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24 October 2024
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Usage of AI in medicine and how can it improve our lives?

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AI in Healthcare: Transforming Diagnosis and Treatment

Artificial intelligence (AI) is revolutionizing various industries, and healthcare is no exception. From early disease detection to personalized treatment plans, AI is poised to transform the way we approach medicine, leading to better patient outcomes and more efficient healthcare systems.

Enhancing Diagnostic Accuracy

One of the most significant contributions of AI in healthcare is improving diagnostic accuracy. Machine learning algorithms can analyze medical images—such as X-rays, MRIs, and CT scans—with remarkable precision. For instance, AI-powered tools have been developed to detect signs of cancer, neurological disorders, and cardiovascular diseases at stages earlier than traditional methods allow. By identifying subtle patterns and anomalies that might be missed by the human eye, AI assists clinicians in making more accurate diagnoses.

Personalized Treatment Plans

AI enables the development of personalized medicine by analyzing vast amounts of patient data to tailor treatment plans to individual needs. Genetic information, lifestyle factors, and medical history can be processed by AI algorithms to predict how a patient might respond to specific treatments. This approach increases the effectiveness of therapies while minimizing side effects, marking a significant shift from the one-size-fits-all model of traditional medicine.

Streamlining Administrative Tasks

Beyond direct patient care, AI is optimizing administrative functions within healthcare facilities. Natural language processing (NLP) algorithms can transcribe and interpret doctors’ notes, streamline patient record management, and even assist in scheduling appointments. By automating these routine tasks, healthcare professionals can devote more time to patient care, improving overall efficiency and satisfaction.

Drug Discovery and Development

The process of developing new medications is time-consuming and costly. AI accelerates drug discovery by predicting how different compounds will interact with targets in the body. Machine learning models can analyze existing pharmaceutical data to identify potential new uses for existing drugs or predict the efficacy of new drug candidates. This not only speeds up the development process but also reduces costs, ultimately bringing effective treatments to patients faster.

Remote Patient Monitoring and Telemedicine

With the rise of wearable technology and the Internet of Things (IoT), AI plays a crucial role in remote patient monitoring. Smart devices can collect real-time health data—such as heart rate, blood pressure, and glucose levels—and AI algorithms analyze this data to detect any concerning trends. This continuous monitoring allows for timely interventions and supports the growing field of telemedicine, making healthcare more accessible, especially in remote areas.

Ethical Considerations and Challenges

While the benefits of AI in healthcare are substantial, they come with ethical considerations. Patient privacy is paramount, and the handling of sensitive health data requires robust security measures. Additionally, there is a need to ensure that AI algorithms are free from biases that could lead to disparities in care. Collaboration between technologists, healthcare professionals, and ethicists is essential to navigate these challenges responsibly.

The Future of AI in Healthcare

As AI technologies continue to advance, their integration into healthcare will likely deepen. We can anticipate more sophisticated diagnostic tools, further personalization of treatment, and even AI-assisted surgeries. The potential for AI to improve global health outcomes is immense, but it will require ongoing innovation, ethical vigilance, and a commitment to equitable access.

Conclusion

AI is reshaping healthcare by enhancing diagnostic capabilities, personalizing treatments, and streamlining operations. While challenges remain, the continued collaboration across disciplines promises a future where AI significantly contributes to improved patient care and health outcomes. Embracing these technologies thoughtfully will be key to unlocking their full potential in the medical field.

TK
AI used: ChatGPT 1o

https://www.nature.com/articles/s41586-019-1799-6

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17 December 2023
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ROLE OF ARTIFICIAL INTELLIGENCE IN PREDICTING RESPONSE TO CARDIAC RESYNCHRONIZATION THERAPY

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Artificial Intelligence (AI) has become a superhero in the world of medicine, especially when it comes to predicting how well a special heart treatment called Cardiac Resynchronization Therapy (CRT) will work, but first let’s get to know what exactly CRT is.

What is Cardiac resynchronization therapy (CRT)?

