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"Primary_Diagnosis", "description": "Main diagnosis or disease" }, { "name": "Secondary_Diagnoses", "description": "Additional diagnoses or comorbidities" }, { "name": "Current_Medications", "description": "List of current medications patient is taking" }, { "name": "Previous_Treatments", "description": "Past treatments or therapies received" }, { "name": "Lab_Values", "description": "Recent laboratory test results (HbA1c, creatinine, liver enzymes, etc)" }, { "name": "ECOG_Performance_Status", "description": "ECOG performance status score (0-4)" }, { "name": "Smoking_Status", "description": "Current smoker, former smoker, or never smoked" }, { "name": "Pregnancy_Status", "description": "For females - pregnant, not pregnant, or not applicable" }, { "name": "Blood_Pressure", "description": "Blood pressure reading in mmHg (e.g., 138/82)" } ] }, "options": {} }, "id": "70efa7ae-cef0-41e2-ad2b-43894812c557", "name": "AI Data Extractor", "type": "@n8n/n8n-nodes-langchain.informationExtractor", "typeVersion": 1.2, "position": [ 192, -96 ] }, { "parameters": { "jsCode": "const patientData = $input.first().json.output;\n\n// ROBUST NUMBER EXTRACTION\nconst extractNumber = (str) => {\n if (!str) return 0;\n const cleaned = str.toString().replace(/[^\\d.-]/g, '');\n const num = parseFloat(cleaned);\n return isNaN(num) ? 0 : num;\n};\n\n// EMBEDDED CLINICAL TRIAL DATABASE\nconst clinicalTrials = {\n \"TRIAL-DM-2025-01\": {\n trial_name: \"GLP-1 Agonist for Type 2 Diabetes\",\n phase: \"Phase 3\",\n condition: \"Type 2 Diabetes Mellitus\",\n sponsor: \"NovoPharm Research\",\n inclusion_criteria: {\n age_min: 18,\n age_max: 75,\n diagnoses_required: [\"type 2 diabetes\", \"diabetes mellitus type 2\", \"t2dm\"],\n hba1c_min: 7.0,\n hba1c_max: 11.0,\n ecog_max: 2\n },\n exclusion_criteria: {\n diagnoses_excluded: [\"type 1 diabetes\", \"diabetic ketoacidosis\", \"severe renal impairment\"],\n medications_excluded: [\"insulin\", \"sglt2 inhibitor\"],\n pregnancy: true,\n smoking_excluded: false\n },\n enrollment_target: 500,\n current_enrolled: 342,\n priority_score_base: 85\n },\n \"TRIAL-HTN-2025-02\": {\n trial_name: \"Novel ARB for Resistant Hypertension\",\n phase: \"Phase 2\",\n condition: \"Resistant Hypertension\",\n sponsor: \"CardioMed Inc\",\n inclusion_criteria: {\n age_min: 35,\n age_max: 70,\n diagnoses_required: [\"hypertension\", \"high blood pressure\", \"resistant hypertension\"],\n systolic_bp_min: 140,\n ecog_max: 1\n },\n exclusion_criteria: {\n diagnoses_excluded: [\"heart failure\", \"myocardial infarction\", \"stroke\"],\n medications_excluded: [\"ace inhibitor and arb combination\"],\n pregnancy: true,\n creatinine_max: 2.0\n },\n enrollment_target: 200,\n current_enrolled: 145,\n priority_score_base: 75\n },\n \"TRIAL-COPD-2025-03\": {\n trial_name: \"Dual Bronchodilator for Severe COPD\",\n phase: \"Phase 3\",\n condition: \"Chronic Obstructive Pulmonary Disease\",\n sponsor: \"RespiraTech\",\n inclusion_criteria: {\n age_min: 40,\n age_max: 80,\n diagnoses_required: [\"copd\", \"chronic obstructive pulmonary disease\", \"emphysema\"],\n fev1_max: 50,\n smoking_history_required: true,\n ecog_max: 2\n },\n exclusion_criteria: {\n diagnoses_excluded: [\"asthma\", \"lung cancer\", \"active