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Artificial Intelligence

This column keeps returning to the healthcare industry because it is so much more complex and varied than so many others. Artificial intelligence (AI) coverage has focused on radiology, has moved to the operating theater, and has been discussed in the back office. Insurance and pharma fraud are arenas where AI risk analysis is useful. Now, along comes another area that is amenable to AI solutions. Its something many people think of as secondary, but is really a critical part of healthcare: physical therapy.

As someone who, many years ago, had an intriguing car crash, and who, not as many years ago, also proved he wasnt as young as he thought he was, by blowing out a knee, Im someone who is very aware of the need for physical therapy (PT). The basics of PT seem very simple: design therapies that cause repeated motions of damaged body parts, analyze that motion, then provide feedback to the patient and the medical community in order to help both improve. Its the capture and analysis of impact (yes, pun intended) of that motion which can prove complex.

Human physical therapists can see a lot of movement, but its impossible for them to capture all the necessary information. SWORD Health is a company focused on this unique healthcare segment. As they are a young company, they are focusing on a few key therapy areas. The hip, knee, lower back, shoulder, wrist and neck comprise more than 90 percent of all musculoskeletal issues in the U.S., said Virgilio Bento, CEO, SWORD Health. Rehabilitating them remotely requires a technology that can learn and expand.

One intriguing area that supports a separate call out section is the oft problematic issue of bias in testing. We know that visual neural networks have had problems identifying women of color. We know that, outside of AI, many drug trials dont include children, pregnant women, and other demographics who will need those drugs. Physical therapy is a healthcare sector that can avoid those problems.

There is already a body of PT information on the wide variety of demographics who receive PT. The ability to track far more information and to analyze it with demographic information (even anonymized for privacy), means that treatments can start with far more segmentation based on available information and then been quickly tuned on an individual basis based on direct, specific results. Starting with patterns based on more detailed segmentation and then transforming treatment on a case-by-case basis removes the bias issues that may be inherent in other areas of medicine or even in the minds of some medical personnel.

As has been regularly mentioned, AI is a tool, not a solution. The company isnt only working with machine learning. They make sensors to capture the information, with the kinematics being sent to the system via wireless communications. Then multiple techniques can be used to address the data. A mixture of deep learning and statistical linear regression is used to understand the progress of the therapies. Changing the therapy can then also be semi-automated, with the system suggesting changes. That doesnt need deep learning, as choosing the therapies is a rules based process.

As with all areas of healthcare dealing with patients, in the United State the FDA requires clearance of both new and updated appliances. The difference between hardware and AI is readily apparent with how each part is handled on change. When a hardware component is changed, detailed specifications can be sent to the FDA for fairly quick analysis and approval. The regulatory agency is still early in its analysis on how to manage AI, especially neural networks, so the process can be slower than with hardware.

AI is still a grey area, primarily through the fault of AI companies. While they like to talk about the black box that is a neural network, for instance, they know their layers, they know the nodes, the code and the weightings. While some of the inference is still not easily explicable, there is far more companies could provide to regulatory agencies if it were mandated.

In the lack of such transparency, expect for at least near-term job security for humans. They must remain in the loop, both as oversight for the AI and as a legal cover to say the AI is not making a prognosis but is providing the humans with options.

Deep learning and other machine learning techniques have an important place in healthcare, but it must be incorporated into the full patient treatment process, along with other technology. Unlike a deep learning system cranking along on its own in a research facility, investigating potential new drugs, AI must play well with other technology and processes the closer to patients it resides. Physical therapy is an excellent aspect of the needed growth, as it is a regular and visible part of patient treatment that includes humans, hardware and software interacting within a regulatory framework to improve patient outcomes.

See the article here:
The Breadth Of Healthcare Applications Of Artificial Intelligence Even Includes Physical Therapy - Forbes

It has been affirmed that the asymptomatic people infected with Covid-19 do not exhibit the diseases visible physical symptoms. Thus they are less likely to get examined for the virus and unknowingly spread the infection to others around.

Recently researchers at MIT have discovered that asymptomatic people differ from healthy people in the way they cough. Although the differences are not decipherable to the human ear, it is stated that artificial intelligence can be employed to discover them. Takeda Pharmaceutical Company Limited supported the research.

Several healthy individuals have voluntarily submitted forced-cough recordings. The researchers at MIT have trained the model on a large number of such samples of coughs and oral words. The AI model distinguishes asymptomatic people from healthy individuals when a new cough sample is fed. The team is now incorporating the model into a user-friendly app that will be a free, easy, and non-invasive pre-screening tool to identify people expected to be asymptomatic for Covid-19. It will be adopted on a large scale if FDA-approved. A user can then login to the app daily, cough into their phone, and immediately get information if they are infected.

