2PCubeHealth- Artificial Intelligence Powered Diagnostic Tools for Early Detection of Cancer
Trial Snapshot
- Phase
- Not Applicable
- Status
- Recruiting
- Sponsor
- Enrollment
- 120
- Locations
- 1
- Primary Endpoint
- The proposed study involves the integration of 2PCube for Health to clinical datasets for early detection of cancer. 2PCube will be adapted and customized for health as a new platform 2PCubeHealth and is based on an optimal integration of physics-based and computational intelligence-based techniques for early detection.
Study Overview
Brief Summary
The proposedstudy on early cancer detection is grounded in the potential to significantlytransform cancer diagnosis and treatment. The development of 2PCube was carriedout through several projects completed successfully by Dr. Krishna Dev Kumar, who is an international renowned expert inArtificial Intelligence and Digital Twin-based system fault diagnosis, prognosisand recovery. The 2PCube has successfully predicted early failures (3 to 6months ahead) of critical systems in aerospace, manufacturing andtransportation sectors. Early cancer detectionis critical for early intervention and better patient outcomes. 2PCube solutionfor health (2PCubeHealth) can analyze vast amounts of medical data with highprecision, potentially reducing the rates of false positives and falsenegatives in cancer screenings. Furthermore, it can process and analyze medicaldata much faster than humans, enabling rapid diagnosis and reducing the timebetween detection and treatment initiation. This is particularly important foraggressive cancers. Finally, 2PCubeHealth’s early detection has the potentialto reduce the overall financial burden on patients and healthcare systems bypreventing late-stage cancer cases that are more costly to treat.
The proposed study will be carried out under the clinical supervision of Dr. J.K. Singh (Senior Oncologist and Padmashri Awardee) at S. S. Hospital and Research Centre, Patna. This observational study will take use of the image-based datasets of diagnosis of Cancer patients who will participate in the project work.
Study Design
- Study Type
- Observational
Eligibility Criteria
- Ages
- 10.00 Year(s) to 75.00 Year(s) (—)
- Sex
- All
Inclusion Criteria
- •Diagnosed with Cancer of breast and/or Head and Neck etc Willing to participate in the studyShould not have HIV/STDs, TB, severe mental disorders Should not be terminally ill.
Exclusion Criteria
- •Patients below 10 years age and above 75 years age Patients who are terminally ill Unwilling to participate in study Terminally ill patients Cancer patients having co-morbid conditions.
Outcomes
Primary Outcomes
The proposed study involves the integration of 2PCube for Health to clinical datasets for early detection of cancer. 2PCube will be adapted and customized for health as a new platform 2PCubeHealth and is based on an optimal integration of physics-based and computational intelligence-based techniques for early detection.
Time Frame: 2 years
Secondary Outcomes
- Development of validated system for early detection of Cancer(up to 1 year)