Cardiac resynchronization therapy(CRT) is a medical intervention designed to treat heart failure, specifically in individuals with impaired cardiac function and conduction abnormalities. It is a standard treatment for mild-to-moderate and severe heart failure.  The primary goal of CRT is to improve the coordination and synchronization of the heart’s ventricles (the lower chambers), which can be disrupted in certain cardiac conditions. However, not all patients exhibit the same positive response to CRT, leading researchers and clinicians to explore innovative approaches to predict individual outcomes. Artificial intelligence (AI) models have shown promising results in predicting response to CRT, offering a personalized and efficient approach to patient management.

Challenges in Predicting CRT Response:

Despite the proven benefits of CRT, predicting which patients will respond optimally remains a challenge. Traditional methods rely on clinical parameters, such as ejection fraction and QRS duration, but these may not provide a comprehensive understanding of an individual’s response. AI models, on the other hand, can integrate a multitude of variables and identify complex patterns that might escape traditional analysis.

Types of AI Models in Predicting CRT Response:

Machine Learning Algorithms:

  1. Supervised learning algorithms, including decision trees, support vector machines, and random forests, can analyze historical patient data to identify patterns associated with positive CRT outcomes.
  2. Unsupervised learning algorithms, such as clustering techniques, can reveal hidden subgroups within the patient population, helping tailor CRT strategies based on specific characteristics.

Deep Learning Models:

  1. Neural networks, especially deep learning models like convolutional neural networks (CNNs) and recurrent neural networks (RNNs), excel at learning intricate patterns and representations from large datasets.
  2. Deep learning models can extract features from various imaging modalities, such as echocardiograms or cardiac magnetic resonance imaging (MRI), to enhance the predictive accuracy.

Natural Language Processing (NLP):

  1. NLP techniques can be employed to analyze and extract valuable information from textual data, such as electronic health records and medical literature, providing additional context for predicting CRT response.

Benefits of AI in CRT Prediction:

Improved Accuracy:

  1. AI models can process vast amounts of data and identify subtle correlations that might be challenging for human clinicians to recognize, leading to more accurate predictions of CRT response.

Personalized Medicine:

  1. By considering a wide range of patient-specific factors, AI models contribute to the realization of personalized medicine, allowing for tailored CRT strategies based on individual characteristics.

Real-time Decision Support:

  1. AI models can provide real-time decision support to clinicians, aiding in the interpretation of complex data and facilitating timely interventions for patients who may benefit from CRT.

Challenges and Future Directions:

While AI holds great promise in predicting CRT response, challenges such as data quality, interpretability, and generalizability need to be addressed. Ongoing research aims to refine existing models, incorporate multi-modal data sources, and validate findings across diverse patient populations to ensure the widespread applicability of AI in CRT prediction.

Conclusion:

The integration of artificial intelligence in predicting response to cardiac resynchronization therapy represents a transformative step towards personalized and effective patient care. As technology continues to advance, AI models will likely play an increasingly crucial role in optimizing CRT outcomes, ultimately improving the quality of life for individuals suffering from heart failure. As research progresses, the collaboration between clinicians, researchers, and AI experts will be vital in harnessing the full potential of these innovative predictive models.

Links:

https://www.hopkinsmedicine.org/health/treatment-tests-and-therapies/cardiac-resynchronization-therapy

https://link.springer.com/article/10.1007/s10741-023-10357-8

https://academic.oup.com/eurheartj/article/44/8/680/6808667

https://pubmed.ncbi.nlm.nih.gov/34454883/

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25 November 2023
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The ethical implications of AI in medicine

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Privacy is one of the concerns related to application of artifical intelligence in medicine. Ai technology can easily gather and analyse vast amount of patient data. This include sensitive information like medical history or generic data. Appropriate protocols must be established for data sharing, storage, and collecting in order to guarantee impartial data management.   

Another ethical concern is bias. AI systems are only as good as the data they are trained on, and if that data is biased, the system will be biased as well. This can lead to unfair treatment of certain groups of patients, particularly those from marginalised communities. To ensure the accuracy of AI systems, it is crucial to use diverse and comprehensive data that represents the entire population. Taking this step will enhance the objectivity and reliability of the technology. 

Another important consederation when it comes to artifical intelligence in medicine is transparency. Patients have a right to know how AI systems are being used to make decisions about their health and treatment.Doctors have responsibility to be transparent about the programs thay are using. This will help in building trust between patients and doctors. 

