Gearing up for its upcoming initial public offering (IPO), Siemens Healthineers has announced plans to cut annual costs by 240 million euros ($293.9 million U.S.).
In a January 16 event in London for analysts and investors, Siemens Healthineers management shared an update on the company and its road map -- called Strategy 2025 -- for generating growth and improving profitability. The planned structural cost savings are expected to have a full visible impact in 2020, and the firm said it expects to realize continuous productivity improvements going forward.
Siemens said that its focus on adjacent growth markets will serve as the basis for generating incremental growth and improve its market positions by 2025 and beyond. Artificial intelligence (AI) technology figures prominently in the company's Strategy 2025 plan, which focuses on five specific areas:
- Utilizing its position in the in vivo and in vitro markets to combine data and knowledge around precision medicine and make it relevant for clinical use
- Using data and AI to integrate existing and innovative technologies for therapy
- Coordinating and optimizing the patient journey through the healthcare continuum
- Developing a full range of technical, operational, and clinical service offerings that are more effective and more efficient by using technologies from Siemens Healthineers
- Continuing to develop and invest in capabilities in AI that support the above areas
Based on certain assumptions, Siemens said that it expects comparable revenue growth in 2018 to be between 3% and 4%, similar to the average growth rate of 3.8% over the past three years. The firm also hopes to achieve adjusted profit margins of 20% to 22% for its imaging and advanced therapies segments and 16% to 19% for its diagnostics segment.
Siemens plans to list Siemens Healthineers on the Frankfurt Stock Exchange's Regulated Market in the first half of the year.
![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)
