## 3 Results
### Data Availability  
Automatic diagnosis systems based on artificial intelligence, particularly methods based on supervised learning (SL), are often confronted with the challenge of the limited availability of labeled databases of sufficient size. In studies involving the diagnosis of knee osteoarthritis based on radiographic images, the Osteoarthritis Initiative (OAI) and the Multicenter Osteoarthritis Study (MOST) are the two most frequently cited datasets. Both the OAI and MOST studies were approved by the Institutional Review Board (IRB) of the coordinating center, the University of California, San Francisco, as well as the IRBs of the collaborating and clinical centers. The OAI is a longitudinal observational study conducted by the US National Institutes of Health (NIH) on both men and women over a ten-year period. The dataset comprises knee images of 4796 participants aged 45-69 years, examined by X-ray, MRI, and other means during nine follow-up exams over a period of 96 months.  
\begin{table}
\begin{tabular}{l l} \hline \hline
**ID** & **Filtering Criteria** \\ \hline SC1 & The article must include at least the Title, Abstract, Source, Year, and Doi. \\ \hline SC2 & Must be in English. \\ \hline SC3 & Abstract must discuss the implementation of artificial intelligence in knee \\  & osteoarthritis diagnosis. \\ \hline SC4 & The article must have been published between January 2018 and May 2024. \\ \hline SC5 & Should not be just a review, survey, preprint, or roadmap. \\ \hline \hline \end{tabular}
\end{table}
Table 2: Inclusion criteria for the filtering stage of the literature review.  
\begin{table}
\begin{tabular}{l l} \hline \hline
**ID** & **Eligibility Criteria** \\ \hline EC1 & Does not address the implementation of artificial intelligence in the KOA diagnosis. \\ \hline EC2 & Is not based on X-ray images. \\ \hline EC3 & Full text not accessible. \\ \hline \hline \end{tabular}
\end{table}
Table 3: Exclusion criteria for the eligibility phase of the literature review.  
The dataset comprises 4446 X-ray images of knees acquired at a fixed angle of 10\({}^{\circ}\) and labeled according to the KL scale by Boston University. The objective of the Osteoarthritis Initiative (OAI) is to facilitate the conduct of new research on osteoarthritis, with the aim of developing novel treatments and diagnostic tools. The MOST dataset comprises lateral and posterior-anterior (PA) views of knee X-ray images of men and women aged 50 to 79. It contains 2920 radiographic images acquired over 84 months and labeled according to KL grades, which are not part of the OAI. The posterior-anterior (PA) view of knee images was acquired at 5\({}^{\circ}\), 10\({}^{\circ}\), and 15\({}^{\circ}\). OAI is funded by the National Institutes of Health (NIH) in a public-private partnership with Merck Research Laboratories, Novartis Pharmaceuticals Corporation, GlaxoSmithKline, and Pfizer, Inc. Similarly, MOST was financed by the NIH in cooperation with Felson, Torner, [PERSON], and Nevitt. Other studies have utilized pre-prepared datasets accessible on the Kaggle platform (12-14). While numerous other studies have employed local databases, Table 4 provides a summary of the various datasets utilized in the literature, along with the means of accessing them.