tuberculosis\"],\n medications_excluded: [],\n pregnancy: true,\n current_smoker_excluded: false\n },\n enrollment_target: 350,\n current_enrolled: 287,\n priority_score_base: 80\n },\n \"TRIAL-CKD-2025-04\": {\n trial_name: \"SGLT2 Inhibitor for CKD Progression\",\n phase: \"Phase 3\",\n condition: \"Chronic Kidney Disease\",\n sponsor: \"NephroGen Labs\",\n inclusion_criteria: {\n age_min: 18,\n age_max: 85,\n diagnoses_required: [\"chronic kidney disease\", \"ckd\", \"renal impairment\"],\n egfr_min: 25,\n egfr_max: 75,\n ecog_max: 3\n },\n exclusion_criteria: {\n diagnoses_excluded: [\"kidney transplant\", \"dialysis\"],\n medications_excluded: [],\n pregnancy: true,\n potassium_max: 5.5\n },\n enrollment_target: 400,\n current_enrolled: 298,\n priority_score_base: 90\n },\n \"TRIAL-CA-2025-05\": {\n trial_name: \"Immunotherapy for Advanced NSCLC\",\n phase: \"Phase 2\",\n condition: \"Non-Small Cell Lung Cancer\",\n sponsor: \"OncoImmune Research\",\n inclusion_criteria: {\n age_min: 18,\n age_max: 999,\n diagnoses_required: [\"non-small cell lung cancer\", \"nsclc\", \"lung cancer\"],\n ecog_max: 2,\n pd_l1_min: 50\n },\n exclusion_criteria: {\n diagnoses_excluded: [\"small cell lung cancer\", \"autoimmune disease\", \"organ transplant\"],\n medications_excluded: [\"immunosuppressant\", \"systemic corticosteroids\"],\n pregnancy: true,\n previous_immunotherapy: true\n },\n enrollment_target: 150,\n current_enrolled: 89,\n priority_score_base: 95\n }\n};\n\n// DRUG INTERACTION DATABASE\nconst drugInteractions = {\n \"warfarin\": [\"nsaid\", \"aspirin\", \"antiplatelet\"],\n \"methotrexate\": [\"nsaid\", \"trimethoprim\"],\n \"digoxin\": [\"amiodarone\", \"verapamil\"],\n \"lithium\": [\"ace inhibitor\", \"arb\", \"nsaid\"],\n \"immunosuppressant\": [\"live vaccine\"]\n};\n\n// Extract patient data\nconst patientID = patientData.Patient_ID || 'UNKNOWN';\nconst patientName = patientData.Patient_Name || 'Unknown';\nconst age = extractNumber(patientData.Age);\nconst gender = (patientData.Gender || 'Unknown').toLowerCase();\nconst primaryDiagnosis = (patientData.Primary_Diagnosis || '').toLowerCase();\nconst secondaryDiagnoses = (patientData.Secondary_Diagnoses || '').toLowerCase();\nconst allDiagnoses = primaryDiagnosis + ' ' + secondaryDiagnoses;\nconst currentMedications = (patientData.Current_Medications || '').toLowerCase();\nconst previousTreatments = (patientData.Previous_Treatments || '').toLowerCase();\nconst labValues = patientData.Lab_Values || '';\nconst ecogStatus = extractNumber(patientData.ECOG_Performance_Status);\nconst smokingStatus = (patientData.Smoking_Status || '').toLowerCase();\nconst pregnancyStatus = (patientData.Pregnancy_Status || '').toLowerCase();\n\n// Parse lab values\nconst parseLabValue = (labStr, keyword) => {\n const regex = new RegExp(keyword + '[:\\\\s]+([\\\\d.]