[{"_1":2,"_3":-5,"_4":-5},"loaderData",{"_5":6,"_7":8,"_9":10},"actionData","errors","root",{"_185":186,"_187":188},"routes/_app.x.$handle.$name",{"_101":100,"_37":49,"_110":91,"_32":111,"_13":14,"_112":-5,"_11":113,"_114":115,"_116":117,"_118":119,"_120":121,"_26":-5,"_122":-5,"_123":-5,"_124":30,"_125":126,"_127":63,"_128":-5,"_129":-5,"_130":131},"routes/_app.x.$handle.$name.branch.$branch.version.$version.diff",{"_11":12,"_13":14,"_15":16,"_17":18,"_19":-5},"project",{"_47":48,"_37":49,"_42":50,"_51":-5,"_52":30,"_53":54,"_55":54,"_56":57,"_58":-5,"_19":59,"_60":61,"_62":63,"_64":-5,"_65":-5,"_66":67,"_68":69,"_70":-5,"_71":-5,"_72":-5,"_73":-5,"_74":75,"_76":75,"_77":78,"_79":78,"_80":78,"_81":75,"_82":75,"_83":84,"_85":86,"_87":88,"_89":30},"version",3,"changes",[25],"aiChatInfo",{"_20":21,"_22":-5,"_23":-5,"_24":-5},"userId","aiChatMessageId","84877cf8-0309-4c8b-827b-ccf4323c06c7","aiChatThreadId","aiChatThreadUserId","aiChatThreadTitle",{"_26":27,"_28":-7,"_29":30,"_31":30,"_32":33,"_34":33},"file",{"_35":36,"_37":33,"_38":39,"_40":41,"_42":43,"_44":14,"_45":46,"_29":30},"previous","deleted",false,"deletedHere","path","report.ts","latestPath","fileId","23b0a038-5c31-11f1-a3b0-ee650bb23af1","name","fileType","script","content","import type { PatientInput, PredictionResult } from \"./predict.ts\";\n\n// Builds a self-contained printable HTML medical report.\n// Users print/save as PDF from the browser (no native PDF lib needed in Deno sandbox).\nexport function buildReportHtml(p: PatientInput, r: PredictionResult): string {\n const esc = (s: unknown) =>\n String(s).replace(/[&<>]/g, (m) => ({ \"&\": \"&\", \"<\": \"<\", \">\": \">\" }[m]!));\n const date = new Date().toLocaleString();\n\n const rows = r.contributions\n .map(\n (c) =>\n `${esc(c.feature)}${esc(c.detail)}${\n c.weight > 0 ? \"→ Hypo\" : \"→ Hyper\"\n } (${Math.abs(c.weight).toFixed(0)})`,\n )\n .join(\"\");\n\n const recs = r.recommendations.map((x) => `

${esc(x)}

`).join(\"\");\n\n return `Thyroid Report\n\n\n

Thyroid Disease Detection Report

Generated ${esc(date)} · AI Clinical Decision Support

\n\n

Patient Details

Age: ${esc(p.age)}

Gender: ${esc(p.gender)}

Heart Rate: ${esc(p.heartRate)} bpm

Pregnant: ${p.pregnant ? \"Yes\" : \"No\"}

Family History: ${p.familyHistory ? \"Yes\" : \"No\"}

Fatigue: ${p.fatigue ? \"Yes\" : \"No\"}

\n\n

Laboratory Values

TSH: ${esc(p.tsh)} mIU/L

T3: ${esc(p.t3)} ng/dL

TT4: ${esc(p.tt4)} µg/dL

T4U: ${esc(p.t4u)}

FTI: ${esc(p.fti)}

\n\n

Prediction

Diagnosis: ${esc(r.diagnosis)}\n Confidence: ${esc(r.confidence)}%

Risk Level: ${esc(r.risk)}

${esc(r.explanation)}

\n\n

Contributing Factors (Explainable AI)

\n ${rows}

Feature	Finding	Direction

\n\n

Health Recommendations

${recs}

\n\n

⚠️ This automated report is decision support only and does not replace a licensed physician's diagnosis.

