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@@ -36,17 +36,17 @@ ReidLM is designed for direct use in generating insightful and reliable informat
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  ReidLM is specifically designed for generating information related to rare diseases and should not be used for the following purposes:
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- -Non-Medical Domains: ReidLM is optimized for rare disease information and may not perform well in other domains such as finance, law, general health conditions, or any other non-medical fields.<br>
 
 
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- -General Conversational AI: While capable of generating detailed information on rare diseases, ReidLM may not be suitable for general conversational AI tasks that require a broad understanding of various topics.
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  ## Bias, Risks, and Limitations
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  ReidLM, like all large language models, has inherent biases and limitations that users should be aware of:<br>
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- -Ethical Concerns: There is a risk of over-reliance on AI for medical decisions, which should always be validated by healthcare professionals.<br>
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- -Accuracy: While the model strives for accuracy, it may generate incorrect or incomplete information, especially in highly specialized or novel cases.
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  <!---### Recommendations
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  This section is meant to convey recommendations with respect to the bias, risk, and technical limitations.
 
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  ReidLM is specifically designed for generating information related to rare diseases and should not be used for the following purposes:
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+ - **Non-Medical Domains:** ReidLM is optimized for rare disease information and may not perform well in other domains such as finance, law, general health conditions, or any other non-medical fields.<br>
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+ - **General Conversational AI:** While capable of generating detailed information on rare diseases, ReidLM may not be suitable for general conversational AI tasks that require a broad understanding of various topics. <br>
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+
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  ## Bias, Risks, and Limitations
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  ReidLM, like all large language models, has inherent biases and limitations that users should be aware of:<br>
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+ - **Ethical Concerns:** There is a risk of over-reliance on AI for medical decisions, which should always be validated by healthcare professionals.<br>
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+ - **Accuracy:** While the model strives for accuracy, it may generate incorrect or incomplete information, especially in highly specialized or novel cases.
 
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  <!---### Recommendations
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  This section is meant to convey recommendations with respect to the bias, risk, and technical limitations.