Finally, accountability is a key ethical consideration when it comes to AI in medicine. Healthcare providers have to ensure that AI systems are being used in a way that is consistent with ethical and legal standards. This includes being sure that the algorithms used are accurate, reliable and that they are not being used to discriminate against certain groups of patients. 

In conclusion, the use of AI in medicine has the big potential to change the healthcare and improve patients treatment. However it is important to be aware of ethical concerns that arise when using AI in medicine. By doing so we can ensure that artificial intelligence is used in a responsible and etical way. 

Sources:

Privacy and artificial intelligence: challenges for protecting health information in a new era | BMC Medical Ethics | Full Text (biomedcentral.com) 

bing.com/ck/a?!&&p=06b7ea41d8c5fc88JmltdHM9MTcwMDg3MDQwMCZpZ3VpZD0yOTBhYjRmMi00MDBmLTY0ZmMtMmNkZi1hNjkwNDExZDY1MTYmaW5zaWQ9NTQ3NA&ptn=3&ver=2&hsh=3&fclid=290ab4f2-400f-64fc-2cdf-a690411d6516&psq=bias+ai+in+medicine&u=a1aHR0cHM6Ly9uaWhjbS5vcmcvcHVibGljYXRpb25zL2FydGlmaWNpYWwtaW50ZWxsaWdlbmNlcy1yYWNpYWwtYmlhcy1pbi1oZWFsdGgtY2FyZSM6fjp0ZXh0PUFydGlmaWNpYWwlMjBpbnRlbGxpZ2VuY2UlMjAlMjhBSSUyOSUyMHRvb2xzJTIwc3VjaCUyMGFzJTIwYWxnb3JpdGhtcyUyMGFyZSx1c2UlMjBvZiUyMHJhY2UlMjB0byUyMHByZWRpY3QlMjBvdXRjb21lcyUyMGFuZCUyMHJpc2su&ntb=1 

AI engine: Bing Ai

Image creator: Kreator Obrazów z aplikacji Projektant Microsoft (bing.com)

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12 November 2023
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AI in Medicine

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Healthcare stands out as a crucial and highly sought-after service. Every day, tens of millions of patients rely on it for diagnosis, treatment, and care. Unfortunately, the diminishing number of specialists and their constrained resources often hinder efficient operations. This is where external assistance becomes essential, and Artificial Intelligence (AI) has played a significant role in addressing these challenges. Let’s explore its contributions to the field of medicine.

  1. Personalized medicine

Personalized medicine, also known as precision medicine, is an innovative approach to medical treatment and healthcare that takes into account individual differences in patients’ genes, environments, and lifestyles. The goal of personalized medicine is to tailor medical care to the characteristics of each patient, allowing for more effective and targeted interventions.

The field of personalized medicine has been made possible by advancements in genomics and other technologies that allow for the analysis of an individual’s genetic information. By understanding a person’s genetic variations, healthcare providers can better predict their risk for certain diseases, determine the most appropriate treatment options, and even develop preventive strategies.

Personalized medicine has the potential to revolutionize healthcare by moving away from a one-size-fits-all approach to treatment. Instead, it allows for treatments that are specifically tailored to an individual’s unique characteristics, increasing the likelihood of successful outcomes.

Some examples of personalized medicine include:

  • Pharmacogenomics. This field focuses on how an individual’s genetic makeup affects their response to medications. By analyzing a person’s genetic variations, healthcare providers can determine the most effective and safe dosage of a medication for that individual.
  • Cancer treatment. Personalized medicine has had a significant impact on cancer treatment. By analyzing a tumor’s genetic profile, healthcare providers can identify specific mutations or biomarkers that can be targeted with specific drugs. This approach, known as targeted therapy, has shown promising results in improving outcomes for certain types of cancer.
  • Genetic testing. Genetic testing can provide individuals with information about their risk for certain diseases, such as Alzheimer’s disease or certain types of cancer. This information can help individuals make informed decisions about their healthcare and take preventive measures if necessary.
  • Mental health Support and AI

AI therapists, also known as virtual therapists or digital mental health platforms, are applications or programs that use artificial intelligence (AI) to provide therapeutic support or mental health services. These AI therapists are designed to simulate certain aspects of human interaction and are often used to supplement traditional therapy or as a convenient and accessible alternative.

Many AI therapists operate through text-based interfaces, allowing users to engage in conversations with the program. These interactions are designed to simulate a therapeutic conversation, providing support, empathy, and guidance.