\n`;\n}\n","createdAt",["D",1780150154706],"branchVersion","branchId","fed6e3da-5c30-11f1-9b8c-ee650bb23af1","id","fed620b2-5c30-11f1-9b8c-ee650bb23af1","thyroid-detection",["D",1780150092882],"deletedAt","legacyEnvVars","privacy","public","httpPrivacy","description","AI-powered thyroid disease detection and risk prediction","imageUrl","8e9a5be3-2677-4cad-887e-7adb0948b6b3","pinnedFileId","198f8722-5c31-11f1-a7e3-ee650bb23af1","pinPreview",true,"pinMigrated","screenshotVersion","likeCount",0,"orgId","019e7930-e027-716a-afbc-94351f999ae6","tursoName","tursoHostname","tursoMeasuredAt","pinned","userPerm","r","valPerm","blobPerm","rw","emailPerm","sqlitePerm","projectPerm","telemetryPerm","user",{"_101":100,"_109":105},"org",{"_101":100,"_102":103,"_104":105,"_19":59,"_106":107,"_108":30},"branch",{"_13":90,"_37":91,"_47":46,"_92":48,"_93":-5,"_94":-5,"_95":-5,"_96":-5,"_97":-5,"_98":49,"_99":100},"isOwned",6,"main","projectId","forkedBranchId","forkedBranchVersion","forkedProjectPrivacy","forkedProjectId","forkedProjectOrgId","projectName","userHandle","vaishnavipm","handle","displayName","Vaishnavi PM","avatar","https://lh3.googleusercontent.com/a/ACg8ocJmHCEBFHIilC1f3MPIwNh0W7HZJzB4e8pNu7T_e6xJHFwoP2s=s96-c","tier","free","canRestrictVals","profileImageUrl","branchName","","adoptOrgId",{"_47":48,"_37":49,"_42":181,"_51":-5,"_52":30,"_53":54,"_55":54,"_56":57,"_58":-5,"_19":59,"_60":61,"_62":63,"_64":-5,"_65":-5,"_66":67,"_68":69,"_70":-5,"_71":-5,"_72":-5,"_73":-5,"_74":75,"_76":75,"_77":78,"_79":78,"_80":78,"_81":75,"_82":75,"_83":182,"_85":183,"_87":184,"_89":30},"tree",[168,169,170],"files",[168,169,170],"counts",{"_158":67,"_159":147,"_160":67,"_161":162,"_163":164},"contents",[135,136,137],"upstreamProject","upstreamBranch","emptyEnvVars","flags",[132],"hasHttpFiles","grants","orgs","customDomains",{},{"_47":133,"_134":-5},"3916aa58-5c31-11f1-9b8c-ee650bb23af1","reporterId",{"_47":151,"_37":152,"_35":61,"_139":-5,"_45":46,"_44":153,"_140":63,"_42":154,"_13":67,"_38":155,"_40":156,"_29":30,"_142":-5,"_32":157},{"_47":144,"_37":145,"_35":146,"_139":-5,"_45":46,"_44":147,"_140":63,"_42":148,"_13":67,"_38":39,"_40":149,"_29":30,"_142":-5,"_32":150},{"_47":138,"_37":33,"_35":36,"_139":-5,"_45":46,"_44":14,"_140":63,"_42":141,"_13":67,"_38":39,"_40":41,"_29":30,"_142":-5,"_32":143},"23b09fa2-5c31-11f1-a3b0-ee650bb23af1","parentId","latest",["D",1780150154706],"label",[33],"13c2874a-5c31-11f1-9fa1-ee650bb23af1","predict.ts","13c287f4-5c31-11f1-9fa1-ee650bb23af1",1,["D",1780150127979],"// Thyroid disease detection engine.\n// A transparent clinical scoring model that mimics ML output with explainable\n// per-feature contributions (SHAP-style). Reference ranges are standard adult labs.\n\nexport interface PatientInput {\n age: number;\n gender: \"male\" | \"female\";\n tsh: number; // mIU/L (ref 0.4 - 4.0)\n t3: number; // ng/dL (ref 80 - 200)\n tt4: number; // µg/dL (ref 5.0 - 12.0)\n t4u: number; // ratio (ref 0.7 - 1.8)\n fti: number; // index (ref 6 - 12)\n familyHistory: boolean;\n fatigue: boolean;\n weightChange: \"gain\" | \"loss\" | \"none\";\n heartRate: number; // bpm\n pregnant: boolean;\n}\n\nexport type Diagnosis = \"Hypothyroidism\" | \"Hyperthyroidism\" | \"Normal\";\nexport type Risk = \"Low Risk\" | \"Medium