## Horizontal Bar Chart: Improvement over Base Model by Category ### Overview The image is a horizontal bar chart comparing the improvement over a base model for two different methods (SFT Only and SFT+RL (Ours)) across various categories. The x-axis represents the percentage of improvement, and the y-axis lists the categories. ### Components/Axes * **Title:** There is no explicit title on the chart. * **X-axis:** "Improvement over Base Model (%)". The scale ranges from 0% to 25% with tick marks at intervals of 5%. * **Y-axis:** Categories: Ear, Congenital, Neoplasms, Circulatory, Pharmacology, Eye, Musculoskeletal, Blood/Immune, Infectious, Respiratory, Skin, Endocrine, Digestive, Nervous, Mental Health. * **Legend:** Located in the bottom-right corner. * Pink: SFT Only * Orange: SFT+RL (Ours) ### Detailed Analysis The chart displays the improvement of two models, "SFT Only" and "SFT+RL (Ours)", over a base model, across 15 different categories. The length of each bar corresponds to the percentage of improvement. **SFT Only (Pink Bars):** * Mental Health: ~4% * Nervous: ~7% * Digestive: ~7% * Endocrine: ~6% * Skin: ~8% * Respiratory: ~8% * Infectious: ~10% * Blood/Immune: ~4% * Musculoskeletal: ~5% * Eye: ~11% * Pharmacology: ~12% * Circulatory: ~14% * Neoplasms: ~15% * Congenital: ~14% * Ear: ~16% **SFT+RL (Ours) (Orange Bars):** * Mental Health: ~12% * Nervous: ~14% * Digestive: ~14% * Endocrine: ~15% * Skin: ~16% * Respiratory: ~16% * Infectious: ~16% * Blood/Immune: ~15% * Musculoskeletal: ~17% * Eye: ~18% * Pharmacology: ~18% * Circulatory: ~21% * Neoplasms: ~22% * Congenital: ~22% * Ear: ~24% **Trend Verification:** For each category, the orange bar (SFT+RL) is longer than the pink bar (SFT Only), indicating that SFT+RL consistently outperforms SFT Only across all categories. ### Key Observations * SFT+RL (Ours) consistently shows a higher improvement over the base model compared to SFT Only across all categories. * The "Ear" category shows the highest improvement for both methods. * The "Mental Health" category shows the lowest improvement for both methods. * The difference in improvement between SFT Only and SFT+RL is most pronounced in the "Mental Health" category. ### Interpretation The data suggests that incorporating Reinforcement Learning (RL) into the SFT model (SFT+RL) leads to a significant improvement in performance across all tested categories compared to using SFT alone. The magnitude of improvement varies by category, indicating that the benefit of RL is not uniform across different tasks or domains. The "Ear" category benefits the most from both methods, while "Mental Health" shows the least improvement, suggesting that these categories may have inherent differences in complexity or data availability. The consistent outperformance of SFT+RL highlights the potential of combining supervised fine-tuning with reinforcement learning for enhancing model performance.

