AI News, Can Artificial Intelligence Live Up to the Hype?

Will Artificial Intelligence Replace Radiologists?

As computer performance on complex vision tasks approaches that of clinical experts, radiologists look over their shoulders.

The hype peaked in the year 2016: An oncologist and key architect of the Affordable Care Act predicted in the New England Journal of Medicine that “machine learning will displace much of the work of radiologists and anatomical pathologists” (4).

Two Oxford economists indicated in the Harvard Business Review that machines will replace doctors because “when professional work is broken down into component parts, many of the tasks involved turn out to be routine and process-based.

But the eager pronouncements initially gave pause to medical students considering their specialty choices and spurred many radiologists to check their retirement accounts.

The effect of computer vision on patient care is still mostly illusory, impeded by the scarcity of training data and the sluggish march to regulatory approval.

Concerns in the 1990s about the variable quality of mammography interpretation (10) led to two key steps forward: (a) the Breast Imaging Reporting and Data System (BI-RADS), arguably the most influential advance in the history of radiology communication (11), and (b) legislation to provide additional reimbursement for the use of AI to help radiologists detect breast cancer on mammograms.

Perhaps the incremental accuracy of these new AI methods will reduce false-positive findings and blunt the “cry wolf” effect, but the generalizability of these algorithms to the diversity of radiology practices remains an open question.

As early as 1896, William Morton, a neurologist who popularized the use of x-rays in the United States, partnered with Edwin Hammer, an engineer who had mastered the electrical generators needed to produce the current for x-rays (15).

A comprehensive catalog of radiology diagnoses lists nearly 20 000 terms for disorders and imaging observations and over 50 000 causal relations (20).

An AI algorithm that diagnoses common chest conditions at the level of a subspecialty thoracic radiologist is a major step forward, an incredible asset to underserved regions, and could serve as a valued assistant for a subspecialty radiologist.

But human radiologists are also trained to detect uncommon diseases in the long tail of the distribution, including rheumatoid arthritis, sickle cell disease, and posttransplantation lymphoproliferative disorder.

To illustrate the overreaction to technology’s role in job displacement, venture capitalist Mary Meeker lists New York Times cry-wolf headlines from the past century (22): “March of the Machine Makes Idle Hands” (February 26, 1928);

Although the danger of AI to radiologists is overblown, the new medical computer vision industry will profoundly change how radiologists practice, most likely in a direction that pleases radiologists.

Artificial Intelligence and Autism

Children born to ASD fathers have a higher chance of having the condition due to the inheritance of certain genetic mutations.

This economic cost is increasing every year as medical cost, education cost and loss of the economic productivity of the parents rises.

There’s a specific set of life skills that a person with ASD needs to learn in order to live more independently from his/her family.

This also means any tools and learning environments developed for a person with ASD must be flexible and tailored to that person’s individual needs.

Being able to learn life skills easily and efficiently, then being able to use these life skills to assimilate to the traditional workplace will allow for people with ASD to live better in society.

Their flagship product, Empower Me teaches social and cognitive skills to people with autism through emotional recognition.

When a child or an adult wears the glasses, it sees and hears special feedback geared toward the situation.

The digital coach helps the wearer to interpret facial expressions of emotions, when to look at people and gives feedback of wearer’s own state of stress or anxiety.

Therapists can easily program the robot for a special set of skills and instructions to tailor learning for the individual patient.

Cognoa’s precision health platform uses parent’s input of behavior information, combined with machine learning and predictive analytics to provide parents with diagnosis and care options.

This tool is empowering parents to face their children’s challenges head on rather than playing the waiting game.

In turn, it can change the outcomes of many children with ASD by getting them the critical help that they need earlier in their lives.

In a workplace of acceptance, people with ASD need to take frequent breaks to rest their mind and detox from overwhelming emotions.

With more people realizing the potential of this untapped work force, accommodations for people with ASD in the work place can potentially become the standard in the next 10 years.

AI in Software Testing

We’ve reached a tipping point that’s prompted CIOs to start actively exploring how AI can help them achieve their digital transformation goals.

While some are poised to deliver distinct business benefits in the clear and present future, others don’t seem ready to live up to the hype.

This site is designed to help you survey the landscape of AI software testing technologies and evaluate which ones can deliver the greatest value to your organization.

Using Artificial Intelligence for Evil | @CloudEXPO @CylanceInc | Cloud #CIO #AI #DataCenter #Security #ArtificialIntelligence | SYS-CON MEDIA

Using Artificial Intelligence for Evil Register for this session HereArtificial intelligence is positively affecting our world in previously unimaginable ways across many different industries.

The use of AI is particularly interesting in the cybersecurity industry because of its unique ability to scale and prevent previously unseen zero-day attacks and for automating complicated analysis and processes at machine speed.

But just in the way drug cartels built their own submarines and cellphone towers to evade law enforcement, so too will cyber-criminals build their own AI systems to carry out malicious attacks.AI is a force for good and has demonstrated great success thus far in security applications;

Malcolm Harkins, Chief Security and Trust Officer at Cylance, will cover the basics of AI technology, how AI is currently being used for evil and suggested ways to combat AI attacks.Through this session attendees will learn and understand: Speaker Bio: Malcolm Harkins is the Chief Security and Trust Officer at Cylance reporting to the CEO and is responsible for enabling business growth through trusted infrastructure, systems, and business processes.

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