Diagnosa Penyakit Radang Sendi Menggunakan Metode Dempster Shafer
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Rapid technological advancements have brought convenience to various fields, including healthcare. Osteoarthritis (OA) is a chronic degenerative joint disease that often affects the knees and hips, particularly in the elderly, and is a major cause of pain, joint dysfunction, and reduced quality of life. The prevalence of OA increases with age, with risk factors such as obesity, excessive activity, and muscle weakness. Early and accurate diagnosis is essential for appropriate treatment. This study aims to develop a diagnostic system for inflammatory arthritis, specifically osteoarthritis, using the Dempster-Shafer method. This method was chosen because of its ability to combine various evidence and expert beliefs to produce a more accurate diagnosis. By utilizing mathematical proof theory, this system is expected to assist medical personnel in detecting OA symptoms more efficiently. The research findings are expected to contribute to the healthcare sector, particularly in improving the accuracy of osteoarthritis diagnosis, allowing for earlier and more appropriate treatment. This system can also be a supporting tool for doctors and patients in understanding joint health conditions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it