Providers of healthcare IT professional services in Europe earned $2.19 billion in revenue in 2008, and the market is expected to reach $3.64 billion in sales in 2015, according to a new report from market research firm Frost & Sullivan.
The demand for services for healthcare IT consulting, training, operations and maintenance, and technical customer services support are steadily increasing, with a compound annual growth rate of more than 7% projected by 2015. The support and maintenance services segment for healthcare IT is expected to account for more than 50% of the market.
Scarcity of professionals with expertise in both healthcare and IT sectors, and the high cost for these services, are currently constraining market growth, according to S. Priyan Viswanathan, senior research analyst at Frost & Sullivan's London office.
Early customized and adaptable training services with appreciable postsale support and maintenance services are expected to boost customer retention, system utilization, and overall growth of the market, Frost & Sullivan said.
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![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&fit=crop&h=112&q=70&w=112)