  • Chatbots and virtual assistants. AI-powered chatbots and virtual assistants can provide immediate support and guidance to individuals experiencing mental health issues. These tools use natural language processing to understand and respond to users’ queries, providing information, resources, and even basic counselling.
  • Accessibility and Convenience. One of the main advantages of AI therapists is their accessibility. Users can access these platforms at any time and from anywhere, providing a level of convenience that traditional therapy may not offer.
  • Anonymity. Some people may feel more comfortable discussing sensitive topics with an AI therapist due to the anonymity it provides. This can be particularly beneficial for those who are hesitant to seek help in a face-to-face setting.
  • Support for Specific Issues. AI therapists can be designed to provide support for a variety of mental health issues, such as stress, anxiety, depression, and more. They may offer coping strategies, relaxation techniques, or refer users to additional resources.

Chatbots are increasingly being used to offer advice and a line of communication for mental health patients during their treatment. They can help with coping with symptoms, as well as look out for keywords that could trigger a referral and direct contact with a human mental healthcare professional.

Conclusion

From my point of view, AI in medicine holds immense potential to revolutionize healthcare by improving diagnostics, personalizing treatments, and increasing efficiency. But we should keep in mind that AI would not replace human, especially in Mental Health Support. There is a plethora of upsides in using technology in Medicine. However, careful consideration of ethical, regulatory, and privacy concerns is essential to ensure responsible and beneficial implementation.

Sources(reference):

https://www.forbes.com/sites/bernardmarr/2023/07/06/ai-in-mental-health-opportunities-and-challenges-in-developing-intelligent-digital-therapies/?sh=7ee87ea75e10

https://www.economist.com/science-and-technology/2018/06/09/artificial-intelligence-will-improve-medical-treatments

https://www.economist.com/technology-quarterly/2020/03/12/medicine-is-getting-to-grips-with-individuality

https://www.ibm.com/topics/artificial-intelligence-medicine

AI generator used: Chat.Openai

Some of the prompts I used:

1. AI in Medicine

2. AI in Mental Health Support

3. Personalised Medicine

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7 November 2023
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THE POWER OF AI IN MEDICINE: TRANSFORMING HEALTHCARE FOR A BETTER FUTURE

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In the evolving landscape of healthcare, Artificial Intelligence is an innovation, reshaping the industry and redefining patient care. The integration of AI technologies has ushered in a new era, promising improved outcomes, enhanced diagnostics, and a patient experience like never before. Let’s explore the remarkable impact AI is making in various areas of medicine while delving into its benefits and acknowledging the challenges it presents.

AI IN MEDICINE: REVOLUTIONIZING PATIENT CARE

DIAGNOSIS

AI-driven diagnostic tools are the vanguard of medical innovation, analyzing vast amounts of medical data swiftly and accurately. These tools enhance the speed and precision of disease identification, providing healthcare professionals with valuable insights for prompt intervention and treatment.

An example of such innovation is AlphaMissense, a new model from Google, which analyzes the effects of DNA mutations and will accelerate research into rare diseases. The model can predict the likelihood of them causing a disease with 90 percent accuracy. AlphaMissense helps researchers accelerate the slow process of matching genetic mutations to diseases.

DRUG DISCOVERY AND DEVELOPMENT

The traditional approach is complex and time-consuming. It typically commences with the identification of a biological target, often a disease-causing protein. The processes can involve thousands of iterations and years of effort before a candidate is even ready for human testing. Furthermore, many of these candidates may fail due to their interactions with the entire human body.

AI provides an enticing shortcut. By processing vast volumes of data such as the effectiveness of existing drugs, generative AI models can create drugs that are precisely designed for the intended purpose. The designed drug molecules can then be synthesized according to specifications. 

Companies like Atomwise leverage AI to repurpose existing drugs, demonstrating its potential in addressing urgent medical needs, such as treating Ebola.

TELEMEDICINE

The rise of AI-powered chatbots and virtual assistants has revolutionized patient engagement. These virtual healthcare companions provide patients with vital health information, schedule appointments, and offer continuous support, enhancing accessibility to medical advice and services. AI can also help monitor a patient, provide feedback to them and alert to early warning signs of disease progression.