Risk\" | \"High Risk\";\n\nexport interface Contribution {\n feature: string;\n detail: string;\n weight: number; // signed: + pushes hypo, - pushes hyper\n}\n\nexport interface PredictionResult {\n diagnosis: Diagnosis;\n confidence: number; // 0-100\n risk: Risk;\n scores: { hypo: number; hyper: number; normal: number };\n contributions: Contribution[];\n explanation: string;\n recommendations: string[];\n}\n\nconst REF = {\n tsh: [0.4, 4.0],\n t3: [80, 200],\n tt4: [5.0, 12.0],\n t4u: [0.7, 1.8],\n fti: [6, 12],\n};\n\nexport function predict(p: PatientInput): PredictionResult {\n const contributions: Contribution[] = [];\n let hypo = 0;\n let hyper = 0;\n\n const add = (feature: string, detail: string, weight: number) => {\n contributions.push({ feature, detail, weight });\n if (weight > 0) hypo += weight;\n else hyper += -weight;\n };\n\n // TSH — the single most important marker (inverse relationship with thyroid activity)\n if (p.tsh > REF.tsh[1]) {\n const w = Math.min(40, 18 + (p.tsh - REF.tsh[1]) * 4);\n add(\"TSH\", `High TSH (${p.tsh} mIU/L)`, w);\n } else if (p.tsh < REF.tsh[0]) {\n const w = Math.min(40, 18 + (REF.tsh[0] - p.tsh) * 30);\n add(\"TSH\", `Low TSH (${p.tsh} mIU/L)`, -w);\n } else {\n add(\"TSH\", `Normal TSH (${p.tsh} mIU/L)`, 0);\n }\n\n // T3\n if (p.t3 < REF.t3[0]) add(\"T3\", `Low T3 (${p.t3} ng/dL)`, 15);\n else if (p.t3 > REF.t3[1]) add(\"T3\", `High T3 (${p.t3} ng/dL)`, -18);\n else add(\"T3\", `Normal T3 (${p.t3} ng/dL)`, 0);\n\n // TT4\n if (p.tt4 < REF.tt4[0]) add(\"TT4\", `Low TT4 (${p.tt4} µg/dL)`, 14);\n else if (p.tt4 > REF.tt4[1]) add(\"TT4\", `High TT4 (${p.tt4} µg/dL)`, -16);\n else add(\"TT4\", `Normal TT4 (${p.tt4} µg/dL)`, 0);\n\n // FTI\n if (p.fti < REF.fti[0]) add(\"FTI\", `Low FTI (${p.fti})`, 10);\n else if (p.fti > REF.fti[1]) add(\"FTI\", `High FTI (${p.fti})`, -12);\n else add(\"FTI\", `Normal FTI (${p.fti})`, 0);\n\n // T4U (mild signal)\n if (p.t4u < REF.t4u[0]) add(\"T4U\", `Low T4U (${p.t4u})`, 4);\n else if (p.t4u > REF.t4u[1]) add(\"T4U\", `High T4U (${p.t4u})`, -4);\n\n // Heart rate — clinical symptom\n if (p.heartRate > 100) add(\"Heart Rate\", `Tachycardia (${p.heartRate} bpm)`, -10);\n else if (p.heartRate < 60) add(\"Heart Rate\", `Bradycardia (${p.heartRate} bpm)`, 8);\n\n // Weight change\n if (p.weightChange === \"gain\") add(\"Weight\", \"Unexplained weight gain\", 8);\n else if (p.weightChange === \"loss\") add(\"Weight\", \"Unexplained weight loss\", -8);\n\n // Fatigue (slight hypo lean)\n if (p.fatigue) add(\"Fatigue\", \"Reports fatigue\", 5);\n\n // Family history raises overall suspicion equally\n if (p.familyHistory) {\n const lean = hypo >= hyper ? 4 : -4;\n add(\"Family History\", \"Positive family history\", lean);\n }\n\n const total = hypo + hyper;\n let diagnosis: Diagnosis;\n let confidence: number;\n const normalScore = Math.max(0, 40 - total);\n\n const sum = hypo + hyper + normalScore || 1;\n const scores = {\n hypo: Math.round((hypo / sum) * 100),\n hyper: Math.round((hyper / sum) * 100),\n normal: Math.round((normalScore / sum) * 100),\n };\n\n if (hypo >= hyper && hypo > 20) {\n diagnosis = \"Hypothyroidism\";\n confidence = scores.hypo;\n } else if (hyper > hypo && hyper > 20) {\n diagnosis = \"Hyperthyroidism\";\n confidence = scores.hyper;\n } else {\n diagnosis = \"Normal\";\n confidence = Math.max(scores.normal, 60);\n }\n\n // Risk level\n let risk: Risk = \"Low Risk\";\n if (diagnosis !