Vocal sentiments

Before the pandemics onset, research groups had already been training algorithms on cell phone recordings of coughs to accurately diagnose conditions such as pneumonia and asthma. Similarly, the MIT team was working on developing AI models that analyze forced-cough recordings to detect signs of Alzheimers disease, which is associated with neuromuscular degradation, such as weakened vocal cords along with memory decline.

Firstly, a neural network known as ResNet50 was trained to discriminate sounds associated with different vocal cord strength degrees. The research showed that the quality of the sound mmmm could indicate how weak or strong a persons vocal cords are. The researchers then developed a sentiment speech classifier model trained on a large dataset of actors intonating emotional states, such as neutral, calm, sad, and happy. A third neural network was trained on a cough database to discern changes in lung and respiratory performance. Lastly, all three models were combined, overlaying an algorithm to detect muscular degradation.

A remarkable relationship

The team found growing evidence that patients infected with coronavirus experienced similar neurological symptoms as Alzheimer patients, such as temporary neuromuscular impairment. So they questioned if their AI framework for Alzheimers would work for diagnosing Covid-19 as well.

The sounds of talking and coughing are affected by the vocal cords and organs surrounding them. When an individual talks, a part of their talking is like coughing, and vice versa. AI can pick up things from the cough that we derive from a speech like a persons gender, mother tongue, age, or even emotional well-being. The team says that there is sentiment embedded in how an individual coughs. Seeing the similarity between the two, they verified and confirmed the Alzheimers biomarkers for Covid.

The team discovered that the AI framework originally meant for Alzheimers discovered patterns in the four biomarkers of vocal cord strength, lung and respiratory performance, sentiment, and muscular degradation are specific to Covid-19. The team stated that the model accurately detected 98.5 percent coughs from people confirmed with Covid-19 and asymptomatic coughs.

Asymptomatic symptoms

The AI model is not intended to diagnose symptomatic people regarding whether their symptoms are due to Covid-19 or any other infirmities like flu or asthma. The models potency rests in its ability to recognize asymptomatic coughs from healthy coughs.

The team is now working with a company to develop a free pre-screening app based on their AI model. They are also partnering with several hospitals worldwide to collect a more extensive and diverse cough recording set, improving training and strengthening the models accuracy.

The team says that the pandemic could become a thing of the past if pre-screening tools are used, imposing a constant check. They also state that these AI models would be incorporated into smart speakers and other listening devices so that people can quickly get an initial assessment of their disease risk.

Paper: https://ieeexplore.ieee.org/document/9208795

Source: https://news.mit.edu/2020/covid-19-cough-cellphone-detection-1029

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MIT Researchers Explore New Advancements In Asymptomatic COVID-19 Detection Using Artificial Intelligence Through Cough Recordings - MarkTechPost

International Business Machines Corp. IBM, -0.60% and Advanced Micro Devices Inc. AMD, +4.21% announced Wednesday morning that they have entered a multi-year agreement focused on enhancing their security and artificial-intelligence offerings. "The joint development agreement will expand this vision by building upon open-source software, open standards, and open system architectures to drive Confidential Computing in hybrid cloud environments and support a broad range of accelerators across high-performance computing (HPC), and enterprise critical capabilities such as virtualization and encryption," the companies said in a release. Confidential Computing is a technology that allows for the encryption of data used to run virtual machines and it helps protect sensitive information. "Confidential Computing for hybrid cloud unlocks new potential for enterprise adoption of hybrid cloud computing, especially in regulated industries such as finance, healthcare and insurance," the companies said in their release. IBM shares are up 0.3% in premarket trading Wednesday, while AMD shares are up 1.4%. IBM shares have lost 12% so far this year as AMD's have risen 70%. The S&P 500 SPX, +0.76% is up 10% in that span, and the Dow Jones Industrial Average DJIA, -0.07%, of which IBM is a component, is up 3%.

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IBM and AMD will work together on security, artificial intelligence - MarketWatch

Two Google employees in a recent Harvard Business Review (HBR) article have emphasised the importance a collaborative approach to AI development; AI developers and data scientists should partner with the communities, stakeholders and experts who understand how those AI systems will interact with in practice.

As the authors note, "AI has the power to amplify unfair biases, making innate biases exponentially more harmful." There is a particular risk that data scientists and developers make "causation mistakes" where a correlation is wrongly thought to signal a cause and effect. "This lack of understanding can lead to designs based on oversimplified, incorrect causal assumptions that exclude critical societal factors and can lead to unintended and harmful outcomes."

To address this risk, the authors suggest that the societal context needs to be factored into the AI system - the "community-based system dynamics". However, no individual person or algorithm can see the society's complexity in its entirety or fully understand it. "So, to account for these inevitable blindspots and innovate responsibly, technologists must collaborate with stakeholders representatives from sociology, behavioral science, and the humanities, as well as from vulnerable communities to form a shared hypothesis of how they work."

The article is of particular interest because there are calls for an Accountability for Algorithms Act in the UK which include "a right for workers to be involved to a reasonable level in the development and application of systems". Such a right is motivated by the need to ensure transparency. But the HBR article shows that such stakeholder involvement can improve an AI system's performance also.

There have been many calls for AI to be developed "ethically" (see the EU's proposals for an ethical framework here); perhaps such calls will carry greater weight if the ethical principles can be shown to simultaneously improve technical performance also. As the authors say, AI engineers need to think beyond engineering.

AI system developers who usually do not have social science backgrounds typically do not understand the underlying societal systems and structures that generate the problems their systems are intended to solve. This lack of understanding can lead to designs based on oversimplified, incorrect causal assumptions that exclude critical societal factors and can lead to unintended and harmful outcomes.

https://hbr.org/2020/10/ai-engineers-need-to-think-beyond-engineering

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Artificial Intelligence: engaging communities and stakeholders in the AI's development improves ethics and performance - Lexology

A clear majority of Germans (60 percent) would like to see AI used more in industry, in sectors such as automaking or aircraft-building. In addition, more than two-thirds of Germans would welcome the use of AI to diagnose machine faults and in high-tech areas such as space exploration.

These are some of the findings of the Bosch AI Future Compass, a survey that polled 1,000 Germans aged 18 and over about their attitude to artificial intelligence.

Germany and Europe have what it takes to be world leaders in industrial AI, said Dr. Michael Bolle, board of management member and Bosch CDO/CTO, at todays digital presentation of the Bosch AI Future Compass. More specifically, he added, they have unique specialist and domain knowledge that allows them to use AI in areas such as quality control, energy efficiency, and improving manufacturing efficiency. In this respect, the relatively high level of acceptance for industrial AI revealed in the survey is encouraging: For the future of Germany and Europe as an industrial location, it is enormously important to have the backing of the general public and of key institutions.

The acceptance of AI use in other areas of application, such as nursing or investment advice, is significantly lower, at 40 percent and 31 percent respectively. And when it comes to making legal decisions or shortlisting candidates for vacancies, Germans are far more willing to trust a human being than a machine. Across all areas, 53 percent of Germans view the use of AI positively, while 36 percent are more negative.

AI applications will only win the day if customers and users trust them.

Dr. Michael Bolle, board of management member and Bosch CDO/CTO

This calls for clear, ethically sound guidelines not only in Germany, but also at the European level. He added that Bosch already set itself a clear ethical framework at the beginning of this year, when it introduced a code of ethics for AI: We have made it absolutely clear that AI must serve people, not the other way around. AI must always be kept under human control.

For two-thirds of the survey participants, it is essential that artificial intelligence be used only in the service of the common good. Similarly, around two-thirds would like to see decisions on legal and ethical standards for the use of AI made multilaterally (38 percent see the need for global action, 27 percent for European action), while only 35 percent advocate a national strategy. Fully 85 percent of the respondents are adamant that people must have the final say wherever artificial intelligence is used.

According to the Bosch AI Future Compass, a majority of Germans (53 percent) think that artificial intelligence is vital for remaining competitive internationally. And 42 percent of those surveyed believe that artificial intelligence offers a better way of solving major problems such as disease or climate change.

Irrespective of their fundamental attitude toward AI, respondents largely agree on the opportunities and risks. The benefits most frequently mentioned include efficiency, progress, and better (work) results, while terms such as surveillance, lack of compassion, and lack of data privacy top the list of negatives.

The Bosch AI Future Compass shows that we need to talk even more about artificial intelligence, Bolle said, adding: Customers and users must be able to understand the basis on which an AI makes certain decisions. This is a discussion that needs to be conducted throughout society, he said, not just in business circles.

The Bosch AI Future Compass shows that more knowledge about AI leads to more willingness to accept it. Accordingly, those respondents who consider themselves tech-savvy and feel they have a sound knowledge of the field rate artificial intelligence as fundamentally positive in 81 percent of cases. But among those who consider themselves less technologically minded and state that they know little about AI, the acceptance rate is only 27 percent.

Any debate about the opportunities and risks of AI, in whatever form, has to be open and objective, Bolle said. To make this debate constructive and unprejudiced, people have to be given a better idea of how artificial intelligence works. AI must be included in the school curriculum, he said, at least as a voluntary additional subject.

Bosch is also taking the initiative: over the next two years, the company will make 20,000 associates ready for AI. By 2025, moreover, the aim is for all Bosch products to either contain AI or have been developed or manufactured with it. This is not about using AI for its own sake, but instead about further increasing the quality and benefits of our solutions for customers and users, Bolle said.

The Bosch AI Future Compass was prepared by the market researchers Gesellschaft fr Innovative Marktforschung mbH (GIM).

SOURCE: Bosch

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Bosch AI Future Compass: 60 percent of Germans would welcome greater use of artificial intelligence in industrial settings - Automotive World