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| Name | Class |
|---|---|
| IISER Pune | UNKNOWN |
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The investigators are testing the ability of convolutional neural networks (CNNs), that is artificial intelligence, on smartphone photographs in detecting inflammatory arthritis. This promises to be an efficient, accurate, and non-invasive diagnostic tool that will significantly improve early detection and management of inflammatory arthritis.
Over the past 4 years the investigators have aimed to help the early detection of arthritis leveraging artificial intelligence. This project aims to detect arthritis based on smart phone photographs of joint areas that make it scalable and available in the community. This group first developed a compelling proof-of-concept pipeline and models using 100 patients. (published in Frontiers in Medicine, Nov 2023, wherein they demonstrated that this technology works with reasonable accuracy in the lab, viz Technology Readiness Level currently stands at 3-4). They followed with a newer paper (submitted for publication, available on preprint server MedRxiv) that trained two different CNNs, a screening CNN on uncropped hands that distinguishes patients from controls followed by joint specific detections.
The system involves supporting infrastructure that will enable efficient detection of arthritis. This includes
This is a Prospective, non-interventional study and this project only involves an investigator taking a smartphone photograph of some joint areas kept in standardized positions. This involves no risk to the patient.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Inflammatory arthritis | Patients with inflammatory arthritis regardless of etiology including rheumatoid arthritis, psoriatic arthritis, systemic lupus erythematosis and viral arthritis |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| AI assisted smartphone diagnosis | Diagnostic Test | Patients will examination and clinical photographs for convolutional networks to diagnose inflammatory arthritis |
|
| Measure | Description | Time Frame |
|---|---|---|
| Accuracy of AI diagnosis against specialist (rheumatologist) opinion | Concordance of detection of synovitis by convolutional neural network (binary) with a clinically diagnosed specialist opinion (rheumatologist opinion) | 3 years |
| Measure | Description | Time Frame |
|---|---|---|
| Accuracy of AI diagnosis against imaging diagnosis on Ultrasound | Concordance of detection of synovitis by convolutional neural network (binary) compared to musculoskeletal ultrasound | 3 years |
| Sensitivity to change |
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Inclusion Criteria:
Exclusion Criteria:
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All patients with inflammatory arthritis. This can include but is not limited to rheumatoid arthritis, lupus, psoriatic arthritis, peripheral spondyloarthritis, viral arthritis.
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| Name | Affiliation | Role |
|---|---|---|
| Sanat Phatak, MD, DM | Med2Measure | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Rheumatology Clinic | Pune | Maharashtra | 411004 | India | ||
| Poona Superspeciality Clinic |
Deidentified photographs and clinical information excluding HIPAA variables
January 2027-January 2028
Researchers with a scientific plan can get in touch with the principal investigator with a brief note.
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| ID | Term |
|---|---|
| D001172 | Arthritis, Rheumatoid |
| D001168 | Arthritis |
| ID | Term |
|---|---|
| D007592 | Joint Diseases |
| D009140 | Musculoskeletal Diseases |
| D012216 | Rheumatic Diseases |
| D003240 | Connective Tissue Diseases |
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Can the convolutional neural network detect change from an inflamed to an non-inflamed joint
| 3 years |
| Pune |
| 411001 |
| India |
| D017437 |
| Skin and Connective Tissue Diseases |
| D001327 | Autoimmune Diseases |
| D007154 | Immune System Diseases |