Susan Cheng - Profile and Journalist Details

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Susan Cheng

Susan Cheng

Verified

Managing Producer, WEBTOON

Final Covers

TV Shows , Fashion, Beauty, Eating disorders

Journalist Type

Seniority Positions

Industries

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Medium Formats

Content

Total articles 288

  • Evaluation of Brain Age as a Specific Marker of Brain Health

    By Kim-Ngan H. Nguyen, Chen Zhang, Ru Kong, Susan Cheng| bioRxiv@ AbstractBrain age is a powerful marker of general brain health. Furthermore, brain age models are trained on large datasets, thus giving them a potential advantage in predicting specific outcomes - much like the success of finetuning large language models for specific applications. However, it is also well-accepted in machine learning that models trained to directly predict specific outcomes (i.e., direct models) often perform better than those trained on surrogate outcomes.

    By Kim-Ngan H. Nguyen, Chen Zhang, Ru Kong, Susan Cheng · bioRxiv

    Nov. 19, 2024

  • Intensive therapy may blunt higher CVD risk for younger women with hypertension, diabetes

    By Michael Monostra Verified, Richard Smith, Susan Cheng| Endocrine Today Verified You've successfully added Diabetes in Endocrinology to your alerts. You will receive an email when new content is published. Click Here to Manage Email Alerts We were unable to process your request. Please try again later. If you continue to have this issue please contact customerservice@slackinc.com. Key takeaways: Women with type 2 diabetes have a higher risk for CVD events if they are diagnosed with hypertension before age 50 years.

    By Michael Monostra Verified, Richard Smith, Susan Cheng · Endocrine Today

    Jul. 03, 2024

  • Evaluation of Brain Age as a Specific Marker of Brain Health

    By Kim-Ngan H. Nguyen, Chen Zhang, Ru Kong, Susan Cheng| bioRxiv@ AbstractBrain age is a powerful marker of general brain health. Furthermore, brain age models are trained on large datasets, thus giving them a potential advantage in predicting specific outcomes - much like the success of finetuning large language models for specific applications. However, it is also well-accepted in machine learning that models trained to directly predict specific outcomes (i.e., direct models) often perform better than those trained on surrogate outcomes.

    By Kim-Ngan H. Nguyen, Chen Zhang, Ru Kong, Susan Cheng · bioRxiv

    Nov. 19, 2024

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