+)', 'i');\n const match = labStr.match(regex);\n return match ? parseFloat(match[1]) : null;\n};\n\nconst hba1c = parseLabValue(labValues, 'hba1c');\nconst creatinine = parseLabValue(labValues, 'creatinine');\nconst egfr = parseLabValue(labValues, 'egfr');\nconst potassium = parseLabValue(labValues, 'potassium');\nconst fev1 = parseLabValue(labValues, 'fev1');\nconst pdl1 = parseLabValue(labValues, 'pd-l1');\nconst systolicBP = parseLabValue(labValues, 'systolic') || parseLabValue(patientData.Blood_Pressure || '', 'systolic') || extractNumber((patientData.Blood_Pressure || '').split('/')[0]);\n\n// INTELLIGENCE: Match patient against all trials\nconst trialMatches = [];\n\nfor (const [trialID, trial] of Object.entries(clinicalTrials)) {\n const inclusion = trial.inclusion_criteria;\n const exclusion = trial.exclusion_criteria;\n \n let eligible = true;\n const inclusionMet = [];\n const inclusionFailed = [];\n const exclusionViolations = [];\n let matchScore = 0;\n \n // Check inclusion criteria\n \n // Age check\n if (age < inclusion.age_min || age > inclusion.age_max) {\n eligible = false;\n inclusionFailed.push(`Age ${age} outside range ${inclusion.age_min}-${inclusion.age_max}`);\n } else {\n inclusionMet.push(`Age ${age} within range`);\n matchScore += 20;\n }\n \n // Diagnosis check\n const hasDiagnosis = inclusion.diagnoses_required.some(dx => allDiagnoses.includes(dx));\n if (!hasDiagnosis) {\n eligible = false;\n inclusionFailed.push(`Required diagnosis not found: ${inclusion.diagnoses_required.join(' OR ')}`);\n } else {\n inclusionMet.push('Required diagnosis present');\n matchScore += 30;\n }\n \n // ECOG check\n if (ecogStatus > inclusion.ecog_max) {\n eligible = false;\n inclusionFailed.push(`ECOG ${ecogStatus} exceeds max ${inclusion.ecog_max}`);\n } else if (ecogStatus > 0) {\n inclusionMet.push(`ECOG ${ecogStatus} acceptable`);\n matchScore += 10;\n }\n \n // Lab value checks (trial-specific)\n if (inclusion.hba1c_min && hba1c) {\n if (hba1c < inclusion.hba1c_min || hba1c > inclusion.hba1c_max) {\n eligible = false;\n inclusionFailed.push(`HbA1c ${hba1c}% outside range ${inclusion.hba1c_min}-${inclusion.hba1c_max}%`);\n } else {\n inclusionMet.push(`HbA1c ${hba1c}% in range`);\n matchScore += 15;\n }\n }\n \n if (inclusion.egfr_min && egfr) {\n if (egfr < inclusion.egfr_min || egfr > inclusion.egfr_max) {\n eligible = false;\n inclusionFailed.push(`eGFR ${egfr} outside range ${inclusion.egfr_min}-${inclusion.egfr_max}`);\n } else {\n inclusionMet.push(`eGFR ${egfr} in range`);\n matchScore += 15;\n }\n }\n \n if (inclusion.fev1_max && fev1) {\n if (fev1 > inclusion.fev1_max) {\n eligible = false;\n inclusionFailed.push(`FEV1 ${fev1}% exceeds max ${inclusion.fev1_max}%`);\n } else {\n inclusionMet.push(`FEV1 ${fev1}% meets criteria`);\n matchScore += 15;\n }\n }\n \n if (inclusion.pd_l1_min && pdl1) {\n if (pdl1 < inclusion.pd_l1_min) {\n eligible = false;\n inclusionFailed.push(`PD-L1 ${pdl1}% below minimum ${inclusion.pd_l1_min}%`);\n } else {\n inclusionMet.push(`PD-L1 ${pdl1}% meets threshold`);\n matchScore += 15;\n }\n }\n \n if (inclusion.systolic_bp_min && systolicBP) {\n if (systolicBP < inclusion.systolic_bp_min) {\n eligible = false;\n inclusionFailed.push(`Systolic BP ${systolicBP} below minimum ${inclusion.systolic_bp_min}`);\n } else {\n inclusionMet.push(`Systolic BP ${systolicBP} meets criteria`);\n matchScore += 10;\n }\n }\n \n if (inclusion.smoking_history_required && !smokingStatus.includes('former') && !smokingStatus.includes('current')) {\n eligible = false;\n inclusionFailed.push('Smoking history required');\n }\n \n // Check exclusion criteria\n \n // Excluded diagnoses\n for (const excludedDx of exclusion.diagnoses_excluded) {\n if (allDiagnoses.includes(excludedDx)) {\n eligible = false;\n exclusionViolations.push(`Excluded diagnosis present: ${excludedDx}`);\n }\n }\n \n // Excluded medications\n for (const excludedMed of exclusion.medications_excluded) {\n if (currentMedications.includes(excludedMed)) {\n eligible = false;\n exclusionViolations.push(`Excluded medication: ${excludedMed}`);\n }\n }\n \n // Pregnancy check\n if (exclusion.pregnancy && gender === 'female' && pregnancyStatus.includes('pregnant')) {\n eligible = false;\n exclusionViolations.push('Pregnancy excluded');\n }\n \n // Lab exclusions\n if (exclusion.creatinine_max && creatinine && creatinine > exclusion.creatinine_max) {\n eligible = false;\n exclusionViolations.push(`Creatinine ${creatinine} exceeds max ${exclusion.creatinine_max}`);\n }\n \n if (exclusion.potassium_max && potassium && potassium > exclusion.potassium_max) {\n eligible = false;\n exclusionViolations.push(`Potassium ${potassium} exceeds max ${exclusion.potassium_max}`);\n }\n \n // Previous treatment exclusions\n if (exclusion.previous_immunotherapy && previousTreatments.includes('immunotherapy')) {\n eligible = false;\n exclusionViolations.push('Prior immunotherapy excluded');\n }\n \n if (exclusion.current_smoker_excluded && smokingStatus.includes('current')) {\n eligible = false;\n exclusionViolations.push('Current smoking excluded');\n }\n \n // Calculate enrollment probability\n const spotsRemaining = trial.enrollment_target - trial.current_enrolled;\n const urgencyBonus = spotsRemaining < 50 ? 10 : 0;\n const finalScore = eligible ? Math.min(trial.priority_score_base + matchScore + urgencyBonus, 100) : 0;\n \n // Determine enrollment priority\n let enrollmentPriority = 'Not Eligible';\n if (eligible) {\n if (finalScore >= 90) enrollmentPriority = 'High Priority';\n else if (finalScore >= 75) enrollmentPriority = 'Medium Priority';\n else enrollmentPriority = 'Low Priority';\n }\n \n trialMatches.push({\n Trial_ID: trialID,\n Trial_Name: trial.trial_name,\n Phase: trial.phase,\n Condition: trial.condition,\n Sponsor: trial.sponsor,\n Eligibility_Status: eligible ? '✅ ELIGIBLE' : '❌ NOT ELIGIBLE',\n Enrollment_Probability: `${finalScore}%`,\n Enrollment_Priority: enrollmentPriority,\n Inclusion_Criteria_Met: inclusionMet.join('; ') || 'None',\n Inclusion_Criteria_Failed: inclusionFailed.join('; ') || 'None',\n Exclusion_Violations: exclusionViolations.join('; ') || 'None',\n Spots_Remaining: spotsRemaining,\n Total_Enrolled: trial.current_enrolled,\n Target_Enrollment: trial.enrollment_target\n });\n}\n\n// Sort by enrollment probability (descending)\ntrialMatches.sort((a, b) => {\n const probA = parseInt(a.Enrollment_Probability);\n const probB = parseInt(b.Enrollment_Probability);\n return probB - probA;\n});\n\n// Create output for each trial match\nconst outputItems = trialMatches.map(trial => ({\n json: {\n Patient_ID: patientID,\n Patient_Name: patientName,\n Age: age.toString(),\n Gender: patientData.Gender || 'Unknown',\n Primary_Diagnosis: patientData.Primary_Diagnosis || 'Unknown',\n ECOG_Status: ecogStatus.toString(),\n ...trial,\n Processing_Timestamp: new Date().toISOString()\n }\n}));\n\nreturn outputItems;" }, "id": "ee2bbbc3-907b-4b7f-a489-feb1967a2c0b", "name": "Trial Eligibility Matcher", "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ 496, -96 ] }, { "parameters": { "operation": "append", "documentId": { "__rl": true, "value": "1BQqh115v1mdgGYIqXIJj8Kc0nf28EtTJgyex9rGTyYc", "mode": "list", "cachedResultName": "Case 55 - Clinical Trial Patient Log", "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1BQqh115v1mdgGYIqXIJj8Kc0nf28EtTJgyex9rGTyYc/edit?usp=drivesdk" }, "sheetName": { "__rl": true, "value": "gid=0", "mode": "list", "cachedResultName": "Sheet1", "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1BQqh115v1mdgGYIqXIJj8Kc0nf28EtTJgyex9rGTyYc/edit#gid=0" }, "columns": { "mappingMode": "autoMapInputData", "value": {}, "matchingColumns": [], "schema": [ { "id": "Patient_ID", "displayName": "Patient_ID", "required": false, "defaultMatch": false, "display": true, "type": 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"displayName": "Trial_Name", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Phase", "displayName": "Phase", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Condition", "displayName": "Condition", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Sponsor", "displayName": "Sponsor", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Eligibility_Status", "displayName": "Eligibility_Status", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Enrollment_Probability", "displayName": "Enrollment_Probability", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Enrollment_Priority", "displayName": 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{ "id": "Target_Enrollment", "displayName": "Target_Enrollment", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Processing_Timestamp", "displayName": "Processing_Timestamp", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true } ], "attemptToConvertTypes": false, "convertFieldsToString": false }, "options": {} }, "id": "7d7e654a-cdb5-4c7c-a482-9d6f8b81729e", "name": "Log to Google Sheets", "type": "n8n-nodes-base.googleSheets", "typeVersion": 4.7, "position": [ 688, -96 ], "credentials": { "googleSheetsOAuth2Api": { "id": "LOs2dbk9lby0NfDM", "name": "Google Sheets account" } } }, { "parameters": { "jsCode": "const allMatches = $input.all();\nconsole.log('Total items received:', allMatches.length);\nconsole.log('First item:', JSON.stringify(allMatches[0]?.json, null, 2));\n\nconst patientID = allMatches[0]?.json.Patient_ID || 'Unknown';\nconst patientName = allMatches[0]?.json.Patient_Name || 'Unknown';\nconst age = allMatches[0]?.json.Age || 'Unknown';\nconst primaryDiagnosis = allMatches[0]?.json.Primary_Diagnosis || 'Unknown';\n\nconst eligibleTrials = allMatches.filter(m => m.json?.Eligibility_Status?.includes('✅'));\nconst notEligibleTrials = allMatches.filter(m => m.json?.Eligibility_Status?.includes('❌'));\n\nconst highPriority = eligibleTrials.filter(m => m.json.Enrollment_Priority === 'High Priority');\nconst mediumPriority = eligibleTrials.filter(m => m.json.Enrollment_Priority === 'Medium Priority');\n\nconst emailSubject = eligibleTrials.length > 0 \n ? `Patient Match Found: ${patientName} - ${eligibleTrials.length} Eligible Trial(s)` \n : `No Trial Matches: ${patientName}`;\n\nlet emailBody = `Dear Research Coordinator,\n\nA patient record has been screened against active clinical trials.