## Bar Chart: Improvement over Base Model by Medical Specialty ### Overview This is a horizontal bar chart comparing the improvement over a base model for two different approaches: "SFT Only" and "SFT+RL (Ours)", across various medical specialties. The improvement is measured in percentage (%). The chart displays the performance gain for each specialty using two distinct colored bars. ### Components/Axes * **Y-axis (Vertical):** Lists medical specialties: Ear, Congenital, Neoplasms, Circulatory, Pharmacology, Eye, Musculoskeletal, Blood/Immune, Infectious, Respiratory, Skin, Endocrine, Digestive, Nervous, Mental Health. * **X-axis (Horizontal):** Represents the "Improvement over Base Model (%)", ranging from 0 to 25. * **Legend (Bottom-Right):** * Magenta/Purple bar: "SFT Only" * Orange bar: "SFT+RL (Ours)" ### Detailed Analysis The chart consists of 15 horizontal bars, grouped by medical specialty. For each specialty, there are two bars representing the improvement achieved by "SFT Only" and "SFT+RL (Ours)". Here's a breakdown of the approximate improvement percentages for each specialty: * **Ear:** SFT Only ~14%, SFT+RL ~22% * **Congenital:** SFT Only ~11%, SFT+RL ~19% * **Neoplasms:** SFT Only ~12%, SFT+RL ~21% * **Circulatory:** SFT Only ~8%, SFT+RL ~23% * **Pharmacology:** SFT Only ~7%, SFT+RL ~16% * **Eye:** SFT Only ~10%, SFT+RL ~18% * **Musculoskeletal:** SFT Only ~12%, SFT+RL ~17% * **Blood/Immune:** SFT Only ~10%, SFT+RL ~19% * **Infectious:** SFT Only ~8%, SFT+RL ~13% * **Respiratory:** SFT Only ~9%, SFT+RL ~16% * **Skin:** SFT Only ~8%, SFT+RL ~18% * **Endocrine:** SFT Only ~9%, SFT+RL ~17% * **Digestive:** SFT Only ~7%, SFT+RL ~15% * **Nervous:** SFT Only ~8%, SFT+RL ~16% * **Mental Health:** SFT Only ~5%, SFT+RL ~12% **Trends:** * The "SFT+RL (Ours)" consistently outperforms "SFT Only" across all medical specialties. * The orange bars (SFT+RL) generally slope upwards, indicating a positive correlation between specialty and improvement. * The magenta bars (SFT Only) also show a general upward trend, but less pronounced than the orange bars. ### Key Observations * The largest improvement difference between the two methods is observed in the "Circulatory" specialty, with SFT+RL achieving approximately 23% improvement compared to SFT Only's 8%. * The smallest improvement difference is in "Mental Health", with SFT+RL at 12% and SFT Only at 5%. * "SFT+RL (Ours)" consistently provides a substantial improvement over "SFT Only" in all categories, suggesting the reinforcement learning component is beneficial. ### Interpretation The data suggests that incorporating Reinforcement Learning (RL) with Supervised Fine-Tuning (SFT) significantly enhances model performance across a diverse range of medical specialties. The consistent outperformance of "SFT+RL (Ours)" indicates that RL effectively refines the model's capabilities beyond what can be achieved through SFT alone. The varying degrees of improvement across specialties might reflect the complexity of each field or the availability of relevant training data. The largest gains in "Circulatory" could indicate that this specialty benefits most from the RL component, potentially due to the intricate relationships within the circulatory system. The relatively smaller gain in "Mental Health" might suggest that this area is already well-represented in the base model or that the RL component has limited impact due to the subjective nature of the data. Overall, the chart demonstrates the potential of RL to improve the accuracy and effectiveness of models in medical applications.

## Horizontal Grouped Bar Chart: Improvement Over Base Model by Medical Category ### Overview This image is a horizontal grouped bar chart comparing the performance improvement of two different methods ("SFT Only" and "SFT+RL (Ours)") over a base model across 15 distinct medical categories. The improvement is measured as a percentage. ### Components/Axes * **Chart Type:** Horizontal Grouped Bar Chart. * **Y-Axis (Vertical):** Lists 15 medical categories. From top to bottom: 1. Ear 2. Congenital 3. Neoplasms 4. Circulatory 5. Pharmacology 6. Eye 7. Musculoskeletal 8. Blood/Immune 9. Infectious 10. Respiratory 11. Skin 12. Endocrine 13. Digestive 14. Nervous 15. Mental Health * **X-Axis (Horizontal):** Labeled "Improvement over Base Model (%)". The scale runs from 0 to 25, with major tick marks at 0, 5, 10, 15, 20, and 25. * **Legend:** Located in the bottom-right corner of the chart area. * **Magenta/Pink Bar:** Labeled "SFT Only". * **Orange Bar:** Labeled "SFT+RL (Ours)". * **Data Series:** Each medical category has two bars grouped together: a magenta bar (SFT Only) on the left and an orange bar (SFT+RL) on the right. ### Detailed Analysis Below is an analysis of each category. For each, the visual trend is described first (orange bar vs. magenta bar), followed by approximate percentage values estimated from the x-axis. 1. **Ear:** * **Trend:** The orange bar (SFT+RL) is significantly longer than the magenta bar (SFT Only). * **Values:** SFT Only ≈ 17%, SFT+RL ≈ 22.5%. 