MEDICAL IMAGING

AI’s prowess in medical imaging has reached unprecedented heights. Algorithms developed by Google’s DeepMind, for instance, can detect diabetic retinopathy from retinal scans, preventing blindness in diabetic patients. Such breakthroughs exemplify the transformative potential of AI in the field of medical imaging.

BENEFITS OF AI IN HEALTHCARE

ENHANCED DIAGNOSTICS

It enables healthcare professionals to make diagnoses with unprecedented accuracy, offering several benefits, including improved patient outcomes and increased survival rates. AI-based diagnostic tools use advanced algorithms to analyze complex medical data quickly and effectively. For example, in the field of medical imaging, AI has demonstrated exceptional prowess in identifying and characterizing abnormalities in radiological scans. 

EFFICIENCY

By automating administrative tasks, AI enables healthcare professionals to focus on what truly matters – patient care. This streamlined approach reduces administrative problems, enabling a more efficient healthcare system.

DRAWBACKS AND CHALLENGES

DATA PRIVACY

The utilization of sensitive patient data raises valid concerns about data privacy and security breaches. To fully harness the advantages of telemedicine technology, healthcare providers must first establish a secure platform for sharing personal health information. Healthcare institutions are prime targets for cyberattacks due to the wealth of valuable data stored in their networks.

ETHICAL DILEMMAS

AI algorithms, while powerful, must navigate complex ethical questions, especially concerning life-altering decisions about patient care and treatment. Striking the right balance between human judgment and AI-driven recommendations is crucial.

CONCLUSION

In conclusion, AI in medicine is more than just a technological advancement; it represents a pivotal shift in healthcare that has the potential to improve patient outcomes, enhance efficiency, and redefine patient care. As the healthcare landscape continues to evolve, harnessing the full potential of AI will require addressing its challenges proactively while upholding the principles of patient-centered and ethical care. The future of healthcare, with AI at its core, holds the promise of a healthier and more accessible tomorrow.

SOURCES

https://www.wired.co.uk/article/deepmind-ai-alphamissense-genetics-rare-diseases

https://www.wired.co.uk/bc/article/generative-ai-will-transform-medicine-hsbc-global-private-banking

https://www.techtarget.com/searchenterpriseai/feature/How-AI-has-cemented-its-role-in-telemedicine

https://www.sciencedirect.com/science/article/pii/S1120179721001733#b0060

https://news.harvard.edu/gazette/story/2020/11/risks-and-benefits-of-an-ai-revolution-in-medicine/

CHAT GPT 3.5

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19 October 2023
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AI in Medicine

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Healthcare is one of the most important and in-demand services we have. Tens of millions of patients need diagnosis, treatment, and care daily. However, the declining number of specialists and their limited resources are not always able to perform efficiently. It’s where external help is required, and by now Artificial Intelligence (AI) has facilitated a lot. Let’s have a look on its role in medicine.

                                              The utilization of AI

The application of AI in medicine has two main branches: virtual and physical. The virtual part includes machine learning (mathematical algorithms). It’s applied to collect and manage patient data, improve the accuracy of diagnoses, recommend treatments, and develop medication. Moreover, you can use machine learning to program computers to make connections and predictions and discover critical insights from large amounts of data that health care providers may otherwise miss. The main goal of machine learning is to improve patient outcomes and discover solutions which were unavailable before.

The physical branch includes physical objects, medical devices and sophisticated robots taking part in the delivery of care (carebots). Some robots assist surgeons during complex procedures that require precise movements. Sometimes they also take the role of solo performers. In many cases, robotic surgery reduces the procedure’s invasiveness, which can also lower complications and improve outcomes. AI-driven robotic devices assist patients with tasks like rehabilitation exercises, providing real-time feedback and adapting routines based on the patient’s progress. The aim is to reduce potential life threatening aftermath, save specialists’ time, and give a faster conduction of treatment.

                                                     Conclusion

AI does a great job in saving lives and making medicine more accurate and efficient. Due to its rapid development we can wait for inventions and upgrades. Nevertheless, it all should be done through ensuring solid data privacy and guaranteeing high-quality and accurate solutions for patients.

