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Challenge

Pediatric Rapid WGS Clinical Decision Multi-Agent Network via AutoGen

Pediatric whole-genome sequencing requires rapid variant interpretation under stringent operational latencies. Deploy an AutoGen multi-agent clinical consensus workflow on decentralized Akash Network infrastructure to evaluate pediatric genomic variants and generate standardized diagnostic FHIR reports within targeted turnaround limits.

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Challenge brief

What you are building

The core problem, expected build, and operating context for this challenge.

Build a multi-agent system using AutoGen hosted on Akash Network compute to process pediatric rapid whole-genome sequencing datasets.

Delivery guide

How work is evaluated

Evaluation

Evaluates multi-agent AutoGen consensus speed, HPO phenotype matching, and FHIR report output validity.

Datasets

Shared data for this challenge

Review public datasets and any private uploads tied to your build.

Evaluation rubric

How submissions are scored

These dimensions define what the evaluator checks and which criteria separate a passable run from a strong one.

Dimensions
2 scoring checks
Binary
2 pass or fail dimensions
Ordinal
0 scaled dimensions
Dimension 1

FHIR Schema Compliance

Validates that DiagnosticReport meets FHIR R4 schema requirements.

Binary check

This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.

Dimension 2

Phenotype Match Rate

Accuracy of correlating phenotypic HPO terms with causative genes. • target: 0.95 • range: 0-1

Binary check

This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.

Learning goals

What you should walk away with

  • Design multi-agent role delegation using Microsoft AutoGen for clinical genetics.

  • Deploy scalable containerized compute workloads onto Akash Network decentralized cloud.

  • Automate phenotype (HPO terms) to genotype cross-referencing.

  • Export structured diagnostic recommendations into HL7 FHIR DiagnosticReport resources.

Resources and assets

Reference links and supporting material

Dataset notes

Pediatric clinical cases dataset linking HPO terms, candidate genetic variants, and expert-validated primary diagnoses.

How this agent runs

Evaluates multi-agent AutoGen consensus speed, HPO phenotype matching, and FHIR report output validity.

Challenge input

JSON containing patient HPO terms and candidate genomic variants

AutoGen

Enables multi-agent role playing for consensus diagnostics.

Akash Network

Provides decentralized cloud infrastructure for fast execution.

Evaluated output

JSON FHIR DiagnosticReport containing primary diagnosis and candidate variant

Checks for
  • Validates that DiagnosticReport meets FHIR R4 schema requirements.
  • Accuracy of correlating phenotypic HPO terms with causative genes. • target: 0.95 • range: 0-1
Proof of success
  • Benchmark: PediatricGenomics-Bench
  • Phenotype Match Rate target: 95%
  • 1 public reference case
Runtime evidence
  • Python execution harness
  • Python sandbox (unavailable on Versalist)
View technical recipe

Configured tools

Action Space
  • AutoGen · Required
  • Akash Network · Optional
  • Zed · Optional

Evaluation contract

  • FHIR Schema Compliance · Weight 1
  • Phenotype Match Rate · Weight 1

Recipe state

This is a preview. The configuration can change before the evaluation recipe is locked.

Frequently Asked Questions about Pediatric Rapid WGS Clinical Decision Multi-Agent Network via AutoGen