Norstella) Evaluate Vantage forecasts which drugs and modalities will matter commercially in the next decade. | none | none | source, news | ||
Flatiron Health and Foundation Medicine Clinico-Genomic Database Flatiron Health (Roche) and Foundation Medicine Real-world evidence at scale: what happened to patients with a given genomic profile on a given treatment. | none | none | real-world | ||
Make the treatment exposure record machine-readable, so surveillance can be computed Risk-based follow-up guidelines key surveillance to cumulative dose and radiotherapy field. Survivors frequently cannot obtain either, so the guidelines are unusable even where someone is willing to follow them. | none | none | rejuvenation, survivorship, open-problem | ||
NCI CDAS: NLST and PLCO screening trial data NCI NCI CDAS holds the lung screening trial images that trained Sybil and most lung-nodule AI. | none | none | none | ||
NCI Imaging Data Commons (IDC) NCI Cancer Research Data Commons The Imaging Data Commons is TCIA in the cloud, ready for large-scale model training. | none | none | none | ||
NICE technology appraisals National Institute for Health and Care Excellence NICE technology appraisals say whether the NHS will pay, and why. They are the most transparent HTA record in the world. | none | none | source | ||
Pathology AI benchmarks (CAMELYON, PANDA, TCGA slide tasks) Grand Challenge / Radboud UMC and partners Pathology AI benchmarks are the open challenge datasets on which every pathology model is scored: CAMELYON16 and 17 for lymph node metastasis detection, PANDA for prostate grading with 11,000 biopsies, and TCGA slide-level tasks used to compare foundation models. Licences are mostly CC BY-NC-SA or set per challenge. | none | none | benchmark | ||
Registries count diagnoses and deaths, and not what treatment left behind Cancer registries are good at incidence and mortality and record almost nothing about late effects, so the scale of the problem is estimated from a handful of cohorts rather than counted. Europe cannot say how many survivors it has. | none | none | rejuvenation, survivorship, open-problem | ||
Semantic Scholar Allen Institute for AI Semantic Scholar offers free literature search with machine-generated summaries and citation context. | none | none | source | ||
Tahoe-100M Vevo Therapeutics with Parse Biosciences and Arc Institute Tahoe-100M is the biggest single-cell dataset ever released, built to teach AI how cancer cells respond to drugs. | none | none | virtual-cell | ||
The Cancer Imaging Archive (TCIA) NCI / University of Arkansas The public archive of cancer scans that most radiology AI is trained and tested on. | none | none | none | ||
UK Biobank UK Biobank Ltd (charity) UK Biobank is the richest population cohort for linking genes, blood and imaging to who later develops cancer. | none | none | none |
