Urine microRNA Pancreatic Cancer Screening Pipeline with Claude Agents SDK and OpenHands
Early detection of pancreatic cancer requires detecting subtle microRNA signatures in non-invasive urine samples. You will build an autonomous agent using Claude Agents SDK and OpenHands to execute quality control, feature selection, and classification pipelines targeting 90% diagnostic specificity.
What you are building
Develop an autonomous bioinformatics agent with Claude Agents SDK and OpenHands to execute urine microRNA biomarker discovery pipelines.
How work is evaluated
Evaluates diagnostic classification accuracy and specificity on unseen urine miRNA validation cohorts.
Datasets
Public datasets, plus the private datasets you have access to.
How submissions are scored
specificity_threshold_test
Ensure specificity is >= 0.90 at required sensitivity cutoff
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
roc_auc
Area under the receiver operating characteristic curve • target: 0.93 • range: 0-1
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
Learning goals
Construct autonomous agent workflows using Anthropic's Claude Agents SDK
Utilize OpenHands environment tools for execution of terminal actions and data inspection
Classify pancreatic cancer risk from urine-derived microRNA expression profiles
Resources
Urine microRNA screening matrix dataset covering 500 pancreatic cancer patients and healthy controls.
Challenge setup
Evaluates diagnostic classification accuracy and specificity on unseen urine miRNA validation cohorts.
Challenge input
CSV file path containing miRNA expression count matrix
Claude Agents SDK
Mandatory Anthropic agent orchestration SDK.
OpenHands
Provides execution environments and tooling.
Evaluated output
JSON array of patient IDs with predicted pancreatic cancer probability
- Ensure specificity is >= 0.90 at required sensitivity cutoff
- Area under the receiver operating characteristic curve • target: 0.93 • range: 0-1
- Benchmark: OncoDiagnostics-Bench
- Roc Auc target: 0.93
- 1 public reference case
- Python execution harness
- Python sandbox (unavailable on Versalist)
Shows the first task, up to three tools, and up to three evidence items.
View technical recipe
Configured tools
- OpenHands · Required
- OpenHands · Required
- PyTorch Lightning · Optional
- Meta · Optional
- OpenHands · Required
Evaluation contract
- specificity_threshold_test · Weight 1
- roc_auc · Weight 1
Metrics
- roc_auc · Target 0.93
Benchmarks
- OncoDiagnostics-Bench
- biotech
Reference cases
- 1 public reference case
Workflow tasks
- Task 1
Input: CSV file path containing miRNA expression count matrix
Output: JSON array of patient IDs with predicted pancreatic cancer probability
Execution harness: Python
Evaluation tools
- Claude Agents SDK · Agent Core Framework
- OpenHands · Agent Workspace Environment
Recipe freeze marker
No recipe freeze time is recorded.