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Clinical Diagnosis of Diabetes Using Surface-enhanced Raman Spectroscopy Liquid Biopsy and Machine Learning

NCT06862778 · Status: COMPLETED · Phase: NA · Type: INTERVENTIONAL · Enrollment: 52

Last updated 2026-04-28

No results posted yet for this study

Summary

This project aims to adapt the gold nanoparticle-based surface-enhanced Raman spectroscopy (SERS) technology to clinical application. In this exploratory study, a measurement protocol will be established to investigate whether SERS (combined with multivariate data analysis or machine learning algorithms) allows the diagnosis of patients with diabetes.

Conditions

Interventions

DIAGNOSTIC_TEST

SERS

Spectroscopic assessment of serum samples from healthy and diabetic patients to identify characteristics for diagnosis.

Sponsors & Collaborators

  • University of Agriculture Faisalabad

    collaborator UNKNOWN

  • Nishtar Medical University

    collaborator OTHER

  • University Hospital, Aachen

    lead OTHER

Study Design

Allocation
NON_RANDOMIZED
Purpose
DIAGNOSTIC
Masking
SINGLE
Model
SINGLE_GROUP

Eligibility

Min Age
18 Years
Max Age
70 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2024-02-02
Primary Completion
2024-08-31
Completion
2025-07-31

Countries

  • Germany

Study Locations

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Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06862778 on ClinicalTrials.gov