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  WISEST (**W**h**I**ch **S**ystematic **E**vidence **S**ynthesis is bes**T**) is an innovative tool designed to streamline the quality assessment of systematic reviews (SRs) using automated deep neural information retrieval techniques. Developed collaboratively by information retrieval specialists and health knowledge synthesis experts, WISEST addresses information overload by automating responses to the widely used ROBIS and AMSTAR-2 frameworks, enhancing the consistency and efficiency of SR evaluation. The user-friendly interface, refined through feedback from active SR practitioners, ensures accessibility for both technical and non-technical users. WISEST’s open-source code base promotes transparency and adaptability, empowering researchers and healthcare professionals to make more reliable, evidence-based decisions with reduced effort and improved accuracy.
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  ## Model Details
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  ### Model Description
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- - **Developed by:** [More Information Needed]
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- - **Funded by [optional]:** [More Information Needed]
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  - **Shared by [optional]:** [More Information Needed]
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  - **Model type:** [More Information Needed]
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- - **Language(s) (NLP):** [More Information Needed]
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- - **License:** [More Information Needed]
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- - **Finetuned from model [optional]:** [More Information Needed]
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  ### Model Sources [optional]
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  - **Repository:** [More Information Needed]
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  - **Paper [optional]:** [More Information Needed]
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- - **Demo [optional]:** [More Information Needed]
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  ## Uses
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  WISEST (**W**h**I**ch **S**ystematic **E**vidence **S**ynthesis is bes**T**) is an innovative tool designed to streamline the quality assessment of systematic reviews (SRs) using automated deep neural information retrieval techniques. Developed collaboratively by information retrieval specialists and health knowledge synthesis experts, WISEST addresses information overload by automating responses to the widely used ROBIS and AMSTAR-2 frameworks, enhancing the consistency and efficiency of SR evaluation. The user-friendly interface, refined through feedback from active SR practitioners, ensures accessibility for both technical and non-technical users. WISEST’s open-source code base promotes transparency and adaptability, empowering researchers and healthcare professionals to make more reliable, evidence-based decisions with reduced effort and improved accuracy.
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+ You can find the model demo at [https://wisest.ls3.rnet.torontomu.ca](https://wisest.ls3.rnet.torontomu.ca)
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+ You can find data used for fine-tuning at [https://wisest-data.ls3.rnet.torontomu.ca](https://wisest-data.ls3.rnet.torontomu.ca)
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+ You can find the annotation studio developed for the model at [https://github.com/radinhamidi/WISEST-Annotation-Platform](https://github.com/radinhamidi/WISEST-Annotation-Platform)
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+ You can find the pipeline implemented for data cleaning and preparation at [https://github.com/radinhamidi/WISEST-Data](https://github.com/radinhamidi/WISEST-Data)
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  ## Model Details
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  ### Model Description
 
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+ - **Developed by:** Naser Al-Obeidat, Radin Hamidi Rad
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+ - **Funded by [optional]:** Laboratory for Systems, Software and Semantics: [https://ls3.rnet.torontomu.ca](https://ls3.rnet.torontomu.ca)
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  - **Shared by [optional]:** [More Information Needed]
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  - **Model type:** [More Information Needed]
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+ - **Language(s) (NLP):** English
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+ - **License:** CC-BY-NC 4.0
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+ - **Finetuned from model [optional]:** Llama-3.1-8B
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  ### Model Sources [optional]
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  - **Repository:** [More Information Needed]
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  - **Paper [optional]:** [More Information Needed]
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+ - **Demo [optional]:** https://wisest.ls3.rnet.torontomu.ca
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  ## Uses
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