Artificial Intelligence | News | Insights | AiThority
[bsfp-cryptocurrency style=”widget-18″ align=”marquee” columns=”6″ coins=”selected” coins-count=”6″ coins-selected=”BTC,ETH,XRP,LTC,EOS,ADA,XLM,NEO,LTC,EOS,XEM,DASH,USDT,BNB,QTUM,XVG,ONT,ZEC,STEEM” currency=”USD” title=”Cryptocurrency Widget” show_title=”0″ icon=”” scheme=”light” bs-show-desktop=”1″ bs-show-tablet=”1″ bs-show-phone=”1″ custom-css-class=”” custom-id=”” css=”.vc_custom_1523079266073{margin-bottom: 0px !important;padding-top: 0px !important;padding-bottom: 0px !important;}”]

AI in Medical Imaging Diagnostics: IDTechEx Benchmarks 60+ Companies

IDTechEx Research predicts that the market for image recognition AI in medical diagnostics will exceed $3 billion by 2030. This article considers the competitive landscape by disease area, company readiness levels by application, and the trends in focus areas.

Companies sit at different stages of readiness. Although multiple firms are already selling, this alone does not guarantee success. Companies are trying one or multiple of the following approaches to succeed:

Recommended AI News: Siduri Winery Serves Up Holographic Augmented Reality Experie

Related Posts
1 of 33,466
  • Towards wider applicability: Showing that the AI is applicable to a wide population set is increasingly critical. This improves outcomes and widens market applicability, but is difficult to implement. One needs to place a robust data acquisition and learning loop via partnerships and customer relationships at the heart of the product development. When successful, this will serve to erect moats around the business, acting as a large barrier to entry for newcomers.
  • Evolving beyond simple abnormality identification towards super-human insights: Whilst there is a spread in what different algorithms are offering, most are positioned as decision support tools. As a minimum, they need to detect (recognize + localize) the anomaly of interest. The evolution is to provide explanations alongside the object detection. Some are even aiming to suggest treatment options. In short, the goal is to raise the AI complexity beyond object detection.
  • Scale: Large scale means more access to data, which translates into an ever-widening performance gap against competitors in terms of algorithm accuracy, versatility, and applicability. Interestingly, the big software firms (Google and Microsoft) have a big program on these topics but are yet to take the plunge into this competitive landscape.
  • Aggressive pricing: The pricing model right now is based on either a tiered subscription model or a pay per use. However, the amortized development costs and the installation fees resemble more like a fixed cost, whilst the supplier’s computing costs vary with the scanning volume so some type of per-use model will prevail. In general, the trend will be towards ever more competitive pricing. This is likely to be leveraged as a tool by well-funded organizations to force out smaller poorly capitalized competitors.

Recommended AI News: Flexential Empowers Floyd Medical Center’s COVID Relief Initiative

IDTechEx’s report provides a detailed analysis of over 50 and examines the company landscape from both a commercial and technical standpoint. In-depth insights into current and upcoming technologies as well as detailed market analysis are also provided.

Recommended AI News: Tickeron Gives Penny Stock Trading New Life With AI-Powered Trading Features

Comments are closed, but trackbacks and pingbacks are open.