| MIT License |
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| Copyright (c) 2025 CAMLAs (Computer Vision and Machine Learning Lab) |
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| Permission is hereby granted, free of charge, to any person obtaining a copy |
| of this software and associated documentation files (the "Software"), to deal |
| in the Software without restriction, including without limitation the rights |
| to use, copy, modify, merge, publish, distribute, sublicense, and/or sell |
| copies of the Software, and to permit persons to whom the Software is |
| furnished to do so, subject to the following conditions: |
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| The above copyright notice and this permission notice shall be included in all |
| copies or substantial portions of the Software. |
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| THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR |
| IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, |
| FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE |
| AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER |
| LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, |
| OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE |
| SOFTWARE. |
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| MEDICAL DISCLAIMER: |
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| This software is intended for research and educational purposes only. |
| It is NOT intended for clinical diagnosis, medical decision-making, or |
| patient care. The software should NOT be used as a substitute for |
| professional medical advice, diagnosis, or treatment. |
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| Users of this software acknowledge that: |
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| 1. The software is experimental and may contain errors or inaccuracies |
| 2. Medical decisions should always be made by qualified healthcare professionals |
| 3. The developers and CAMLAs organization are not responsible for any |
| medical decisions or outcomes resulting from the use of this software |
| 4. Users assume all risks associated with the use of this software |
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| By using this software, you agree to these terms and acknowledge that you |
| understand the limitations and appropriate use cases for this technology. |
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| ATTRIBUTION: |
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| If you use this software in academic research, please cite: |
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| CAMLAs Research Team. (2025). Ovarian Cancer Detection API using Hybrid |
| ConvNeXt-NASNet Architecture. HuggingFace Spaces. |
| https://huggingface.co/spaces/CAMLAs/ovarian-cancer |
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| THIRD-PARTY LICENSES: |
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| This software uses the following third-party libraries and frameworks: |
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| - PyTorch: BSD-style license (https://github.com/pytorch/pytorch/blob/master/LICENSE) |
| - timm: Apache License 2.0 (https://github.com/rwightman/pytorch-image-models/blob/master/LICENSE) |
| - scikit-learn: BSD License (https://github.com/scikit-learn/scikit-learn/blob/main/COPYING) |
| - Gradio: Apache License 2.0 (https://github.com/gradio-app/gradio/blob/main/LICENSE) |
| - NumPy: BSD License (https://github.com/numpy/numpy/blob/main/LICENSE.txt) |
| - Pillow: HPND License (https://github.com/python-pillow/Pillow/blob/main/LICENSE) |
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| All third-party libraries retain their original licenses and copyrights. |
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