\n\n━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\n👤 PATIENT INFORMATION\n━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\nPatient ID: ${patientID}\nPatient Name: ${patientName}\nAge: ${age} years\nPrimary Diagnosis: ${primaryDiagnosis}\nECOG Performance Status: ${allMatches[0]?.json.ECOG_Status || 'Not recorded'}\n\n━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\n📊 SCREENING SUMMARY\n━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\nTotal Trials Screened: ${allMatches.length}\n✅ Eligible Trials: ${eligibleTrials.length}\n❌ Ineligible Trials: ${notEligibleTrials.length}\n\n`;\n\nif (eligibleTrials.length > 0) {\n emailBody += `━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\n✅ ELIGIBLE TRIALS (Ranked by Priority)\n━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\n\n`;\n \n eligibleTrials.forEach((trial, index) => {\n const priorityEmoji = trial.json.Enrollment_Priority === 'High Priority' ? '🔥' : \n trial.json.Enrollment_Priority === 'Medium Priority' ? '⚡' : '📋';\n \n emailBody += `${index + 1}. ${priorityEmoji} ${trial.json.Trial_Name}\n`;\n emailBody += ` Trial ID: ${trial.json.Trial_ID}\n`;\n emailBody += ` Phase: ${trial.json.Phase}\n`;\n emailBody += ` Sponsor: ${trial.json.Sponsor}\n`;\n emailBody += ` Enrollment Probability: ${trial.json.Enrollment_Probability}\n`;\n emailBody += ` Priority: ${trial.json.Enrollment_Priority}\n`;\n emailBody += ` Spots Remaining: ${trial.json.Spots_Remaining}/${trial.json.Target_Enrollment}\n`;\n emailBody += ` ✓ Criteria Met: ${trial.json.Inclusion_Criteria_Met}\n`;\n emailBody += `\\n`;\n });\n}\n\nif (notEligibleTrials.length > 0) {\n emailBody += `━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\n❌ INELIGIBLE TRIALS\n━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\n\n`;\n \n notEligibleTrials.slice(0, 3).forEach((trial, index) => {\n emailBody += `${index + 1}. ${trial.json.Trial_Name}\n`;\n emailBody += ` Reason: ${trial.json.Inclusion_Criteria_Failed || trial.json.Exclusion_Violations}\n`;\n emailBody += `\\n`;\n });\n \n if (notEligibleTrials.length > 3) {\n emailBody += ` ... and ${notEligibleTrials.length - 3} more (see detailed report)\n\\n`;\n }\n}\n\nif (eligibleTrials.length > 0) {\n emailBody += `━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\n🎯 RECOMMENDED NEXT STEPS\n━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\n`;\n \n if (highPriority.length > 0) {\n emailBody += `1. URGENT: Contact patient immediately for ${highPriority[0].json.Trial_Name}\n`;\n emailBody += `2. Schedule screening visit within 3-5 days\n`;\n emailBody += `3. Prepare informed consent documents\n`;\n emailBody += `4. Coordinate with principal investigator\n`;\n } else {\n emailBody += `1. Review eligible trials with patient\n`;\n emailBody += `2. Discuss trial benefits and requirements\n`;\n emailBody += `3. Schedule screening visit if patient interested\n`;\n emailBody += `4. Document patient decision\n`;\n }\n} else {\n emailBody += `━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\n📋 NEXT STEPS\n━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\nNo eligible trials at this time. Patient record will be re-screened when new trials open.\nConsider referring to standard of care treatment protocols.\n`;\n}\n\nemailBody += `\\n━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\nDetailed screening results logged to Clinical Trial Database.