Sentence examples for recommendations based on an from inspiring English sources

Exact(11)

Experts devised seven recommendations based on an analysis of existing research.

Another form is brief, dynamic psychotherapy, in which the clinician makes recommendations based on an understanding of the situation and the reasons for resisting change.

Second, while the RUC makes its recommendations based on an anonymous two-thirds majority vote, about 80 percent of those voting to begin with — accounting for 23 of the 29 seats — are physicians representing professional societies.

Micro-future scenarios provide context-sensitive information, alternative future paths and recommendations based on an individual's personal circumstances and her environment.

Already we're seeing multiple, superior avenues for product discovery enabled by AI: You'll be able to take pictures of items you like, search visually online and get personal recommendations based on an AI-generated model.

Former Attorney General Eric Holder and his law partner Tammy Albarrán announced some highly anticipated recommendations based on an internal harassment probe to employees in an all-hands meeting this morning.

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Similar(49)

The Institute of Medicine made its recommendations based on a population-based model; the Endocrine Society's Practice Guidelines on Vitamin D was for the prevention and treatment of vitamin D deficiency, which helps explain the differences in the recommendations.

Evidence-based practitioners need to be aware that any conclusions and recommendations based on a systematic review with a meta-analysis should be read with caution even if the methodology is rigorous.

Panasonic and Samsung demonstrated a similar feature in their TV sets that makes recommendations based on a person's TV habits.

As explained in a company blog post, a Facebook account is now required to log into Vevo, and the site will make playlist recommendations based on a user's "likes" on Facebook.

For starters, the iPad version of Shazam generates charts of the songs that have been most frequently tagged and makes music recommendations based on a user's tagging history.

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