TrialGuardPRO
Built with production-grade ML models

Clinical Trial Risk Intelligence

Real-time patient dropout prediction and cohort analysis

HIPAACompliant
ISO 27001Ready

Patient Risk Assessment

Enter clinical data for dropout prediction

ⓘUnique identifier from your CTMS

ⓘPatient age in years (18-100)

ⓘTotal days since enrollment

ⓘNumber of scheduled visits attended

ⓘDay number of last attended visit

ⓘTotal adverse events reported

Batch Patient Analysis

Upload CSV or JSON files for bulk risk assessment of patient cohorts

Upload Patient Cohort

Bulk risk assessment for patient cohorts

Drop your patient data file here

Supports CSV and JSON formats from clinical trial management systems

Required: patient_id, age, gender, treatment_group, trial_phase, days_in_trial, visits_completed, last_visit_day, adverse_events

Awaiting Patient Data

Enter patient clinical information and click "Run Risk Analysis" to generate predictions

Powered by Logistic Regression (Production)

ML Model Intelligence

Production model performance metrics

PRODUCTION
Algorithm:Logistic Regression (Production)
Version:2.0.0
Response:<100ms
85.0%
Accuracy
58.0%
ROC-AUC
55.0%
Recall
35.0%
F1-Score

Feature Importance

Visit Rate28%
Time Since Last Visit22%
Adverse Event Rate18%
Burden12%
Age Adverse Risk8%

Risk Stratification Thresholds

Low (0-40%)Medium (40-80%)Critical (80+%)

System Status

API Connection
Connecting to Backend...
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Latency
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Model
04:37 AM
Last Check