3D printing in healthcare

7

October

2022

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Nowadays, customization and personalization are becoming more standard practices in many areas, whether it is in retail or in technology. A technology that enables this in many different facets is 3D printing. 3D printing is an upcoming technology that can be used for multiple purposes. Currently, for businesses, it is enabling them to easily create prototypes of their final product. This is called “rapid prototyping” (Hoffman, 2020). The 3D printer allows them to quickly adjust the product and implement potential changes.

In several industries such as healthcare, art and automotive industry 3D printing can be used and an increasing number of ways of applying this technique are found. Especially in healthcare 3D printing can have multiple benefits such as customisation and personalisation, increased cost efficiency, enhanced productivity and democratization and collaboration. For surgeries that involve implants or prosthetics, 3D printing will allow for easier customisation as the prototype can be made at a higher speed and adjustments that are needed can be implemented faster, which thus makes the customisation easier. Also, the speed at which these customised parts are made is much higher compared to the current traditional methods. As these surgeries and therefore the customised parts are relatively low volume, the cost of 3D printing is minimal (Ventola, 2014).  

As mentioned above one current use is the personalisation of implants and prosthetics. There are several more and potentially more complicated applications in the healthcare industry. One application of 3D printing is the bio-printing of tissues and organs. Tissue or organ failure is currently treated by organ transplants, but there is a chronic shortage of human organs. Even if a transplant has taken place, it is still unsure how the body reacts to this new organ and if it will not be rejected. Bio-printing with cells from the patient’s body could eliminate this risk of rejection.

In conclusion, bio-printing is a promising technology that could increase the speed of customisation in healthcare as well as a potential solution to the organ shortage.

Bibliography

Hoffman, T. (2020, July 1). 3D Printing: What You Need to Know. Retrieved from pcmag.com: https://www.pcmag.com/news/3d-printing-what-you-need-to-know#:~:text=Designers%20use%203D%20printers%20to,and%20novelty%20items%2C%20and%20toys

Ventola, C. L. (2014). Medical Applications for 3D Printing: Current and Projected Uses. P&T, 704-711.

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Proteus: the end of the smart pill? 

4

October

2022

5/5 (1)

Andy Thompson, CEO of Proteus Digital Health, came up with an idea that brings AI and the healthcare together. He invented the world’s first pill with microchip that tracks your health. The tiny microchip has to be taken together with the medicine and is able to gather data about the effectivity and safety of the related medicine. The microchip is coupled to a smart system where the consumer can see their personal data and get reminders when to take the drug. The sensors in the microchip detect effects of the medicine as high adherence or negative side-effects. As a consequence, a huge amount of costs and even deaths can be reduced. The World Health Organization (WHO) estimated that in developed countries, 50% of patients that are chronically ill experiences non-adherence of medicines. For instance, in the US this amount is approximated around 25%-50% and causes around 125.000 deaths annually.

Moreover, healthcare providers that have permission to gain insight into the data, can work with more efficacy. The doctors are better able to prescribe treatments and prevent unnecessary bad health outcomes. As depicted in the picture below, the microchip is inserted into a capsule of the drug and will eventually transfer the data to a wearable sensor patch (Kleinsmith, 2022).

This innovation seemed very promising at first. However, Proteus filed for bankruptcy one year after its invention. The CEO remains positive and is convinced that its product will flourish in the future (Kleinsmith, 2022). My thoughts on this are also positive and it makes me think why it did not become popular as it can improve the health industry to a great extent.
So, I am curious, have you ever heard of this and what are your thoughts of it?
Sources

Kleinsmith, N. a. P. S., 2022. Proteus Digital Health: Healthcare for Everyone, Everywhere, Rotterdam: s.n.

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AI4Covid: Effective AI covid-tests using only cough sounds

3

October

2022

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In the fight against the coronavirus, early and accurate diagnosis is vital. To this day most common tests still rely on antibodies, therefore results are often only conclusive after several days and not reliable enough.

Researchers in the field of automated cough classification have been working on another strategy: They adapted a supervised machine-learning algorithm that detects slight differences in coughs and can diagnose or rule out respiratory infections accordingly. 

This tool is supposed to automatically identify cough sounds and define them pursuant to certain parameters. AI makes it possible to compare patterns with other coughs and diagnose instantaneously. Cough sounds are especially informative because the sounds correlate with tissue structure in the respiratory organs, in addition to providing insight to the behavior of surrounding organs and structures.