== \"Normal\") {\n if (total > 55) risk = \"High Risk\";\n else if (total > 30) risk = \"Medium Risk\";\n else risk = \"Low Risk\";\n }\n\n // Explanation — top 2 drivers\n const drivers = [...contributions]\n .filter((c) => c.weight !== 0)\n .sort((a, b) => Math.abs(b.weight) - Math.abs(a.weight))\n .slice(0, 2);\n let explanation: string;\n if (diagnosis === \"Normal\") {\n explanation = \"All key thyroid markers fall within normal reference ranges.\";\n } else {\n const pct = Math.round(\n (drivers.reduce((s, d) => s + Math.abs(d.weight), 0) / (total || 1)) * 100,\n );\n explanation = `${drivers.map((d) => d.detail).join(\" and \")} contributed ${pct}% to the prediction of ${diagnosis}.`;\n }\n\n return {\n diagnosis,\n confidence,\n risk,\n scores,\n contributions: contributions.filter((c) => c.weight !== 0),\n explanation,\n recommendations: recommend(diagnosis, risk, p),\n };\n}\n\nfunction recommend(d: Diagnosis, risk: Risk, p: PatientInput): string[] {\n const recs: string[] = [];\n if (d === \"Hypothyroidism\") {\n recs.push(\"🩺 Consult an endocrinologist about levothyroxine therapy.\");\n recs.push(\"🥗 Diet: iodine-rich foods, selenium (Brazil nuts), avoid excess soy & raw cruciferous veg.\");\n recs.push(\"🏃 Exercise: regular low-impact cardio to support metabolism.\");\n recs.push(\"🔁 Re-test TSH/T4 in 6–8 weeks to monitor response.\");\n } else if (d === \"Hyperthyroidism\") {\n recs.push(\"🩺 Urgent endocrinology referral; discuss anti-thyroid medication.\");\n recs.push(\"🥗 Diet: adequate calories & calcium; limit iodine and caffeine.\");\n recs.push(\"🧘 Manage stress; avoid stimulants that worsen palpitations.\");\n recs.push(\"❤️ Monitor heart rate and blood pressure regularly.\");\n } else {\n recs.push(\"✅ Thyroid function appears normal — maintain a balanced diet and routine checkups.\");\n recs.push(\"🔁 Re-screen annually, or sooner if symptoms develop.\");\n }\n if (p.pregnant) recs.push(\"🤰 Pregnancy detected: thyroid levels need close monitoring — inform your OB-GYN.\");\n if (risk === \"High Risk\") recs.push(\"⚠️ High risk: seek medical consultation promptly.\");\n recs.push(\"ℹ️ This tool is decision support only and does not replace professional diagnosis.\");\n return recs;\n}\n",[145],"198f8678-5c31-11f1-a7e3-ee650bb23af1","main.tsx",2,["D",1780150137711],"http","/** @jsxImportSource https://esm.sh/react@18.2.0 */\nimport { Hono } from \"npm:hono@4.4.0\";\nimport { predict, type PatientInput } from \"./predict.ts\";\n\nconst app = new Hono();\n\n// Serve the front-end HTML page (static asset, no logic in template strings).\napp.get(\"/\", async (c) => {\n const { readFile } = await import(\"https://esm.town/v/std/utils/index.ts\");\n const html = await readFile(\"/index.html\", import.meta.url);\n return c.html(html);\n});\n\n// Prediction API\napp.post(\"/api/predict\", async (c) => {\n try {\n const body = (await c.req.json()) as PatientInput;\n const result = predict(normalize(body));\n return c.json(result);\n } catch (e) {\n return c.json({ error: String(e) }, 400);\n }\n});\n\n// Plain-text printable medical report (browser \"Save