Sources:

  1. https://www.sciencedirect.com/science/article/abs/pii/S1096288319300816
  2. https://www.who.int/news-room/facts-in-pictures/detail/patient-safety
  3. https://www.coursera.org/articles/machine-learning-in-health-care?utm_medium=sem&utm_source=gg&utm_campaign=B2C_EMEA__coursera_FTCOF_career-academy_pmax-multiple-audiences-country-multi&campaignid=20665163467&adgroupid=&device=c&keyword=&matchtype=&network=x&devicemodel=&adposition=&creativeid=&hide_mobile_promo&gclid=CjwKCAjwp8OpBhAFEiwAG7NaEi7mKzm7WBJJp_p5xHiC77xQ2mYxuOmMXDInA9YPMF9wGf_6w8Z2kxoCU2UQAvD_BwE
  4. https://bmcmedinformdecismak.biomedcentral.com/articles/10.1186/s12911-020-01191-1#Ack1
  5. The information about the role of the robots was partly taken from https://chat.openai.com/c/d26a2b3b-0925-4f2c-ba75-ac72083e9c06
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29 January 2023
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AI is creating human proteins that can treat cancer, COVID and flu

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I think that almost all of you are familiar with a new shocking AI technology called Dall-e, which was introduced quite recently. This is a platform that generates images by just specifying what you wish to view. Social media sites are now crowded with these surprisingly detailed, often photorealistic images created by this or similar technologies. However, some scientists perceive it as more than just a means of creating pictures. They see it as a way to treat various diseases, such as cancer or flu.

Recently, by using these modern AI technologies, scientists have started generating blueprints for new proteins – tiny biological mechanisms that play a significant role in our bodies’ operation, ranging from digesting food to moving oxygen through the bloodstream. Although these proteins are produced naturally in our bodies, researchers are still striving to improve the ability to fight diseases and do things that our bodies can not produce on their own.

For more than 30 years, David Baker, the head of the Institute for Protein Design at the University of Washington, has worked to develop artisanal proteins. He and his colleagues have established this was feasible by 2017. However, they did not anticipate how the emergence of new AI technologies would radically speed up this task, cutting the period of time required to produce new blueprints from years to only a few weeks.

Proteins are made up of long chains of chemical components that then twist and fold into three-dimensional structures. Recent research from AI labs like DeepMind, which is owned by Alphabet, has demonstrated that neural networks can successfully predict the three-dimensional shape of any protein in the body based only on the smaller compounds it contains.

T1037, part of a protein from (Cellulophaga baltica crAss-like) phage phi14:2, a virus that infects bacteria.

Nowadays researchers are taking a step further by creating blueprints for totally new proteins that do not exist in nature, by using AI systems. The objective is to develop proteins that adopt highly specific shapes. A particular shape can perform a certain function, such as preventing the COVID-19 virus. Researchers can provide a rough description of the protein they want, then a diffusion model can generate its three-dimensional shape. However, scientists still need to test it in a wet lab with actual chemical compounds to make sure it functions as expected.

On the one hand, some experts take this innovation with a grain of salt. Frances Arnold, a Nobel laureate, comments it as “Just a game”. He states that what really matters is what a generated structure can actually do.

On the contrary, Andrei Lupas, an evolutionary german biologist, is convinced that it will change medicine, research and bioengineering. “It will change everything”. AlphaFold has helped him to find the structure of a protein he was tinkering with for almost a decade.

Personally I agree with a majority of researches and assume that AI is a tool for exploring new innovations that scientists could not previously think on their own.

References:

https://www.seattletimes.com/nation-world/artificial-intelligence-intelligence-turns-its-artistry-to-creating-human-proteins/

https://www.nature.com/articles/d41586-020-03348-4

https://www.scientificamerican.com/article/one-of-the-biggest-problems-in-biology-has-finally-been-solved/

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13 January 2023
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AI, Devices

New step forward to fight agains breasts cancer using AI

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At least once in a year or two years every woman is recommended to go through mammography test. Such testings are important to spot the cancer on early stages. However, outside of being crucial, it is also expensive. This problem is faced by low-/middle-income countries, while the amount of woman that have or, as a result, die from cancer is gradually increasing over last years.

In India, where half of the woman with this disease die, new way of spotting breast cancer was found. A small and portable camera which works basing on AI and consisting thermal in it.

