E-mail Tips
5 Tips for Building Your eBroadcast
Five tips for you make the most the most of your eBroadcast to ensure the best deliverability, open rates and consistent user experience across all readers.
Telling a better story
Some quick ideas and starting points for how best to make your eBroadcast stand out to readers and identify with them.
Subject lines the forgotten element
In this video we cover why subject lines are so important and why it's worth the time and effort to create a good one.
Improving click-through rates
Got an important message but having not seeing the click through rates you want? Here are some ideas for improving that percentage.
Improving Lead Collection
Everybody wants to collect lead information for sales but it's easier said than done. In this video we discuss some key ideas about bartering with readers for their information and then we cover some key points for creating a successful landing page.
![Overview of the study design. (A) The fully automated deep learning framework was developed to estimate body composition (BC) (defined as subcutaneous adipose tissue [SAT] in liters; visceral adipose tissue [VAT] in liters; skeletal muscle [SM] in liters; SM fat fraction [SMFF] as a percentage; and intramuscular adipose tissue [IMAT] in deciliters) from MRI. The fully automated framework comprised one model (model 1) to quantify different BC measures (SAT, VAT, SM, SMFF, and IMAT) as three-dimensional (3D) measures from whole-body MRI scans. The second model (model 2) was trained to identify standardized anatomic landmarks along the craniocaudal body axis (z coordinate field), which allowed for subdividing the whole-body measures into different subregions typically examined on clinical routine MRI scans (chest, abdomen, and pelvis). (B) BC was quantified from whole-body MRI in over 66,000 individuals from two large population-based cohort studies, the UK Biobank (UKB) (36,317 individuals) and the German National Cohort (NAKO) (30,291 individuals). Bar graphs show age distribution by sex and cohort. BMI = body mass index. (C) After the performance assessment of the fully automated framework, the change in BC measures, distributions, and profiles across age decades were investigated. Age-, sex-, and height-adjusted body composition reference curves were calculated and made publicly available in a web-based z-score calculator (https://circ-ml.github.io).](https://img.auntminnieeurope.com/mindful/smg/workspaces/default/uploads/2026/05/body-comp.XgAjTfPj1W.jpg?auto=format%2Ccompress&dpr=2&fit=crop&h=167&q=70&w=250)
