The television medical drama "House" was a big hit during the 2000s, and not just because of the trademark sarcastic wit that the curmudgeonly lead character, played by Hugh Laurie, wielded with such wicked deftness. Another key part of the show's appeal was watching the brilliant Dr. House and his nearly-as-talented team of diagnosticians work together as a sort of hive mind to investigate perplexing medical mysteries. They pieced together bits of information and debated their significance, until finally arriving at a solution and devising some ingenious treatment to save the patient.

That all made for fascinating drama. Wouldn't it be great, though, if your doctor could consult a diagnostician who was even more brilliant, knowledgeable and resourceful than Dr. House (and a lot less prickly)? And what if any physician could seek that assistance from the computer on his or her desk, with just a few keystrokes?

The good news is that doctors now can tap into that sort of expert help, thanks to a new generation of medical software programs that use artificial intelligence (AI) -- that is, the capability of computers to emulate and improve upon human thinking. AI systems have the potential to revolutionize medicine. While a human physician -- especially a tired one at the end of a long shift -- might overlook or misinterpret the subtle symptoms of a rare disease that he or she hasn't encountered since medical school, computers don't need coffee and sleep and they don't forget information. Better yet, an AI system also may be able to track the latest medical research and even tap continuously into the observations and experiences of other doctors, and then crunch all that data to come up with statistically-validated treatment options [source: de la Torre].

AI researchers have been looking at ways to utilize such software in medicine for several decades [source: Patel, etal]. But the recent development of the artificial neural network, or ANN -- a program that utilizes the combined knowledge of its network connections and then learns from the data, in the fashion of a biological brain -- has really opened the door. In 2009, Mayo Clinic researchers reported that they had put data on 189 cardiac patients with implanted medical devices into such a system and that the software had screened them for potentially fatal heart infections with better than 99 percent accuracy. Not only did the software spot 72 of 73 implant-related infections, but it accomplished that without having to insert an endoscope down their throats to look around -- a potentially risky invasive procedure [source: Mayo Clinic].

While no one wants computers to replace human doctors, AI systems can help make them more effective in treating patients. Just how do these systems show promise for the medical field?