The most challenging aspect of the studies is to find the most significant features, on which grounds to train the machine-learning system. The Massachusetts Institute of Technology has based their program on the four attributes: Muscular degradation, vocal cord strength, sentiment as well as respiratory and lung performance (Saplakoglu, 2020). For their program thousands of volunteers uploaded forced coughs and filled out information on their health status, symptoms and covid infection. While a large group of cases were then used to train the machine-learning system, another was used to function as a test group. Although results were very encouraging, transferring this success out of the laboratory provided a challenge, since cough sound not only vary on respiratory function, but many other parameters, such as mother-tongue and gender. Therefore investigation continued and showed that time-frequency representation of a cough successfully aided in achieving higher quality results. So far the best model is Random Forest with an accuracy of 90% (Tena, Clarià and Solsona, 2022).

These cough related covid tests have the potential to contain the pandemic in a more efficient way, as they would – if installed as an app on phones – not need high cost data evaluation in labs and would therefore be more easily accessible and affordable. Also AI can spot covid infections sooner than rapid covid tests can and would therefore be a strong advantage to the prevention of high spreading.

References

Saplakoglu, Y. (2020). Newsela [online] newsela.com. Available at: https://newsela.com/read/ai-detect-covid19-cough/id/2001015957/%C2%A0/https://newsela.com/read/ai-detect-covid19-cough/id/2001015957/%C2%A0/ [Accessed 2 Oct. 2022].
Tena, A., Clarià, F. and Solsona, F. (2022). Automated detection of COVID-19 cough. Biomedical Signal Processing and Control, [online] 71, p.103175. doi:10.1016/j.bspc.2021.103175. Available at: https://www.sciencedirect.com/science/article/pii/S1746809421007722  [Accessed 1 Oct. 2022].
Detecting COVID-19 through cough sounds. (n.d.). www.nature.com. [online] Available at: https://www.nature.com/articles/d42473-022-00294-9 [Accessed 2 Oct. 2022].

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Horse Racing: Reduction of Death Cases using Modern Technology

30

September

2022

5/5 (2)

Although for years Horse Racing has been popular for its thrill and the opportunity to place bets, it has been increasingly targeted with criticism by the public for its numerous fatal injuries – not only concerning horses, but also jockeys. In order to cast off this unfavorable reputation, the British Horse Racing Authority (BHA) has established means to reduce mid race injuries, such as obligatory pre-race examinations. 

With the general amelioration of medical technology, those health check-ups strongly increased in significance. Especially the refinement of the MRI has fostered an early detection of illnesses or injuries, like small ruptures of muscle tissue or tendons. Over the last five years, this is estimated to have averted about 30% of fatal equine injuries (EBR, 2022). 

Next to MRIs, ultrasound and thermal imaging cameras that are used to monitor a horse’s temperature post race, other technologies have been developed specifically for this sport. 

The University of Bath has designed an equine fitness tracker referred to as EquiVi (the Guardian, 2019). This device includes three sensors, which are placed on the horse’s body during practice or a race. The sensors are able to continuously measure important vital signs, such as blood pressure, temperature and respiratory rate, and transfer this data simultaneously via a wireless connection to a digital device. This enables coaches, owners and veterinarians to track the horse’s welfare during extreme physical exertion and adapt its training and racing schedule accordingly. In addition, the relation of the visible performance and cardiovascular activity can be examined, which is again very conclusive about the horse’s true level of fitness. Lead researcher Dr. Ben Metcalfe stresses the benefits of such an non-intrusive monitoring device as the horse is not exposed to any damaging influences (www.bath.ac.uk, 2019).

The risk reduction for fatal equine injuries automatically minimises health threats for the jockey. Still, accidents can and do occur, which led the BHA to ask the University of Bath for another research project. Through remodeling countless falls of jockeys accessible in the digital race archive, they are working to better understand and treat common injuries such as concussions and injuries involving the spinal cord. 

These different approaches to not only prevent mid-race injuries, but also maximise a positive treatment outcome, are only possible through the newest technological innovations. Therefore nowadays, modern technology even contributes to the safety and with it the continued existence of one of the oldest and most traditional sports.

References:
the Guardian. (2019). Equine fitness trackers could save lives of racehorses. [online] Available at: https://www.theguardian.com/sport/2019/mar/30/racehorses-to-be-fitted-with-life-savingfitness-sensors [Accessed 29 Sep. 2022].
Incze, G. (2022). How Horse Racing Has Embraced Technological Innovations. [online] European Gaming Industry News. Available at: https://europeangaming.eu/portal/latest-news/2022/03/02/110251/how-horse-racing-has-embraced-technological-innovations/ [Accessed 29 Sep. 2022].
EBR, E. (2022). How Technology Has Changed Horse Racing. [online] The European Business Review. Available at: https://www.europeanbusinessreview.com/how-technology-has-changed-horse-racing/ [Accessed 29 Sep. 2022].
www.bath.ac.uk. (2019). Boost to horse welfare and performance thanks to new monitoring device. [online] Available at: https://www.bath.ac.uk/announcements/boost-to-horse-welfare-and-performance-thanks-to-new-monitoring-device/ [Accessed 29 Sep. 2022].

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Google’s DeepMind facing data privacy lawsuit

5

October

2021

4/5 (1)

From data to app to lawsuit

2015: Alphabet Inc.’s British artificial intelligence subsidiary DeepMind obtains private health records of 1.6 million patients from the Royal Free London NHS Foundation Trust. 

This data was to be used to develop the ‘Streams’ app which aims to alert, detect, and diagnose kidney injuries. The app was being developed for use by doctors to detect acute kidney injury. This app was already being used by the Royal free with great praise.

From DeepMinds point of view, they are making use of valuable data in order to progress healthcare and save lives. From Royal Free’s point of view, they are enabling this by sharing this data and then using the app created by this to treat patients. However, for some citizens, this seems like a breach of data privacy.

The British law firm Mishcon de Reya has filed a class-action lawsuit against DeepMind to represent Andrew Prismall and the other 1.6 million patients whose data was shared. 

Who is at fault?

Something I find quite interesting about this case is that DeepMind is accused of being at fault rather than the Royal Free, who shared the data in the first place. Although the Streams app was developed by DeepMind, the app was a collaboration between DeepMind and Royal Free and could not have succeeded without both of their inputs.

I believe that both players are to blame in this situation and that DeepMind can not be put at fault alone. Who do you believe is at fault in this situation?

How can we prevent this in the future?

For such situations, a healthcare system with strong regulations regarding data privacy, and healthcare providers who abide by such regulations, would largely diminish the threat of major tech firms such as Alphabet. However, too many regulations can inhibit innovation in some situations. Finding a balance between innovation and safety is a challenge that many industries and regulators struggle with worldwide.

I believe that it is no easy task to find such a balance. There is a growing number of factors influencing a push for both regulation and free innovation as digital information becomes one of the most important assets for innovative development. Experts on data privacy and innovation must come together to form regulations that can foster safe innovation.

What do you think should be done to foster safe innovation in the information era?

References:

https://www.bbc.com/news/technology-40483202

https://www.bbc.com/news/technology-58761324

https://www.cnbc.com/2021/10/01/google-deepmind-face-lawsuit-over-data-deal-with-britains-nhs.html

https://deepmind.com/

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Big Tech in Healthcare

16

September

2021

5/5 (1)

Hightech giants – such as Google, Amazon and Apple – are on the fast line when it comes to incorporating healthcare into their business. The past months have shown how seriously the big technology companies are already involved in the healthcare market. It becomes clear that from telemedicine to health trackers, to clinical studies, a whole range of market trends are addressed. Each player pursues its own strategy, which is based on its own digital, tech or platform competence: 

Apple continues to strengthen its leading position in the wearables market and adds an ever-increasing number of features every few months. The focus is always on gathering and evaluating user health data. Apple and its devices (iPhone, Apple Watch, etc.) are already deeply embedded in customers’ daily lives, which should not be overlooked. Apple makes use of this proximity to bring clinical research to its consumers’ wrists. According to the latest news, Apple even plans the move to blood-pressure measures and a wrist thermometer in the Apple Watch to help with fertility planning. Furthermore, Apple users will soon be able to share personal health data (e.g. vital, movement and sleep data) with others via the app, e.g. their relatives, their fitness trainer and ideally with the doctor. Consequently, Apple continues its journey into the “closed” ecosystem where Apple users and devices are connected with one another efficiently and in a value-oriented manner. 

With its fundamental skill of data analysis, Google, as the most important point of contact for patients, is continuously developing new services and therefore data sources. With the acquisition of Fitbit in 2019, Google likewise joined the wearables industry. Along with the pharmaceutical company Boehringer Ingelheim, Google works on discovering new application possibilities of super-fast quantum computers for drug development. Furthermore, Google’s Health App incorporated a new function for assessing skin, hair, and nail issues. A sophisticated system analyzes three photos taken by the camera. Several questions are then added to the analysis. Consequently, a list of probable explanations for the symptom is generated. As Google has the most data power they apply this information to create customer-centric goods, which is critical to their success. The software is not intended to replace medical advice from a dermatologist, but it is apparent that it should and will move in this direction.

Amazon is expanding its range of medical services with Alexa, in addition to expanding the variety of its “Amazon Care” health platform and its presence in the online pharmacy market by adding prescription drugs to its “Amazon Pharmacy” range. Furthermore, Amazon dares to step into the highly competitive wearables market with its “halo” bracelet. What makes “halo” so intriguing is that, in addition to tracking vital health parameters like activity level, heart rate, and sleep, it can also analyze the mood/emotional condition of its carrier based on the tone of his or her voice. This sets them apart from the competition and provides Amazon with highly sensitive data which gives them an even more detailed understanding of their customers. For Amazon, the focus is always on the proximity to customers and their needs, or the customer experience.

However, all this hype of the big tech companies in healthcare can only succeed in the long term if patients and healthcare professionals also accept and incorporate their initiatives. Currently, corporations such as Apple are actively pursuing participation from both health researchers and hospitals. A prevalent fear of healthcare professionals is that patients may utilize new technology to self-diagnose, and medical devices would induce worrying results without having an expert opinion. However, if this is actually the case still must be proven. For now, doctors should focus on integrating rather than disregarding new technologies and be more receptive to new innovations brought to the table by both big tech and various entrepreneurs.

References:

https://www.mobihealthnews.com/news/apple-reportedly-looking-expand-smartwatch-health-features-blood-pressure-and-fertility

https://www.apple.com/de/newsroom/2021/06/apple-advances-personal-health-by-introducing-secure-sharing-and-new-insights/

https://www.businessinsider.com/2-14-2021-big-tech-in-healthcare-report?international=true&r=US&IR=T

https://www.theverge.com/2021/5/18/22440754/google-health-ai-skin-condition-model-dermatology

https://healthcaresuccess.com/blog/tag/big-tech-in-healthcare

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AI in Healthcare: “The AI will see you now”

13

September

2021

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In recent years, AI has been integrated in various disciplines with great success (i.e., Supply chain, Recruitment and Video Game Industry). However, one discipline remains heavily apprehensive of AI, and this is the healthcare industry. According to Challen et al (2019), AI and machine learning bots in other industries are able to identify errors and quickly correct themselves before any harm is done. Unfortunately, this is not transferable to the healthcare industry as when it comes to the patient’s health, there is literally no room for trial and error.

Despite the apprehensiveness of the healthcare sector, the use of AI is slowly adopted and can be seen providing simple aid that otherwise requires an additional personnel. Creating chatbots for mental health assistance, monitoring patients’ health and predicting cardiac arrest and/or seizures are some ways AI supports physicians in less high-risk tasks. With the developing technologies in the field of AI, AIs are also able to diagnose patients based on electronic health records, patient history, and pathology images (analysis of blood, urine and tissue samples).

The adoption of AI is slowly progressing due to its ability to alleviate physician burnout, a genuine concern in the field of healthcare. Physician Weekly (2018) states that at least 42% of practitioners experience burnout due to lack of support/personnel, short patient visits, complicated patients and overwhelming workload. Consequently, this affects their performance in providing quality patient care as well as the patient’s safety. Hence, what if the next step for AI in healthcare is to aid physicians with walk-in patients diagnosis and treatment? 

A study by Longoni, Bonezzi & Morewedge (2019) has deduced that despite AI predictive analysis can identify potential ailments faster than human doctors as well as having a higher accuracy rate, patients are reluctant and derive negative utility towards an automated healthcare provider. The argument for these findings are linked to Uniqueness Neglect, a concern that AI are unable to account for each patient’s unique circumstances which makes them hesitant to trust an AI diagnosis. An AI may be able to predict accurately what treatment a patient needs, however, a human practitioner may be able to weigh the pros and cons more specifically, also taking into account the well-being of the patient. 

From a technological point of view, the adoption of AI in the healthcare industry may alleviate physician burnout, aid in less risky decisions such as analytics and image processing, as well as maximizing physician efficiency. However, when it comes to treatment, AI does not have the ability to take over the role of human physicians…… yet.


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Quality Data is Quality Care

8

October

2020

No ratings yet. Big Data has changed the way we manage and analyse data in any industry. The healthcare industry is a promising area where data analytics can be applied as it not only reduces costs, it can prevent diseases, predict epidemic outbreaks and improve overall life quality. The future of healthcare will therefore be driven by data analytics and digital transformation. In this blog post I will address why big data in healthcare is important and in what ways it can be applied.

Big data refers to vast quantities of information created by the digitization of everything that gets analysed by specific technologies. Data collection is critical in the healthcare industry. Doctors need to understand as much as possible about patients, as early as possible. Treating diseases at early stages is simpler and less expensive (Lebied, 2018). For years, health data collection has been very costly and time consuming. With today’s innovative technologies, it becomes easier to collect data and translate it to useful insights for better care. This not only reduces costs; it also makes a patient’s health situation more predictable (Lebied, 2018). This in turn enables insurance companies to tailor their packages based on this information.

Healthcare analytics can provide support in asking critical questions such as ‘What is the probability that this patient will recover within 6 months?’ or ‘How likely is this patient to suffer from complications if we perform this surgery’? Driven by the rise of Internet of Things (IoT) and Artificial Intelligence (AI) such as machine learning and robotics, we now have algorithms that can help us answer these questions (Philips, 2020). According to a 2019 survey, 60% of health executives recognize the benefits of healthcare analytics, and 42% of them have seen improved patient satisfaction (Kent, 2019). Below we see how healthcare organizations are using predictive analytics (Dé, 2019).

BlogpostIS

So in what ways do healthcare organizations apply analytics? Here are 3 examples of innovative technologies driven by healthcare analytics.

  1. Electronic Health Records (EHRs)

An EHR is a digital record of a patient’s demographics, medical history, allergies and more. These records are shared via secured systems and are available for providers from the public and private sector (Lebied, 2018). Leading healthcare organizations have integrated next generation analytics platforms into their EHR, such as algorithms and machine learning. This enables predictive, analytics- powered patient risk assessment. EHR can, for example, generate warnings and reminders when a patient should get a new test or when a patient is not following prescriptions.

  1. Precision Medicine

Precision Medicine (PM) is the most common application of machine learning in healthcare. It predicts what treatment protocols are likely to succeed on a patient, based on various attributes and the treatment context (Davenport & Kalakota, 2019). PM requires a training dataset for which the outcome variable is known, which is called supervised learning. Philips, the global leader in healthcare, for example applies PM to the field of oncology. PM will enable treatments to be tailored to genetic changes in each individual’s cancer (Philips, 2020). Cancer patients currently may receive a combination of treatments, while with PM, information about genetics can help doctors decide which treatment is best for each individual patient (Davenport & Kalakota, 2019).

  1. Real-Time Alerting

The traditional way of analysing medical data is facilitated through software that is only used in hospitals (Lebied, 2018). However, as in-house treatments are expensive, doctors want patients to stay away from hospitals as much as possible. To track patient data anytime and anywhere, real-time alerting is applied to wearables. These wearables collect the patient’s data continuously and send this data to the cloud (Knapp, 2018). An example is a blood pressure tracker, which alarms doctors when a patient’s blood pressure is too low or too high, so that appropriate action can be taken. This not only reduces in-house treatment costs; it also makes sure doctors can treat a patient as early as possible. What is more, it allows health executives to access the cloud with collected data to compare data in socioeconomic context and translate the data to useful insights (Lebied, 2018).

Evidently, the opportunities arising from healthcare analytics are very promising. Yet, as predictive analytics can be, their impact eventually depends on their knowledgeable use by health executives. The development of applications empowered by data analytics relies on the expert input. Another important note is that the issue of data privacy arises from the data driven nature of healthcare analytics. What will happen when data is shared seamlessly between different stakeholders? Should patients have control over what data is shared and with whom? The debate of how data can be shared without breaching patients’ trust is still ongoing.

 

References

Davenport, T., & Kalakota, R. (2019). The potential for artificial intelligence in healthcare. Future healthcare journal, 6(2), 94–98. https://doi.org/10.7861/futurehosp.6-2-94.

Dé, A., (2019). Why Healthcare Analytics Will Deliver More Results In 2019. [online] Biplatform.nl. Available at: <https://biplatform.nl/1826849/why-healthcare-analytics-will-deliver-more-results-in.html> [Accessed 7 October 2020].

Kent, J., (2019). 60% Of Healthcare Execs Say They Use Predictive Analytics. [online] HealthITAnalytics. Available at: <https://healthitanalytics.com/news/60-of-healthcare-execs-say-they-use-predictive-analytics> [Accessed 5 October 2020].

Knapp, J., (2018). Real-Time Healthcare Analytics: Monitor, Predict, Nudge, Act | Vocera. [online] Vocera.com. Available at: <https://www.vocera.com/blog/real-time-healthcare-analytics-monitor-predict-nudge-act> [Accessed 7 October 2020].

Lebied, M., (2018). 12 Examples Of Big Data In Healthcare That Can Save People. [online] BI Blog | Data Visualization & Analytics Blog | Available at: <https://www.datapine.com/blog/big-data-examples-in-healthcare/> [Accessed 5 October 2020].

Philips. (2020). Predictive Analytics In Healthcare: Three Real-World Examples. [online] Available at: <https://www.philips.com/a-w/about/news/archive/features/20200604-predictive-analytics-in-healthcare-three-real-world-examples.html> [Accessed 6 October 2020].

 

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BIM, Meet Gertrude!

6

October

2020

Gertrude enjoying a well deserved drink during her performance. 

In August 2020, famous tech entrepreneur Elon Musk revealed his latest technological project: a pig called Gertrude. On first sight, Gertrude looks like an ordinary Pig. She seems healthy, curious, and eager to taste some delicious snacks. When looking at her, it is hard to imagine how she managed to get one of the world’s most radical and well known tech entrepreneurs so excited. Gertrude just seems normal.

This is exactly the point!

ElonMuskGotcha

Elon Musk “Gotcha”

Gertrude is no ordinary pig. She has been surgically implanted with a brain-monitoring chip, Link V0.9, created by one of Elon Musk’s latest start-ups named Neuralink.

Neuralink was founded in 2016, by Elon Musk and several neuroscientists. The short term goal of the company is to create devices to treat serious brain diseases and overcome damaged nervous systems. Our brain is made up of 86 billion neurons: nerve cells which send and receive information through electrical signals. According to Neuralink, your brain is like electric wiring. Rather than having neurons send electrical signals, these signals could be send and received by a wireless Neuralink chip.

To simplify: Link is a Fitbit in your skull with tiny wires

The presentation in August was intended to display that the current version of the Link chip works and has no visible side-effects for its user. The user, in this case Gertrude, behaves and acts like she would without it. The chip is designed to be planted directly into the brain by a surgical robot. Getting a Link would be a same day surgery which could take less than an hour. This creates opportunities for Neuralink to go to the next stage: the first human implantation. Elon Musk expressed that the company is preparing for this step, which will take place after further safety testing and receiving the required approvals.

The long term goal of the Neuralink is even more ambitious: human enhancement through merging the human brain with AI. The system could help people store memories, or download their mind into robotic bodies. An almost science-fictional idea, fuelled by Elon Musk’s fear of Artificial Intelligence (AI). Already in 2014, Musk called AI “the biggest existential threat to humanity”. He fears, that with the current development rate, AI will soon reach the singularity: the point where AI has reached intelligence levels substantially greater than that of the human brain and technological growth has become uncontrollable and irreversible, causing unforeseeable effects to human civilization. Hollywood has given us examples of this with The Matrix and Terminator. With the strategy of “if you cannot beat them, join them”, Elon Musk sees the innovation done by Neuralink as an answer to this (hypothetical) catastrophical point in time. By allowing human brains to merge with AI, Elon Musk wants to vastly increase the capabilities of humankind and prevent human extinction.

Singularity
Man versus Machine

So, will we all soon have Link like chips in our brains while we await the AI-apocalypse?

Probably not. Currently, the Link V0.9 only covers data collected from a small number of neurons in a coin size part of the cortex. With regards to Gertrude, Neuralink’s pig whom we met earlier in this article, this means being able to wirelessly monitor her brain activity in a part of the brain linked to the nerves in her snout. When Gertrude’s snout is touched, the Neuralink system can registers the neural spikes produced by the neurons firing electronical signals. However, in contrast: major human functions typically involve millions of neurons from different parts of the brain. To make the device capable of helping patients with brain diseases or damaged nervous system, it will need to become capable of collecting larger quantities of data from multiple different areas in the brain.

On top of that, brain research has not yet achieved a complete understanding of the human brain. There are many functions and connections that are not yet understood. It appears that the ambitions of both Elon Musk and Neuralink are ahead of current scientific understanding.

So, what next?

Neuralink has received a Breakthrough Device Designation from the US Food and Drug Administration (FDA), the organisation that regulates the quality of medical products. This means Neuralink has the opportunity to interact with FDA’s experts during the premarket development phase and opens the opportunity towards human testing. The first clinical trials will be done on a small group of patients with severe spinal cord injuries, to see if they can regain motor functions through thoughts alone. For now a medical goal with potentially life changing outcomes, while we wait for science to catch up with Elon Musk’s ambitions.

 Neuralink-Logo

Thank you for reading. Did this article spark your interest?
For more information, I recommend you to check out Neuralink’s website https://neuralink.com/

Curious how Gertrude is doing?
Neuralink often posts updates on their Instagram page https://www.instagram.com/neura.link/?hl=en

Want to read more BIM-articles like this?
Check out relating articles created by other BIM-students in 2020:

Sources used for this article:

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Diagnosis: Cyberattack – A New Threat for Healthcare

2

October

2020

5/5 (1) Cybercrime and healthcare… One might think what a weird combination – right? However, I have to disappoint you. It is a cruel reality.

But let’s start at the beginning… the enabler: It is, what a ’surprise’, the increasing use of technology in the healthcare industry. But using technology does not only imply risks. We all know how beneficial technology in healthcare is. No matter which technology, it (most of the time…) all comes down to an increase in efficiency and effectiveness (AIMS Education 2019). Furthermore, those improvements aim to increase our quality of life while, hopefully, reduce its costs (AIMS Education 2019).

One of the easiest and best examples of technological adoption in healthcare is the digitalization of health records (Online Health Informatics 2020). Do you remember one of your doctors using a paper record? No? Me neither. This example might sound too simple to be true. However, digital healthcare records had a positive impact on not only the quality of public healthcare but also its costs. Those records can be communicated through the Internet of Things (IoT) within hospitals and stored in, e.g., clouds (Jayaraman et al. 2019).

The consequences are tremendous: Due to the sensitivity of medical data, its value is constantly increasing, making it a vulnerable target for cybercrime (Jayaraman et al. 2019). To get a glimpse of how valuable healthcare records are; it is up to 20x higher when compared to credit card details…

Cybercrime – two real-world examples and its dramatic consequence(s): The most recent (known) happened this Monday (28/09/20). The American hospital chain ‘Universal Health Services’ with its over 250 hospitals experienced an IT outage due to a cyberattack – causing no access to medical records and everything connected to WiFi (including the devices that monitored critical care patients) (CBS News 2020). Luckily, this cyber attack had no fatalities. The latter, however, happened two weeks earlier to a hospital in Düsseldorf, Germany. There, a cyberattack caused the death of a critical patient (The Guardian 2020)…

Even though it is highly unethical to put monetary gains over human life; I do personally think that this trend will continue. The increasing use of interconnected devices in healthcare will create even more sensitive data which will make it an even more attractive target to hackers…

What do you think? Will this trend will continue, or are technological enhancements, such as blockchain, chances to put an end to it? Let me know in the comments!

 

References:

AIMS Education. (2019). The Impact Of Technology In Healthcare. [online] Available at: <https://aimseducation.edu/blog/the-impact-of-technology-on-healthcare> [Accessed 1 October 2020].

CBS News. (2020). Cyberattack Hobbles Hospital Chain Universal Health Services. [online] Available at: <https://www.cbsnews.com/news/cyberattack-universal-health-services-hospital-chain-united-states/> [Accessed 1 October 2020].

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