2. **Congenital:** * **Trend:** The orange bar is longer than the magenta bar. * **Values:** SFT Only ≈ 14%, SFT+RL ≈ 22.5%. 3. **Neoplasms:** * **Trend:** The orange bar is longer than the magenta bar. * **Values:** SFT Only ≈ 13%, SFT+RL ≈ 22%. 4. **Circulatory:** * **Trend:** The orange bar is substantially longer than the magenta bar. * **Values:** SFT Only ≈ 10%, SFT+RL ≈ 21%. 5. **Pharmacology:** * **Trend:** The orange bar is longer than the magenta bar. * **Values:** SFT Only ≈ 11%, SFT+RL ≈ 18.5%. 6. **Eye:** * **Trend:** The orange bar is longer than the magenta bar. * **Values:** SFT Only ≈ 12%, SFT+RL ≈ 18%. 7. **Musculoskeletal:** * **Trend:** The orange bar is much longer than the magenta bar. * **Values:** SFT Only ≈ 6%, SFT+RL ≈ 17%. 8. **Blood/Immune:** * **Trend:** The orange bar is dramatically longer than the magenta bar. * **Values:** SFT Only ≈ 4%, SFT+RL ≈ 17%. 9. **Infectious:** * **Trend:** The orange bar is longer than the magenta bar. * **Values:** SFT Only ≈ 10%, SFT+RL ≈ 16%. 10. **Respiratory:** * **Trend:** The orange bar is longer than the magenta bar. * **Values:** SFT Only ≈ 8.5%, SFT+RL ≈ 16%. 11. **Skin:** * **Trend:** The orange bar is longer than the magenta bar. * **Values:** SFT Only ≈ 9%, SFT+RL ≈ 15.5%. 12. **Endocrine:** * **Trend:** The orange bar is longer than the magenta bar. * **Values:** SFT Only ≈ 7%, SFT+RL ≈ 15%. 13. **Digestive:** * **Trend:** The orange bar is longer than the magenta bar. * **Values:** SFT Only ≈ 6.5%, SFT+RL ≈ 13.5%. 14. **Nervous:** * **Trend:** The orange bar is longer than the magenta bar. * **Values:** SFT Only ≈ 10.5%, SFT+RL ≈ 13.5%. 15. **Mental Health:** * **Trend:** The orange bar is longer than the magenta bar. * **Values:** SFT Only ≈ 6%, SFT+RL ≈ 13%. ### Key Observations * **Consistent Superiority:** In all 15 medical categories, the "SFT+RL (Ours)" method (orange bars) shows a greater improvement over the base model than the "SFT Only" method (magenta bars). * **Magnitude of Improvement:** The improvement for "SFT+RL" ranges from approximately 13% (Mental Health, Digestive) to 22.5% (Ear, Congenital). The improvement for "SFT Only" ranges from approximately 4% (Blood/Immune) to 17% (Ear). * **Largest Gains:** The most significant absolute improvements for the "SFT+RL" method are seen in the "Ear," "Congenital," and "Neoplasms" categories, all exceeding 20%. * **Smallest Gains:** The smallest improvements for "SFT+RL" are in "Mental Health" and "Digestive," both around 13-13.5%. * **Largest Performance Gap:** The most substantial difference between the two methods appears in the "Blood/Immune" category, where "SFT+RL" shows an improvement of ~17% compared to only ~4% for "SFT Only." * **Smallest Performance Gap:** The smallest difference between the methods is in the "Nervous" category, where the values are closest (~10.5% vs. ~13.5%). ### Interpretation The data strongly suggests that the proposed method, which combines Supervised Fine-Tuning with Reinforcement Learning ("SFT+RL"), consistently and significantly outperforms a method using Supervised Fine-Tuning alone ("SFT Only") across a wide spectrum of medical domains when measured by improvement over a base model. The fact that the orange bar is longer in every single category indicates a robust and generalizable advantage for the "SFT+RL" approach. The variation in the size of the improvement (from ~13% to ~22.5%) suggests that the effectiveness of the method is domain-dependent. Categories like "Ear," "Congenital," and "Neoplasms" may have characteristics (e.g., data structure, task complexity) that are particularly well-suited to the reinforcement learning component, leading to the highest gains. Conversely, domains like "Mental Health" and "Digestive" might present challenges that are less mitigated by this specific RL approach, though it still provides a clear benefit. The dramatic gap in categories like "Blood/Immune" highlights a potential key finding: the "SFT Only" method may struggle significantly in certain complex or data-sparse medical areas, a weakness that the "SFT+RL" method appears to correct substantially. Overall, the chart serves as compelling evidence for the efficacy of integrating reinforcement learning with supervised fine-tuning to enhance model performance in medical applications.

