AI News, 31 Companies Making AI and Blockchain A Powerful Pair
Artificial intelligence in healthcare
Artificial intelligence (AI) in healthcare is the use of complex algorithms and software to estimate human cognition in the analysis of complicated medical data.
What distinguishes AI technology from traditional technologies in health care is the ability to gain information, process it and give a well-defined output to the end-user.
AI algorithms behave differently from humans in two ways: (1) algorithms are literal: if you set a goal, the algorithm can't adjust itself and only understand what is has been told explicitly, (2) and algorithms are black boxes;
AI programs have been developed and applied to practices such as diagnosis processes, treatment protocol development, drug development, personalized medicine, and patient monitoring and care.
Additionally, hospitals are looking to AI solutions to support operational initiatives that increase cost saving, improve patient satisfaction, and satisfy their staffing and workforce needs.
are developing predictive analytics solutions that help healthcare managers improve business operations through increasing utilization, decreasing patient boarding, reducing length of stay and optimizing staffing levels.
During this time, there was a recognition by researchers and developers that AI systems in healthcare must be designed to accommodate the absence of perfect data and build on the expertise of physicians.
An ability to interpret imaging results may aid clinicians in detecting a minute change in an image that a clinician might accidentally miss.
A study at Stanford created an algorithm that could detect pneumonia at that specific site, in those patients involved, with a better average F1 metric (a statistical metric based on accuracy and recall), than the radiologists involved in that trial.
The emergence of AI technology in radiology is perceived as a threat by some specialists, as the technology can achieve improvements in certain statistical metrics in isolated cases, as opposed to specialists.
Recent advances have suggested the use of AI to describe and evaluate the outcome of maxillo-facial surgery or the assessment of cleft patients therapy in regard to facial attractiveness or age appearance.
One study conducted by the Centerstone research insititute found that predictive modeling of EHR data has achieved 70–72% accuracy in predicting individualized treatment response at baseline.
The subsequent motive of large based health companies merging with other health companies, allow for greater health data accessibility.
A second project with the NHS involves analysis of medical images collected from NHS patients to develop computer vision algorithms to detect cancerous tissues.
Intel's venture capital arm Intel Capital recently invested in startup Lumiata which uses AI to identify at-risk patients and develop care options.
identRx is the first fully automated medication verification and dispensing device, using AI to identify and verify pill in real time, with an accuracy greater than 99%.
As an autonomous, AI-based system, IDx-DR is unique in that it makes an assessment without the need for a clinician to also interpret the image or results, making it usable by health care providers who may not normally be involved in eye care.
team associated with the University of Arizona and backed by BPU Holdings began collaborating on a practical tool to monitor anxiety and delirium in hospital patients, particularly those with Dementia.
The AI utilized in the new technology – Senior's Virtual Assistant – goes a step beyond and is programmed to simulate and understand human emotions (artificial emotional intelligence).
Doctors working on the project have suggested that in addition to judging emotional states, the application can be used to provide companionship to patients in the form of small talk, soothing music, and even lighting adjustments to control anxiety.
Overall, as Quan-Haase (2018) says, technology “extends to the accomplishment of societal goals, including higher levels of security, better means of communication over time and space, improved health care, and increased autonomy” (p. 43).
While research on the use of AI in healthcare aims to validate its efficacy in improving patient outcomes before its broader adoption, its use may nonetheless introduce several new types of risk to patients and healthcare providers, such as algorithmic bias, Do not resuscitate implications, and other machine morality issues.
As of November 2018, eight use cases are being benchmarked, including assessing breast cancer risk from histopathological imagery, guiding anti-venom selection from snake images, and diagnosing skin lesions.
SINGAPORE, 1st July, 2019 (WAM) -- Dubai Chamber of Commerce and Industry, DCCI, has signed a Memorandum of Understanding, MoU, with the International Chamber of Commerce, ICC, and Perlin, making it the first chamber of commerce in the world to offer innovative blockchain solutions.
What are the pros and cons of AI?
Artificial intelligence (AI) may seem like a concept from the far future, or something straight out of Hollywood, but in reality, it's a phenomenon that's already impacting our daily lives.
There are standout names like Watson and AlphaGo, systems which have already proven they can roundly beat even the most accomplished human competitors, with a poker-playing AI being the most recent example, beating five professional players at once.
While this is one of the more visible ways AI influences our world, both it and its allied discipline machine learning are used in other areas, such as mining data and helping businesses, NGOs, governments and others make informed decisions on everything from strategy to product development.
AI is set to dominate the business, consumer and public sector landscape over the next few years with technologists predicting that soon we will be surrounded by IoT devices capable of performing mundane tasks and speeding up complex ones.
Online grocer Ocado uses automated machines in its warehouse, controlling thousands of robots, communicating with them 10 times a second to coordinate the movement of hundreds of thousands of crates.
Job losses This is arguably the number one downside to AI consistently highlighted as a doom and gloom scenario were workers are laid off, unable to outperform machines.
In what seems like the scary nightmares of a dystopian future, IBM's Watson has been using AI and Watson Analytics to decide if employees are worthy of a pay rise, a bonus or a promotion by looking at the experience and past projects of employees to judge the qualities and skills that individuals might have to serve the company in the future.
For example, Microsoft's ill-fated chatbot, Tay Tweets, had to be taken down after only 16 hours after it started to tweet racist and inflammatory content – ideas it repeated from other Twitter users.
- On Monday, December 9, 2019
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