Siemens Healthineers may someday grow to be bigger than its parent company following the anticipated spin-off of the health division next year, according to Siemens CEO Joe Kaeser.
In an interview with the German publication Manager Magazin, Kaeser speculated on the future of Siemens after the health unit is spun off in an initial public offering (IPO), which is expected to occur in the first half of 2018.
Kaeser specifically addressed concerns that the IPO amounted to breaking up Siemens, stating that "we are not breaking anything up, we are creating new companies," according to Reuters coverage of the story.
The Siemens Healthineers IPO is considered to be the most radical restructuring move that Kaeser has taken since assuming control of Siemens in 2013, Reuters noted. Kaeser has divested a number of the conglomerate's other businesses, but in the case of Siemens Healthineers the parent company will retain a majority stake after the IPO -- at least in the near term.
The health division is the most profitable of Siemens' various operations, and spinning off the unit could unlock potential that couldn't be achieved if it remained part of the parent organization, according to the article.
"Perhaps one day Siemens industry won't control Healthineers but it will be the other way around," Kaeser is quoted as saying in the Manager Magazin interview.
![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)
