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Artificial intelligence is on the rise — and carving out a place for itself in healthcare technology stacks. As noted by research firm PWC, "the potential for both AI and robotics in healthcare is vast," especially as these tools take on more traditionally human tasks at a lower cost. According to Forbes, AI is the "next big thing" thanks to advancements in computing architecture, access to historical datasets and advancements in deep neural networks — and this couldn't come at a better time. Becker's Hospital Review notes that 65 percent of physicians are overworked and 58 percent said that their time with patients has decreased.

However, there's plenty of room for AI in healthcare, but which capabilities offer the best return on investment? Here's a look at the top three opportunities for AI in healthcare technology.

1. Surgical Assistance

As noted by Venture Beat, robot-assisted surgery tops the list of potential AI-healthcare crossovers with a potential market value of more than $40 billion. Beyond dollar signs, however, there's sensible data to back up this idea. Preoperative medical data is combined with real-time surgical metrics to help reduce complications, while surgical robots are able to make smaller and more precise incisions under a surgeon's guidance. Another benefit includes potential reduction of post-op recovery times by up to 21 percent. By offloading some surgery tasks to AI-enhanced devices while keeping the surgery as a whole under expert physician control, it's not hard to see the through-line — reduced surgery times and complications mean lower costs for hospitals even as patient satisfaction increases.

The caveat is that effective implementation requires a slow ramp-up to ensure patients are comfortable with the use of AI-powered tools.

2. Personalized Care

Physicians already have trouble finding more face-to-face time with patients, and many physicians report that technology advancements such as text messaging and video calls don't offer substantive assistance. Meanwhile, AI has big potential here — using big data sets, it's possible for machines to create new diagnostic tools which could help identify early markers of disease onset and empower physicians to develop patient-specific treatment plans that are more proactive. Ideally, this provides better cross-patient care, especially across disparate social and economic groups which are susceptible to different risk factors.

But given the under-representation of some populations and the over-representation of others based on health provider location and prevailing socioeconomic conditions, this evolving healthcare technology must include deep research to help eliminate potential bias.

3. Improved Medical Decisions

According to Managed Healthcare Executive, AI in healthcare could also help make better medical decisions. New tools are already able to predict the course of patient diseases and potential mortality with 95 percent accuracy — creating a clear path from current use to more advanced medical decision-making as AI tools handle more data and more quickly discover patterns. For physicians, use of decision-making AI could act as a solid second opinion: Is there agreement on diagnosis? Treatment plan? Progression? While doctors would still have the last word, artificially intelligent assistance could help develop more comprehensive treatment plans or help physicians think outside of the box.

Data is critical but it isn't enough in isolation — AI must be able to situate that data in the context of patient lives and experiences. For example, AI might recommend a course of treatment that's outside of a patient's budget or simply not feasible under current living conditions. Context allows healthcare technology to create custom-built responses which take into account not only the patient but the person.

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