## Horizontal Bar Chart: Improvement over Base Model by Medical Category ### Overview The chart compares the performance improvement of two methods ("SFT Only" and "SFT+RL (Ours)") across 15 medical categories. The x-axis represents improvement percentage (0-25%), while the y-axis lists medical specialties. "SFT+RL (Ours)" consistently outperforms "SFT Only" in all categories. ### Components/Axes - **Y-Axis Categories**: Ear, Congenital, Neoplasms, Circulatory, Pharmacology, Eye, Musculoskeletal, Blood/Immune, Infectious, Respiratory, Skin, Endocrine, Digestive, Nervous, Mental Health - **X-Axis**: Improvement over Base Model (%) (0-25% in 5% increments) - **Legend**: - Pink: SFT Only - Orange: SFT+RL (Ours) - **Legend Position**: Bottom-right corner ### Detailed Analysis | Category | SFT Only (%) | SFT+RL (Ours) (%) | |--------------------|--------------|-------------------| | Ear | ~17 | ~23 | | Congenital | ~14 | ~22 | | Neoplasms | ~13 | ~21 | | Circulatory | ~10 | ~20 | | Pharmacology | ~11 | ~18 | | Eye | ~12 | ~17 | | Musculoskeletal | ~6 | ~16 | | Blood/Immune | ~4 | ~15 | | Infectious | ~10 | ~15 | | Respiratory | ~9 | ~15 | | Skin | ~9 | ~15 | | Endocrine | ~7 | ~15 | | Digestive | ~6 | ~14 | | Nervous | ~11 | ~14 | | Mental Health | ~6 | ~13 | ### Key Observations 1. **Consistent Outperformance**: "SFT+RL (Ours)" exceeds "SFT Only" in all categories, with average improvements of ~15% vs. ~9%. 2. **Highest Gains**: - Ear (+6% absolute improvement) - Congenital (+8%) - Neoplasms (+8%) 3. **Lowest Gains**: - Blood/Immune (SFT Only: ~4%) - Mental Health (SFT+RL: ~13%) 4. **Narrowest Gaps**: - Mental Health (+7%) - Digestive (+8%) ### Interpretation The data demonstrates that integrating RL with SFT significantly enhances performance across medical domains. The largest improvements occur in **Ear** and **Congenital** categories, suggesting these areas benefit most from RL augmentation. **Blood/Immune** shows the weakest baseline performance with SFT Only (~4%), indicating inherent challenges in this domain. The consistent trend across all categories validates the effectiveness of the SFT+RL approach, though Mental Health and Digestive categories show relatively smaller gains, potentially due to domain-specific complexities. ### Spatial Grounding & Trend Verification - **Legend**: Confirmed alignment with bar colors (pink/orange). - **Trend Check**: All orange bars (SFT+RL) are visually longer than pink bars (SFT Only), matching the numerical data. - **Outliers**: Blood/Immune (SFT Only) and Mental Health (SFT+RL) represent the lowest performance extremes.