FDA


FDA-approved robot assistant gives surgeons force feedback

Engadget

Surgeons are trained to accurately operate on you when you need it, but robotic assistants could help them get to hard-to-reach areas and boost their accuracy even more. Senhance, the robotic surgical assistant that has just earned the FDA's approval, was designed to accomplish both of those. According to TransEnterix, the company that developed the machine, it's the first surgical assistant for the abdominal area to get the FDA's approval since 2000. As you can see above, surgeons sit behind a console with a 3D view of the site of operation to control three surgical arms.


Autonomous Robots Coming To U.S. Hospitals

#artificialintelligence

The FDA approved the country's first human-interacting autonomous robot for hospitals on Thursday. The RP-VITA, made by iRobot (best known to consumers as the makers of the Roomba) and InTouch Health, is a human-sized telepresence robot which allows doctors to remotely interact with hospital patients. The robot can navigate hospital corridors autonomously, while medical professionals talk and interact with patients through a special iPad app. The Food and Drug Administration has given the RP-VITA full 510(k) clearance for hospital use.


Healthcare Industry Will Stagnate Without AI – Know Why! - HIE Answers

#artificialintelligence

In healthcare, the opportunity for AI is not just limited to making doctors and medical providers more competent in their work; in fact, it's about saving lives and making the lives of the patients better. It enhances the digital healthcare experiences of patients by offering them conversational and personalized engagement. Moreover, doctor's efforts will be greatly supported, especially when conducting differential diagnosis and evidence-based treatment and precision medicine practice using artificial intelligence with IBM's Watson. Whether it is a voice-based medical intelligence system for remotely monitoring a patient, or diagnosing disease symptoms, or sending alerts for medical appointments and medications and more.


AI diagnostics are coming

#artificialintelligence

Earlier this year, artificial intelligence scientist Sebastian Thrun and colleagues at Stanford University demonstrated that a "deep learning" algorithm was capable of diagnosing potentially cancerous skin lesions as accurately as a board-certified dermatologist. Unlike more-traditional vision software, where a programmer defines rules--for example, a stop sign has eight sides--in deep learning the algorithm finds the rules itself, but often without leaving an audit trail to explain its decisions. The FDA required Arterys to do extensive testing to make sure the results from its algorithm were on par with those generated by physicians. These covered 2,032 different diseases and included 1,942 images of confirmed skin cancers.


First FDA Approval For Clinical Cloud-Based Deep Learning In Healthcare

#artificialintelligence

The first FDA approval for a machine learning application to be used in a clinical setting is a big step forward for AI and machine learning in healthcare and industry as a whole. Arterys's medical imaging platform has been approved to be put into use to help doctors diagnose heart problems. It uses a self-teaching artificial neural network which has learned from 1,000 cases so far, and will continue to improve its knowledge and understanding of how the heart works with each new case it examines. In order to be approved by the US Food and Drug Administration (FDA), it had to pass tests to show it can produce results at least as accurately as humans are currently able to. The key difference though is that Arterys takes an average of 15 seconds to produce a result for one case, which a professional human analyst would expect to spend between 30 minutes to an hour working on.


Flipboard on Flipboard

#artificialintelligence

The first FDA approval for a machine learning application to be used in a clinical setting is a big step forward for AI and machine learning in healthcare and industry as a whole. Arterys's medical imaging platform has been approved to be put into use to help doctors diagnose heart problems. It uses a self-teaching artificial neural network which has learned from 1,000 cases so far, and will continue to improve its knowledge and understanding of how the heart works with each new case it examines. In order to be approved by the US Food and Drug Administration (FDA), it had to pass tests to show it can produce results at least as accurately as humans are currently able to. The key difference though is that Arterys takes an average of 15 seconds to produce a result for one case, which a professional human analyst would expect to spend between 30 minutes to an hour working on.


First FDA Approval For Clinical Cloud-Based Deep Learning In Healthcare

Forbes

The first FDA approval for a machine learning application to be used in a clinical setting is a big step forward for AI and machine learning in healthcare and industry as a whole. Arterys's medical imaging platform has been approved to be put into use to help doctors diagnose heart problems. It uses a self-teaching artificial neural network which has learned from 1,000 cases so far, and will continue to improve its knowledge and understanding of how the heart works with each new case it examines. In order to be approved by the US Food and Drug Administration (FDA), it had to pass tests to show it can produce results at least as accurately as humans are currently able to. The key difference though is that Arterys takes an average of 15 seconds to produce a result for one case, which a professional human analyst would expect to spend between 30 minutes to an hour working on.


Riverain gets FDA approval of lung cancer detection software

AITopics Original Links

Riverain Technologies has received regulatory approval for the next-generation version of its imaging software that "suppresses" bones to help radiologists detect cancerous lung nodules. OnGuard 5.2, the latest version of the software, uses pattern recognition and machine learning technologies to essentially allow radiologists to see behind ribs and clavicles that often obscure lung abnormalities. OnGuard also circles areas that may be a lung tumor, according to the Dayton, Ohio-area company. The software's aim is to help clinicians reading chest X-rays get better views of pulmonary nodules -- spots on the lungs that can be a form of early stage cancer, but can also be benign. The new version of the software offers greater sensitivity, meaning it can better detect nodules, and better specificity, meaning it yields fewer false positives, said Steve Worrell, Riverain's chief technology officer.


Dean Kamen's "Luke Arm" Prosthesis Receives FDA Approval

AITopics Original Links

Its creators nicknamed it the "Luke Arm," after Luke Skywalker's ultra-advanced bionic limb. Now, after nearly eight years of development and testing, this robotic arm for amputees has been approved for commercialization by the U.S. Food and Drug Administration (FDA). The "Luke Arm," whose official name is DEKA Arm System, is one of the most advanced robotic prostheses ever built. According to the FDA, this is the first prosthetic arm approved by the agency that "translates signals from a person's muscles to perform complex tasks." The DEKA Arm was created by famed inventor Dean Kamen and his team at DEKA Research and Development Corp., in Manchester, N.H., as part of DARPA's Revolutionizing Prosthetics program.