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a. HIPAA and GDPR Compliance Data Anonymization:

Mask or anonymize patient data when it is no longer needed for diagnostic purposes. Audit Trails:

Log all access and changes to patient data with timestamps and user IDs. Store audit logs securely for at least 6 years (as per HIPAA guidelines). Training and Awareness:

Ensure all developers and operators handling the swarm are trained on HIPAA and GDPR regulations.

  1. Agent Communication Protocol Secure Inter-Agent Communication:

Encrypt messages between agents using shared secrets or public/private key pairs. Communication Verification:

Add integrity checks (e.g., HMAC) to ensure messages between agents haven’t been tampered with.

  • Structured outputs

  • List of possible ICD 10 codes with supporting evidences, final_summary icd 10,

  • icd 10

    • supporting evidence

  • icd 10

    • supporting evidence

  • icd 10

    • supporting evidence

  • icd 10

    • supporting evidence

  • most_likely_code:

    • code:
    • summary

  • patient may have many conditions,

  • patient needs to identify list of icd 10s, for every code, what is the servicing provider, what is evidence for that code including reference to page number,

  • for every patient, generate unique id,

  • for every doc in the database, attach some unique id, when we query the data using that id,

  • same patient can be handled differently, document from different year'

  • for some docs, average doc size is 20+ pages, but others is 300+, biggest document is 30,000 pages, overview of the entire patient and medical history of the patient

  • handle the number of pages

  • turn around time, handle processes of 100+ pages, process 30,000 pages

Diagnosis or symptions into icd 10 codes

  • agent that goes searches, what labs we could order

  • Based off a diagnosis, find a lab to monitor condition

  • rule out the condition or monitor the condition

  • lab test results analysis agent, based off lab results -> what diagnosis

  • not just labs,

  • kidney stones or ultra sound,

  • monitoring agent that finds how to best monitor a patient

  • urine lab, they have stones, what type of kidney stones,

  • testing agent for evaluation

  • all conditions and records of all the diagnosises,

  • is this condition being monitored or not

  • results of the lab, maybe

  • alert doctor if diagnosis

  • identify lab reports from pdfs or ehrs, in reports identify diagnosis, identify normal baselines, and abnormal line,

  • diagnositic tests for the lab agent

  • For each diagnosis, pull lab results,

  • egfr

  • for each diagnosis, pull lab ranges,

  • pull ranges for diagnosis

  • if the diagnosis is x, then the lab ranges should be a to b

  • train the agents, increase the load of input

  • medical history sent to the agent

  • setup rag for the agents

  • run the first agent -> kidney disease -> don't know the stage -> stage 2 -> lab results -> indicative of stage 3 -> the case got elavated ->

  • how to manage diseases and by looking at correlating lab, docs, diagnoses

  • put docs in rag ->

  • monitoring, evaluation, and treatment

  • can we confirm for every diagnosis -> monitoring, evaluation, and treatment, specialized for these things

  • find diagnosis -> or have diagnosis, -> for each diagnosis are there evidence of those 3 things

  • swarm of those 4 agents, ->

  • fda api for healthcare for commerically available papers

  • what are the labs that can be ruled out to verify each diagnosis, lab results,

  • lab result

  • labs and diagbnoses

  • 3 main labs one is quest diagnosists, lab core,

  • reference laboroties,

  • top 15k diagnosises, find out what labs get ordered, another agent will say what labs results indicidate this particular diagnosis

  • for monitoring do we order what lab results indicate this condition

  • find lab in document, this is the lab we found, when user click on lab, redirect to diagnosis

  • multiple lab results, multiple diagnosiss, indicative of thi code, this code is because of that code of that lab result

  • find the position of the lab result in the document, find the diagnosis in the document, find the lab result in the document, find the diagnosis in the document

  • result that indicates the abnormal result in the lab that refers to the diagnosis.

  • showcase where in the document is the lab results -> correlation

Output format for the api:

  • report:
  • diagnosis_code:
  • lab: