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Technology
AI technology AI-Healthcare system Medical Data Patient Data Technology

Future Health: AI's Impact on Personalised Care in 2024

 



As we dive into the era of incorporating Artificial Intelligence (AI) into healthcare, the medical sector is poised for a profound transformation. AI holds immense potential in healthcare, offering groundbreaking advancements in diagnostics, personalised treatment approaches, and streamlined administrative processes. Casting our gaze forward to 2024, the influence of AI on patient care is increasingly palpable, with the seamless fusion of technology and healthcare charting a collaborative course toward a future marked by synergy. 

AI's influence is particularly notable in diagnostics, where healthcare professionals leverage its ability to interpret intricate health data. Unlike traditional methods, AI systems analyse diverse datasets, providing a more comprehensive understanding of a patient's health. Recent regulatory recommendations from the World Health Organization (WHO) highlight the global recognition of AI's significance in healthcare, emphasising effective integration, patient safety, and data privacy. 

The concept of personalised medicine, tailoring treatments to individual patients, is evolving with AI playing a crucial role. AI's ability to process and analyse diverse patient data, including genetic details and lifestyle factors, is propelling the development of highly individualised treatment plans. This shift marks a pivotal moment in healthcare, promising a future where care is not only more precise but also tailored to the nuanced needs of individuals. 

In the next three years, trends in AI healthcare use cases are expected to shape the industry. Natural Language Processing (NLP) and Conversational AI will aid in symptom checking and triage, while virtual assistants guide patients and improve automated scheduling. Integrating omics data with Electronic Health Records (EHRs) and wearable device data will enhance patient phenotyping. Stringent regulations on AI, particularly in medical devices, are anticipated in the U.S. and Europe. The evolving role of AI in targeted diagnostics and personalised care simplifies data structuring, empowering healthcare professionals to focus on quality care. 

However, the widespread adoption of AI in daily clinical practice poses a critical challenge. The true potential of AI in healthcare can only be realised when medical professionals collaborate with these technologies, leveraging unique human skills and cognitive function. Those embracing this partnership are poised to harness AI's full potential, offering a glimpse into a future defined by advancements and redefined patient care standards. 

As AI reshapes the industry, ethical considerations take centre stage, especially regarding patient data privacy and the potential for algorithmic bias. The World Health Organization's recommendations reinforce the necessity for robust regulatory frameworks to ensure responsible AI use in healthcare. 

While AI brings significant benefits, the crucial role of human oversight cannot be overstated. AI serves as a valuable tool to assist healthcare professionals rather than replace them, with human judgement remaining essential in interpreting AI-generated data and making final treatment decisions. 

The year 2024 signifies a pivotal moment for AI in healthcare, showcasing its evolution from a conceptual idea to a practical tool enhancing patient care. This journey underscores the relentless pursuit of innovation in the medical field. As AI continues to progress, it holds the potential to unlock new dimensions in personalised patient care, making healthcare more efficient, precise, and tailored to individual needs. Challenges accompany this transformative journey, and the healthcare community must navigate them with a steadfast commitment to ethical practices, ensuring that AI integration enhances rather than compromises patient well-being.


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Privacy
AI-Healthcare system Artificial Intelligence Cyberattacks CyberCrime Cybersecurity Digital healthcare system Health Threat Medical Emergency Privacy

Hacked Health: Unmasking the Reasons Behind the Targeting of Medical Facilities

 


There is no more important way to handle sensitive data in the healthcare field than to take care of the patient's own health, which is why taking care of sensitive data is just as important. Especially now that healthcare is under attack on a global scale, it is extremely important to keep it in mind. A growing number of industries and sectors are implementing technology in their operational processes over the past few years. 

There has been a graceful embrace of this technological advancement by the healthcare sector. It is the objective of adopting advanced technology, including AI, to make sure patients receive the best possible diagnosis and treatment by making use of advanced technologies. 

As healthcare leaders prepare for increased spending on cybersecurity, they are ready to invest. Despite this, with new threats being discovered every day, it can be a bit difficult to decide where an organization should invest its budget to protect against them. 

A more interconnected environment is one of the main reasons for the hospital to be vulnerable, as it comes with technology being tied together. In a way, this gives MSPs and IT professionals the unique opportunity to provide healthcare organizations with support in modernizing their backup systems and security systems. 

To protect sensitive patient information from threat actors looking for an easy target, these teams must collaborate closely with healthcare IT teams to create a comprehensive security strategy. As digital transformation is sweeping across a wide range of industries, hospitals have been slowly digitizing their processes and patient care over the past few decades.

Hospitals are becoming an increasingly attractive target due to more patient data in the system. With the growing number of asynchronous working patterns, the need for patient data to be easily accessible and shareable has also increased. 

Due to the increased amount of data, there is also an increased opportunity for hackers to hack into the system and exploit its vulnerabilities. Many hospitals have become dependent on their digital networks, and they would rather pay a ransom to restore their operations than lose that functionality. This leaves them vulnerable to attacks on their digital networks.

It is common for hackers to target healthcare as a lucrative prey. When hackers compromise patient data or hospital systems, they know that they could demand a high ransom. The ransom will likely be paid by healthcare organizations—and fast—since compromised data and systems can potentially lead to the death of patients in a hospital environment. The fact is that hospitals, of course, rely on constant and immediate access to patient data to deliver care, which may result in people becoming ill and dying. 

It may seem naive to think that there are many reasons why healthcare is a potential target for cyberattacks. However, there may be a variety of reasons why healthcare organizations are more attractive targets for cyberattacks. Patients or providers of healthcare organizations need to be aware of why cyberattacks are so common. 

Hackers Can Profit Greatly From Private Patient Information 


The information contained in health records and other patient-related documents is vital to the operation of healthcare facilities. But, the same cannot be said for some of the best hackers who are looking to make a fortune. Since hospitals are often faced with life-or-death stakes when it comes to this sensitive data, many opt for paying ransoms to protect their valuable data on the black market.  

Cyberattacks Often Overwhelm Healthcare Staff 


Staff must understand that medical devices may interface with other systems and that these interconnected systems and devices create additional risks that they need to be aware of to identify them correctly. A complete understanding of cyberattacks requires adding additional layers of context to training so that cybersecurity across all departments becomes part of the organization's cybersecurity defence program. 

Attackers Can Gain Access to Connected Devices 


As part of routine medical care, medical devices, such as X-ray machines, insulin pumps, and implantable defibrillators, can now be accessed via a network and serve as an important part of the care process. There is no doubt that these devices may not have been the intended targets of hackers for network access, but, because they are typically not well protected, they could be used as an entry point to launch attacks on servers or other networked assets that contain critical (and financially rewarding) information, even though they are not intended targets of their attackers. 

Risks for Small Healthcare Organizations 


As big healthcare systems suffer from cyberattacks as well as small ones, the reasons for that are different for larger and smaller healthcare systems. In many cases, the reason for a cyberattack on a large system is due to its large amount of data, and that’s why hackers target big healthcare systems.

To ensure the security of their patient data, healthcare organizations must be aware of the latest online threats that can threaten them. The right solution is crucial to the success of any organization and an owner must invest their budget and time in it. If an organization owner wants to ensure their staff is protected rather than struggling to protect all of their devices, it is important to consider how their staff works and keep up with new threats as they emerge. 

There has been an increase in the number of breaches and ransomware attacks in the healthcare sector in the past few years, which can be attributed to the fact that the industry has become a profitable target for threat actors in recent years. The key here is to band together with security professionals and managed service providers to mitigate these threat actors and their attack methods. This is a prime opportunity. 

Providing healthcare providers with an understanding of the most effective and most commonly used attack styles, as well as training their employees and patients, will give them a much better chance of reducing their risk of being exploited through phishing emails and multi-factor authentication (MFA) attacks to provide support to themselves and their stakeholders.
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Wireless
AI-Healthcare system ANC Cyberattacks CyberCrime Cybersecurity Earbuds Google Fit Technology Wireless

Wearable Tech Evolution: Google Integrates Heart Rate Monitoring into ANC Earbuds

 


It has been made clear by Google that they have made rapid progress in developing technology that will allow users to make a significant upgrade to their existing true wireless earbuds. Wireless earbuds might be able to integrate heart rate monitoring with just a software update, so there will be no additional hardware requirements when upgrading to wireless earbuds. Since they are going to use a similar method as noise cancellation to work, the earbuds, earphones or headphones in question must have active noise cancellation. 

The wrist-worn devices that can provide reliable heart rate data are available from almost every major manufacturer. A companion application such as Google Fit crunches the data over time for you to be able to see patterns and irregularities in your health that may indicate something serious is wrong. 

Even though the system seems to work well, Google researchers recently published two technical papers that describe an alternative method for monitoring cardiac activity called Audioplethysmography (APG), which is used to measure heart rate. It is clear from the name that this method utilizes audio equipment like earbuds, as the market trends show that earbuds have proven to be a far more popular wearable in comparison to fitness trackers and smartwatches for wristwear. 

As a result of the deformation of blood vessels in the user's ear canal, Google notes that the volume of their ear canal changes slightly with every heartbeat. In this way, an earbud's speaker driver can pump out ultrasonic sound waves of different frequencies at the same time reverberating up through feedback microphones, also housed in the earbud's speaker, to pick up the reverberation in real-time. 

This works very much the same as sonar in a submarine works. Using a mathematical model, the time and variations between the received echos are then calculated, which then leads to the calculation of an individual's changes in ear canal volume, which are directly related to the rhythm of their hearts. 

According to the research paper titled, ‘APG: Audioplethysmography for Cardiac Monitoring in Hearables’, an ultrasound probing signal that is routed through an active noise cancellation (ANC) headphone's microphone and speaker is routed through the headphone. Echoes then are received from the feedback microphones located on the headphones. 

ANC earphones are equipped with tiny microphones that can be used to detect ambient sounds, so the method will use this function to take note of how the skin surface reacts to changes in blood flow when the low-intensity signal bounces off the ear canal. 

To give persons who do not enjoy wearing smartwatches an opportunity to measure their heart rate on the go, wireless earbuds with heart rate monitoring features are an exciting concept; they allow them to examine their heart rate at any time, no matter where they are. 

The majority of mechanical watch enthusiasts do not wish to give up their traditional timepieces in favour of tech-enabled smartwatches. A significant change will not be required since the technology will utilise existing hardware in the wireless earbuds as already present in these devices. The heart rate monitoring functionality will simply need to be activated by a software update. 

In the meantime, there are no indications that the new heart rate monitoring feature will be available in ANC earbuds shortly. It would however still have to pass all the layers of regulatory approval before its use can be commercially marketed. 

The use of APG involves using a low-intensity ultrasound signal that bounces off the wearer’s ear canal into a microphone that is used to detect ambient sound and then listening back to the earphones or headphones to hear back any disturbances on the skin surface that happen during blood pumping. Despite the limitations of APG technology, few alternatives have prevented ear wearables from being used as health-tracking devices as well. 

Researchers have discovered that the APG measurements are stable regardless of variables like skin colour, the fit or position of the wearable in the canal or the size of the ear canal. The material of the ear tip (silicon or foam are the most commonly used ones that come with the earphones) does not affect the measurements either. 
  
As a result of the evolution of PPG technology, it is expected that users will be able to detect and monitor cardiac activity even while using headphones or earphones to listen to music as they exercise in a gym.

Despite these limitations, it is noted that the work aims to use multiple frequencies and then use software to capture readings to determine which frequency delivers the most accurate signal reading. There are, however, several limitations, including disturbed signal readings in noisy environments. It will be interesting to see how Google uses this technology, however, it is not on the verge of taking this to the real world quite yet. It might not be until sometime shortly, if at all. 

The tech is still in the early stages of testing and refinement, but in all probability, Google could embed this technology in their Pixel wireless earbuds products in the future, and this is something Google might want to consider.
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User Privacy
AI Chatbot AI-Healthcare system Artificial Intelligence Cyber Security Encryption Healthcare Healthcare Data Malicious actor User Privacy

AI in Healthcare: Ethical Concerns for a Sustainable Era

Artificial intelligence (AI) is rapidly transforming healthcare, with the potential to revolutionize the way we diagnose, treat, and manage diseases. However, as with any emerging technology, there are also ethical concerns that need to be addressed.

AI systems are often complex and opaque, making it difficult to understand how they work and make decisions. This lack of transparency can make it difficult to hold AI systems accountable for their actions. For example, if an AI system makes a mistake that harms a patient, it may be difficult to determine who is responsible and what steps can be taken to prevent similar mistakes from happening in the future.

AI systems are trained on data, and if that data is biased, the AI system will learn to be biased as well. This could lead to AI systems making discriminatory decisions about patients, such as denying them treatment or recommending different treatments based on their race, ethnicity, or socioeconomic status.

AI systems collect and store large amounts of personal data about patients. This data needs to be protected from unauthorized access and use. If patient data is compromised, it could be used for identity theft, fraud, or other malicious purposes.

AI systems could potentially make decisions about patients' care without their consent. This raises concerns about patient autonomy and informed consent. Patients should have a right to understand how AI is being used to make decisions about their care and to opt out of AI-based care if they choose.

Guidelines for Addressing Ethical Issues:

  • Transparency: Healthcare organizations should be transparent about how they are using AI and what data is being collected. They should also provide patients with clear information about how AI is being used to make decisions about their care. This information should include the potential benefits and risks of AI-based care, as well as the steps that the organization is taking to mitigate risks.
  • Accountability: There needs to be clear accountability mechanisms in place for AI systems. This may involve developing ethical guidelines for the development and use of AI in healthcare, as well as mechanisms for reviewing and auditing AI systems.
  • Bias and discrimination: Healthcare organizations should take steps to mitigate bias in their AI systems. This may involve using diverse training data sets, developing techniques to identify and mitigate bias, and conducting regular audits to ensure that AI systems are not making discriminatory decisions.
  • Privacy and security: Healthcare organizations need to implement strong data security measures to protect patient data from unauthorized access and use. This may involve using encryption, access controls, and audit trails.
  • Autonomy and informed consent: Healthcare organizations should obtain patient consent before using AI to make decisions about their care. Patients should also have the right to opt out of AI-based care if they choose.

In addition to the aforementioned factors, it's critical to be mindful of how AI could exacerbate already-existing healthcare disparities. AI systems might be utilized, for instance, to create novel medicines that are only available to wealthy patients. Alternatively, AI systems might be applied to target vulnerable people for the marketing of healthcare goods and services.

Regardless of a patient's socioeconomic level, it is critical to fight to ensure that AI is employed in a way that helps all patients. Creating laws and programs to increase underserved people's access to AI-based care may be necessary for this.
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Medical Data
AI Tool AI-Healthcare system Al Technology Artifical Intelligence Cyber Security Healthcare Information Technology Medical Data

Accurate Eye Diagnosis, Early Parkinson's Detection

A revolutionary advancement in the realm of medical diagnostics has seen the emergence of cutting-edge AI tools. This ground-breaking technology identifies a variety of eye disorders with unmatched accuracy and has the potential to transform Parkinson's disease early detection.

According to a recent report from Medical News Today, the AI tool has shown remarkable precision in diagnosing a wide range of eye conditions, from cataracts to glaucoma. By analyzing high-resolution images of the eye, the tool can swiftly and accurately identify subtle signs that might elude the human eye. This not only expedites the diagnostic process but also enhances the likelihood of successful treatment outcomes.

Dr. Sarah Thompson, a leading ophthalmologist, expressed her enthusiasm about the implications of this breakthrough technology, stating, "The AI tool's ability to detect minute irregularities in eye images is truly remarkable. It opens up new avenues for early intervention and tailored treatment plans for patients."

The significance of this AI tool is further underscored by its potential to assist in the early diagnosis of Parkinson's disease. Utilizing a foundational AI model, as reported by Parkinson's News Today, the tool analyzes eye images to detect subtle indicators of Parkinson's. This development could be a game-changer in the realm of neurology, where early diagnosis is often challenging, yet crucial for better patient outcomes.

Dr. Michael Rodriguez, a neurologist specializing in movement disorders, expressed his optimism, stating, "The integration of AI in Parkinson's diagnosis is a monumental step forward. Detecting the disease in its early stages allows for more effective management strategies and could potentially alter the course of the disease for many patients."

The potential impact of this AI-driven diagnostic tool extends beyond the realm of individual patient care. As reported by Healthcare IT News, its widespread implementation could lead to more efficient healthcare systems, reducing the burden on both clinicians and patients. By streamlining the diagnostic process, healthcare providers can allocate resources more effectively and prioritize early intervention.

An important turning point in the history of medical diagnostics has been reached with the introduction of this revolutionary AI technology. Its unmatched precision in identifying eye disorders and promise to improve Parkinson's disease early detection have significant effects on patient care and healthcare systems around the world. This technology has the potential to revolutionize medical diagnosis and treatment as it develops further.
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Software
AI-Healthcare system Artificial Intelligence Cyber Security database Google Healthcare Data Software

AI Surpasses Humans in Odor Identification

Artificial intelligence (AI) has reached another milestone in its quest to mimic human sensory perception. Recent breakthroughs in AI technology have demonstrated its ability to identify odors with remarkable precision, surpassing the capabilities of human noses. This development promises to revolutionize various industries, from healthcare to environmental monitoring.

Researchers from a Google startup have unveiled an AI system that can describe smells more accurately than humans. This innovative technology relies on machine learning algorithms and a database of molecular structures to discern and articulate complex scent profiles. The system's proficiency is not limited to simple odors; it can distinguish between subtle nuances, making it a potential game-changer in fragrance and flavor industries.

One of the key advantages of AI in odor identification is its ability to process vast amounts of data quickly. Human olfaction relies on a limited number of odor receptors, while AI systems can analyze a multitude of factors simultaneously, leading to more accurate and consistent results. This makes AI particularly valuable in fields such as healthcare, where it can be used to detect diseases through breath analysis. AI's unmatched sensitivity to odor compounds could potentially aid in the early diagnosis of conditions like diabetes and cancer.

Moreover, AI's odor identification capabilities extend beyond the human sensory range. It can detect odors that are imperceptible to us, such as certain gases or chemical compounds. This attribute has significant implications for environmental monitoring, as AI systems can be employed to detect pollutants and dangerous substances in the air more effectively than traditional methods.

In addition to its practical applications, AI's prowess in odor identification has opened up new avenues for creative exploration. Perfumers and chefs are excited about the possibilities of collaborating with AI to design unique fragrances and flavors that were previously unimaginable. This fusion of human creativity with AI precision could lead to groundbreaking innovations in the world of scents and tastes.

However, there are ethical considerations to be addressed as AI continues to advance in this field. Questions about privacy and consent arise when AI can detect personal health information from an individual's scent. Striking the right balance between the benefits and potential risks of AI-powered odor identification will be crucial.

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Technology
AI technology AI-Healthcare system Data reading Technology

Aberdeen AI Trial helps Doctors Spot Breast Cancers

 

A trial is happening at Aberdeen Royal Infirmary to test if artificial intelligence (AI) can help radiologists review many mammograms each year. In the trial, AI helped detect early-stage breast cancer in June, who is a healthcare assistant and part of the study. Because of this finding, June will have surgery soon. 

Mammograms are special X-rays used to examine breasts and detect small changes that may indicate breast cancer, even before they can be felt. They are an essential tool in breast cancer screening and are estimated to save around 1,300 lives each year in the UK, according to the NHS. 

In Scotland, there has been an increase in the number of women attending routine breast screenings in the three-year period leading up to 2022. However, at the same time, there has been a decline in the availability of radiologists who review the results. This means that there are fewer healthcare professionals available to analyze mammograms and provide timely diagnoses. 

Artificial Intelligence and Healthcare Systems 

Artificial intelligence (AI) is a technology that enables computers to perform tasks that usually require human intelligence. It is already extensively employed in various industries. The field of healthcare is already witnessing the practical applications of AI, which have garnered considerable attention recently. 

This technology's potential impact on various healthcare aspects has become increasingly apparent. Many scientists and doctors recognize the potential of AI to accelerate the process of discovering new drugs and understanding diseases. Rather than replacing practitioners, AI is viewed as a powerful tool that can work alongside them, enhancing their abilities and improving overall outcomes in healthcare. 

AI and Aberdeen's Trails 

NHS Grampian's Gemini project, a collaboration between the NHS, the University of Aberdeen, and industry partners, was mentioned in Scotland's AI Strategy of 2021. Kheiron Medical Technologies developed the AI model Mia, used in the trial, with cloud computing support from Microsoft. 

Due to existing rules, AI cannot be automatically deployed in screenings, so Dr. Lip and other radiologists are conducting trials to assess its effectiveness as an additional verification step. June, a trial participant, received a biopsy after the AI tool identified a concerning area, as explained by Dr. Lip. 

Additionally, Public Health Scotland (PHS) data discovered that the number of screen-detected breast cancers in women of all ages increased to 1,830 between 2021 and 2022. On average, radiologists review around 5,000 mammograms annually. 

Out of these, approximately 250 to 300 patients are summoned for further examination, with around 30 to 40 individuals requiring closer attention due to potential concerns identified during the initial screening.
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