Question

Subject: artificial intelligence.

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QUESTION:1   -- IROBOT: SMARTER HOME ROBOTS.

QUESTION:2 --- HOW TO USE AI TECHNOLOGY IN THE MEDICAL FIELD ? GIVE ANY ONE SIMPLE EXAMPLE.

Answer 1

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1.

The home robotics future many of us have imagined is here, although adoption into the technology has been limited to date. Pricing, availability, and consumer awareness are some of the factors involved, but another overlooked facet is the current disconnect between home robots and smart home technology. While robots in the home have always to some degree been a widely anticipated endeavor, smart home has emerged as a vital complement, and vendors are beginning to see increased value in supporting integration of their products into the smart home ecosystem. This is borne out in the projection of nearly 79 million homes worldwide that will feature a robot inside the home by 2024.

Home Care And Personal Robots

The market is comprised of two verticals: home care, which specializes in one particular function in or around the home (vacuum cleaner, lawnmower, pool cleaner); and personal robots, which are considered companion devices capable of responding to and interacting with the homeowner. Home care robots are the current pacesetters with regard to consumer adoption and smart home integration. A key reason is the gradual interweaving of smart home functionality and home care robots. For instance, wireless security cameras — a smart home device — are now being installed in robotic vacuum cleaners.

Blurring The Robotics And Smart Home Line

The main differentiator between smart home and robotics remains voice activation. Smart home products such as Google Home and the Echo line have sent adoption rates soaring past those of home robots, reinforcing the belief that a more unified integration can drive potential for increased consumption in both home care and personal robotics.

In addition to voice control, artificial intelligence is another smart home component considered integral to home robotics, particuarly on the personal/social side. Amazon and Google are believed to be strong frontrunners to lead the pack, due to AI and voice recognition being the center of their smart home assistant platforms. Echo and Google Home devices increasingly support screens and cameras alongside microphone arrays, providing the means to support facial recognition in line with voice activation — features that should become the basis for more personalized interactions between users and their devices. With both companies competing for a top spot in this market, it will be worth watching eventual consumer demand, as long as price points remain affordable.

Articulation and mobility will be key features that will accelerate the transition from smart speaker to a social robot that can move and converse with its user, providing two-way communication and even simulated facial expressions. While many consumers are not quite ready to live with a walking, talking robot, one obvious segment in which robotic capabilities have been useful is Ambient Assisted Living (AAL). Improving the user experience to integrate voice activation with home robots can drastically improve quality of life for the end-user. Start-ups such as Intuition Robotics and Blue Frog Robotics have already developed devices that are compatible with smart home services.

2.

When it comes to our health, especially in matters of life and death, the promise of artificial intelligence (AI) to improve outcomes is very intriguing. While there is still much to overcome to achieve AI-dependent health care, most notably data privacy concerns and fears of mismanaged care due to machine error and lack of human oversight, there is sufficient potential that governments, tech companies, and healthcare providers are willing to invest and test out AI-powered tools and solutions. Here are five of the AI advances in healthcare that appear to have the most potential.

Medical artificial intelligence (medical AI) mainly uses computer techniques to perform clinical diagnoses and suggest treatments. AI has the capability of detecting meaningful relationships in a dataset and has been widely
used in many clinical situations to diagnose, treat, and predict the results. In the research and studies of medical AI, we primarily focus on the viability and feasibility to in-corporate various computer AI techniques in medical in-formation modeling and clinical procedure deployments.

1. Deep Learning to Diagnose Diseases

One of the areas where AI in health care has shown the most promise is in diagnostics. Early diagnosis is one of the most important factors in the ultimate outcome of a patient’s care. AI deep-learning algorithms are being used to shave down the time it takes to diagnose serious illnesses. The way AI rapidly processes large amounts of information and arrives at likely causes for symptoms can drastically reduce the diagnosis-treatment-recovery cycle for many patients. The effects of this are already being felt in several areas.

2. Machine Learning and Radiology

A team of researchers at Osaka University has developed a deep-learning algorithm that can reliably diagnose many neurological diseases, including epilepsy. The program scans patients’ magnetoencephalography results, comparing their images with tens of thousands of other scans from healthy patients. It then identifies potential lesions and other abnormal regions in the brain. Since epilepsy often spreads across the brain, identifying abnormal scans as early as possible is crucial to improving patients’ treatment options and ultimate outcomes.

Reducing Operational Costs

The operational costs of running a health care organization can be staggering. This is as true for private practice providers as it is for sprawling HMOs with tens of thousands of employees. AI in health care is cutting those costs and letting providers at every level extend their budget further. This results in more resources for the practice, more time for the patient and significantly improved outcomes for many.

One example of how AI is improving health care delivery by cutting operating costs is in the field of joint replacement therapy. An intelligent program known as PeerWell helps patients prep for total joint replacement by guiding the course of pre-op physical therapy. As reported in Healthcare Finance, a study in the Annals of Translational Medicine reported that patients using the AI saw a reduction in surgery costs of $1,215.

Even better, the intelligent prep work the program recommended got so many patients into such good shape prior to their surgeries that the test group saw a reduction of 25% in the time patients spent in the hospital, 80% in the need for post-op home care and a staggering 91% in the number of patients discharged to nursing home care after their operations.

The providers saw similar reductions in operating costs because patients no longer required pre-op care from clinicians. This not only saves time for doctors and expense for patients and their insurers, it also dramatically reduces demand for post-op and rehab facilities, which frees up resources for the remaining patients and improves outcomes for nearly everyone.

Medical AI Technology

* PATHAI MORE ACCURATE CANCER DIAGNOSIS WITH AI

How it's using AI in healthcare: PathAI is developing machine learning technology to assist pathologists in making more accurate diagnoses. The company's current goals include reducing error in cancer diagnosis and developing methods for individualized medical treatment.

PathAI has worked with drug developers like Bristol-Myers Squibb and organizations like the Bill & Melinda Gates Foundation to expand its AI technology into other healthcare industries.

* BUOY HEALTH
AN INTELLIGENT SYMPTOM CHECKER

How it's using AI in healthcare: Buoy Health is an AI-based symptom and cure checker that uses algorithms to diagnose and treat illness. Here's how it works: a chatbot listens to a patient’s symptoms and health concerns, then guides that patient to the correct care based on its diagnosis.

Harvard Medical School is just one of the many hospitals and healthcare providers that uses Buoy’s AI to help diagnose and treat patients more quickly.