\nProcessed: ${new Date().toISOString()}\n\nThis is an automated screening from the Clinical Trial Eligibility System.\n\nBest regards,\nClinical Trial Screening System`;\n\nreturn {\n json: {\n email_subject: emailSubject,\n email_body: emailBody,\n recipient_email: 'research.coordinator@hospital.com',\n cc_email: eligibleTrials.length > 0 ? 'principal.investigator@hospital.com' : '',\n patient_id: patientID,\n patient_name: patientName,\n eligible_trials_count: eligibleTrials.length,\n high_priority_count: highPriority.length\n }\n};" }, "id": "e87b3fe0-3ddc-48a9-a3f2-904e9021540a", "name": "Generate Email Summary", "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ 928, -96 ] }, { "parameters": { "sendTo": "={{ $json.recipient_email }}", "subject": "={{ $json.email_subject }}", "emailType": "text", "message": "={{ $json.email_body }}", "options": {} }, "id": "b5d9e735-415f-4b80-9a49-e6d271ebfad2", "name": "Send Email via Gmail", "type": "n8n-nodes-base.gmail", "typeVersion": 2.1, "position": [ 1152, -96 ], "webhookId": "4eda12c9-65bc-4426-bc29-0c710fb0731b", "credentials": { "gmailOAuth2": { "id": "cyqCGWcggZNMcSOv", "name": "Gmail account" } } }, { "parameters": { "model": { "__rl": true, "value": "gpt-4o-mini", "mode": "list" }, "builtInTools": {}, "options": {} }, "id": "ae9ca475-c31f-4320-b77a-871f71fd359e", "name": "OpenAI GPT-4o Mini", "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi", "typeVersion": 1.3, "position": [ 192, 128 ], "credentials": { "openAiApi": { "id": "ICwxUBbatsF2sDvy", "name": "OpenAi account" } } } ], "pinData": {}, "connections": { "Monitor Patient Records Folder": { "main": [ [ { "node": "Download Patient Record", "type": "main", "index": 0 } ] ] }, "Download Patient Record": { "main": [ [ { "node": "Upload to Parser", "type": "main", "index": 0 } ] ] }, "Upload to Parser": { "main": [ [ { "node": "Wait for Parsing", "type": "main", "index": 0 } ] ] }, "Wait for Parsing": { "main": [ [ { "node": "Check Parsing Status", "type": "main", "index": 0 } ] ] }, "Check Parsing Status": { "main": [ [ { "node": "Route Based on Status", "type": "main", "index": 0 } ] ] }, "Route Based on Status": { "main": [ [ { "node": "Extract Parsed Content", "type": "main", "index": 0 } ], [ { "node": "Wait for Parsing", "type": "main", "index": 0 } ] ] }, "Extract Parsed Content": { "main": [ [ { "node": "AI Data Extractor", "type": "main", "index": 0 } ] ] }, "AI Data Extractor": { "main": [ [ { "node": "Trial Eligibility Matcher", "type": "main", "index": 0 } ] ] }, "Trial Eligibility Matcher": { "main": [ [ { "node": "Log to Google Sheets", "type": "main", "index": 0 } ] ] }, "Log to Google Sheets": { "main": [ [ { "node": "Generate Email Summary", "type": "main", "index": 0 } ] ] }, "Generate Email Summary": { "main": [ [ { "node": "Send Email via Gmail", "type": "main", "index": 0 } ] ] }, "OpenAI GPT-4o Mini": { "ai_languageModel": [ [ { "node": "AI Data Extractor", "type": "ai_languageModel", "index": 0 } ] ] } }, "active": false, "settings": { "executionOrder": "v1" }, "versionId": "84cd5334-edf3-4ded-8a74-a6dac4b7d842", "meta": { "templateCredsSetupCompleted": true, "instanceId": "3a43da28588548e21903e71cf1dc3ddd65c24bf0c62e7e4b77542ffe87ad79c6" }, "id": "XWlI30uYRepggymC", "tags": [] }