as PDF\")\napp.post(\"/api/report\", async (c) => {\n const body = (await c.req.json()) as PatientInput;\n const r = predict(normalize(body));\n const { buildReportHtml } = await import(\"./report.ts\");\n return c.html(buildReportHtml(body, r));\n});\n\nfunction normalize(b: any): PatientInput {\n return {\n age: Number(b.age) || 0,\n gender: b.gender === \"male\" ? \"male\" : \"female\",\n tsh: Number(b.tsh) || 0,\n t3: Number(b.t3) || 0,\n tt4: Number(b.tt4) || 0,\n t4u: Number(b.t4u) || 0,\n fti: Number(b.fti) || 0,\n familyHistory: !!b.familyHistory,\n fatigue: !!b.fatigue,\n weightChange: [\"gain\", \"loss\", \"none\"].includes(b.weightChange) ? b.weightChange : \"none\",\n heartRate: Number(b.heartRate) || 0,\n pregnant: !!b.pregnant,\n };\n}\n\nexport default app.fetch;\n",[152],"pulls","branches","forks","envVars",{"_165":67,"_167":67},"connections",{"_165":67,"_166":67},"count","unfilledCount","emptyCount",{"_47":151,"_37":152,"_35":61,"_139":-5,"_45":46,"_44":153,"_140":63,"_42":178,"_13":67,"_38":155,"_40":156,"_29":30,"_142":-5,"_172":179,"_32":180},{"_47":144,"_37":145,"_35":146,"_139":-5,"_45":46,"_44":147,"_140":63,"_42":175,"_13":67,"_38":39,"_40":149,"_29":30,"_142":-5,"_172":176,"_32":177},{"_47":138,"_37":33,"_35":36,"_139":-5,"_45":46,"_44":14,"_140":63,"_42":171,"_13":67,"_38":39,"_40":41,"_29":30,"_142":-5,"_172":173,"_32":174},["D",1780150154706],"children",[],[33],["D",1780150127979],[],[145],["D",1780150137711],[],[152],["D",1780150092882],{"_101":100,"_109":105},{"_101":100,"_102":103,"_104":105,"_19":59,"_106":107,"_108":30},{"_13":90,"_37":91,"_47":46,"_92":48,"_93":-5,"_94":-5,"_95":-5,"_96":-5,"_97":-5,"_98":49,"_99":100},"ctx",{"_83":-5,"_129":218,"_219":220,"_221":222,"_223":30,"_224":30,"_225":30,"_226":63,"_227":-5,"_228":-7,"_229":-7,"_230":67,"_231":30,"_232":30,"_233":-5,"_234":30,"_235":30,"_236":30,"_237":-5},"ENV",{"_189":190,"_191":192,"_193":91,"_194":195,"_196":197,"_198":199,"_200":201,"_202":203,"_204":205,"_206":207,"_208":209,"_210":211,"_212":213,"_214":215,"_216":217},"REACT_APP_SENTRY_DSN","https://586020d86f05489db63a554690acf1e9@o1398359.ingest.sentry.io/6724499","RENDER_GIT_COMMIT","899124c68db8496248a17ee95f074b807335ea7b","RENDER_GIT_BRANCH","POSTHOG_API_TOKEN","phc_nmoyuAkStEZuUp69rYlg1DZgrIt19Gx0Y4Hwf8tGgJP","POSTHOG_API_HOST","https://wart.val.town","WEB_API_TEMPLATE","https://{val}.web.val.run","APP_URL","https://www.val.town","MODULE_URL","https://esm.town","VANITY_WEB_API_TEMPLATE","https://{label}.val.run/","DENOLS_URL","https://lsp.val.town","NODE_ENV","production","CLOUDFLARE_TURNSTILE_SITE_KEY","0x4AAAAAACtaIZJH7s9rBMZ6","GOOGLE_CLIENT_ID","875989696899-jtsqkhlbdv5jrlsk8631p7ipjg3c6o62.apps.googleusercontent.com","STRIPE_PUBLISHABLE_KEY","pk_live_51N2zvWEpZTTLipIkVEwXrUG9AT0yeOOEYxszarZT1jpsZV58Ly6wlg3SltZpHN26CUalOBmUSY7adQRQiSkCZz2500qSXNkf8Y","API_URL","https://api.val.town",[],"preferencesKeybindings","default","preferencesTheme","light","preferencesFixers","preferencesCopilot","preferencesSelectionAi","preferencesCloseBrackets","preferencesChatPanelState","preferencesDprint","preferencesDenofmt","notificationCount","flagDenols","isBusinessOrgMember","businessOrgHandle","isBusinessOrgAdmin","isHigherTownieTier","navCollapsed","currentOrgId"]

Diff · v3