Calc Fleischner 2017

{
  "count": 2,
  "items": [
    {
      "citation": {
        "authors": "MacMahon H, Naidich DP, Goo JM, Lee KS, Leung ANC, Rajendran K, Travis WD, Bankier AA",
        "doi": "10.1148/radiol.2017161659",
        "id": "macmahon-2017",
        "pmid": "28240562",
        "source": "Radiology. 2017;284(1):228-243",
        "title": "Guidelines for Management of Incidental Pulmonary Nodules Detected on CT Images: From the Fleischner Society 2017"
      },
      "criteria": [
        {
          "factor": "size_lt_6",
          "met": true,
          "value": 5
        },
        {
          "factor": "size_6_to_8",
          "met": false,
          "value": 5
        },
        {
          "factor": "size_gt_8",
          "met": false,
          "value": 5
        },
        {
          "factor": "high_risk",
          "met": false
        }
      ],
      "disclaimer": "Not a medical device. Deterministic published-formula or published-code output for autonomous agents. A licensed clinician remains responsible for patient care and billing submissions.",
      "formula": "fleischner_2017",
      "formula_expression": "Single solid noncalcified incidental nodule (MacMahon 2017): size_mm < 6 → no_routine_followup if not high_risk else optional_ct_12_months; 6 <= size_mm <= 8 → ct_6_12_then_consider_18_24 if not high_risk else ct_6_12_then_18_24; size_mm > 8 → consider_ct_3_pet_or_tissue (low or high risk). Not subsolid. Not multiple nodules. Not Lung-RADS screening. magent does not read CT.",
      "high_risk": false,
      "recommendation": "no_routine_followup",
      "size_band": "<6"
    },
    {
      "citation": {
        "authors": "MacMahon H, Naidich DP, Goo JM, Lee KS, Leung ANC, Rajendran K, Travis WD, Bankier AA",
        "doi": "10.1148/radiol.2017161659",
        "id": "macmahon-2017",
        "pmid": "28240562",
        "source": "Radiology. 2017;284(1):228-243",
        "title": "Guidelines for Management of Incidental Pulmonary Nodules Detected on CT Images: From the Fleischner Society 2017"
      },
      "criteria": [
        {
          "factor": "size_lt_6",
          "met": true,
          "value": 5
        },
        {
          "factor": "size_6_to_8",
          "met": false,
          "value": 5
        },
        {
          "factor": "size_gt_8",
          "met": false,
          "value": 5
        },
        {
          "factor": "high_risk",
          "met": false
        }
      ],
      "disclaimer": "Not a medical device. Deterministic published-formula or published-code output for autonomous agents. A licensed clinician remains responsible for patient care and billing submissions.",
      "formula": "fleischner_2017",
      "formula_expression": "Single solid noncalcified incidental nodule (MacMahon 2017): size_mm < 6 → no_routine_followup if not high_risk else optional_ct_12_months; 6 <= size_mm <= 8 → ct_6_12_then_consider_18_24 if not high_risk else ct_6_12_then_18_24; size_mm > 8 → consider_ct_3_pet_or_tissue (low or high risk). Not subsolid. Not multiple nodules. Not Lung-RADS screening. magent does not read CT.",
      "high_risk": false,
      "recommendation": "no_routine_followup",
      "size_band": "<6"
    }
  ],
  "path": "/api/calc/fleischner_2017"
}

# bash or zsh: see the payment challenge. Nothing is charged.
curl -sS -g -i -X POST 'https://api.magentlab.com/api/calc/fleischner_2017' \
  -H 'content-type: application/json' \
  --data-raw '{"items":[{"high_risk":false,"size_mm":5},{"high_risk":false,"size_mm":5}]}'

# x402 v2 sends the challenge base64-encoded in the PAYMENT-REQUIRED header (v1 sends it in the body).
# To read the header:
curl -sS -g -o /dev/null -D - -X POST 'https://api.magentlab.com/api/calc/fleischner_2017' \
  -H 'content-type: application/json' \
  --data-raw '{"items":[{"high_risk":false,"size_mm":5},{"high_risk":false,"size_mm":5}]}' \
  | grep -i '^payment-required:' | cut -d' ' -f2 | tr -d '\r' | base64 --decode

// npm i @x402/fetch @x402/evm viem
import { wrapFetchWithPayment, x402Client } from "@x402/fetch";
import { registerExactEvmScheme } from "@x402/evm/exact/client";
import { privateKeyToAccount } from "viem/accounts";

// Pays at most $0.007 per call.
const client = new x402Client().setSpendControls({ maxAmountPerPayment: "$0.007" });
registerExactEvmScheme(client, { signer: privateKeyToAccount(process.env.EVM_PRIVATE_KEY) });
const pay = wrapFetchWithPayment(fetch, client);

// Not sure it's safe to pay? ToolVet checks it first for $0.005. Pay for that from a separate
// client: this one is capped at $0.007 per payment. GET https://toolvet.app/api/v1/check?url=https%3A%2F%2Fapi.magentlab.com%2Fapi%2Fcalc%2Ffleischner_2017&method=POST
const res = await pay("https://api.magentlab.com/api/calc/fleischner_2017", {
  method: "POST",
  headers: { "content-type": "application/json" },
  body: JSON.stringify({
    "items": [
      {
        "high_risk": false,
        "size_mm": 5
      },
      {
        "high_risk": false,
        "size_mm": 5
      }
    ]
  }),
});
console.log(res.status, await res.text());

# pip install "x402[requests,evm]"
import os
from eth_account import Account
from x402 import x402ClientSync
from x402.http.clients import x402_requests
from x402.mechanisms.evm import EthAccountSigner
from x402.mechanisms.evm.exact.register import register_exact_evm_client

# Pays at most $0.007 per call.
client = x402ClientSync().set_spend_controls({"max_amount_per_payment": "$0.007"})
register_exact_evm_client(client, EthAccountSigner(Account.from_key(os.environ["EVM_PRIVATE_KEY"])))

with x402_requests(client) as session:
    res = session.post(
        "https://api.magentlab.com/api/calc/fleischner_2017",
        json={
            "items": [
                {
                    "high_risk": False,
                    "size_mm": 5,
                },
                {
                    "high_risk": False,
                    "size_mm": 5,
                },
            ],
        },
    )
    print(res.status_code, res.text)