Researcher Builds Non-Invasive Device To Detect Breast Cancer

The test is taking around 10 minutes and the only thing woman should do is to remove the top. One of the main advantages of this test is that no one is touching you, especially considering that this fact was stopping some people from the mammography test. 

The test works in the way of producing detailed heatmap of the breasts, and if it spots patterns typical for cancer, the woman is required to undertake further tests 

There is the hope that this invention will make tests more accessible in the place where mammography is considered intrusive or is less accessible.

60,000 women were already tested using this technology, the inventor of the ‘machine’ claims that the camera is 90% accurate in detecting abnormalities. 

However, what is the Western countries’ opinion on this Indian invention? 

Doctors from US and Europe still doubt this invention and think that thermal tests are not reliable, so you cannot use this, when it comes to the point that the result can threaten patient’s life. 

What is more, the US Food and Drug Administration stated that mammography is and will be the best screening method. On controversy to this, the other statement of US FDA is that they hope, these specific tests will reach people, that cannot afford or avoid undertaking regular ones. 

However, that is a great start for such an important development of 21st century. Breast cancer is one of the biggest problems when it comes to causes of womens’ death. 

Here you can read more about AI related test that help doctors to fight with breasts cancer by detecting it on early stages: https://www.cureus.com/articles/106594-artificial-intelligence-in-breast-cancer-screening-and-diagnosis

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28 December 2022
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AI

Telesurgery. Worthwhile or dangerous?

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Would you ever believe that surgeons will be able to operate on a patient even though they are 400 km away? That is exactly what telesurgery can allow. It is an innovative surgical tool that connects patients and surgeons who are geographically distant. The surgeon observes the surgical area on the screen and uses a haptic arm to move the robotic arm during the operation.

On the one hand, there are many benefits of telesurgery in comparison to conventional surgical methods. First and foremost, telesurgery is an excellent solution for those who for some reason can not travel to get medical care. Not only financial constraints but also travel-related health issues can pose a problem for some people. Secondly, it enables surgery through smaller incisions and its robotic arms are able to reach hard-to-access areas in the body. It also eliminates a surgeon’s possible tremor resulting in improved surgical accuracy. Consequently, the risk of damaging surrounding structures, the risk of blood loss, and the risk of infection are alleviated. Aside from this, telesurgery gives surgeons from different centres an opportunity to collaborate and operate on a patient simultaneously. 

On the other hand, there are some issues in the field of telerobotic surgery. Firstly, a time lag is considered to be a major drawback while using telesurgery. It was determined that a time delay of more than 2 seconds can be a threat. Secondly, being operated on by a surgeon, a patient has never met face-to-face, can cause distrust and anxiety. And finally, a researcher at Obuda University in Budapest who studies space telesurgery, Tamas Haidegger, noted that despite having a master surgical plan, things can go wrong. For example, blood circulation can collapse, or there is an unforeseen reaction to certain drugs. That is why there is still a necessity to have a trained surgeon on-site. Nonetheless, he believes that soon robots will be augmented with artificial intelligence and will be able to go into autopilot mode. It would be a significant breakthrough in human history! 

Having considered all possible pros and cons of telesurgery, in my opinion, the technology is worth being widely embedded. I would agree that it can scare some people that a robot is performing an operation. However, in reality, surgeons are in full control of the machine at all times and the robot’s movements are far more precise. 

https://www.cureus.com/articles/54068-telesurgery-and-robotics-an-improved-and-efficient-era

https://www.bbc.com/future/article/20140516-i-operate-on-people-400km-away

https://my.clevelandclinic.org/health/treatments/22178-robotic-surgery

https://www.google.com/url?sa=i&url=https%3A%2F%2Fwww.zdnet.com%2Farticle%2Fsurgery-digitized-telesurgery-becoming-a-reality%2F&psig=AOvVaw24ZZag0koxCxL8Q79N4bMp&ust=1672333433108000&source=images&cd=vfe&ved=0CBAQjRxqFwoTCIjfz9PlnPwCFQAAAAAdAAAAABAj

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15 December 2022
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AI

AI in medicine

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Artificial intelligence has a wide range of use in every industry that we can think off. It is meant to make people’s work more efficient and more accurate. But the biggest advantage of using this algorithms is that they can conduct hard and time consuming tasks with the imperceptible margin of error.

But how AI is used in medicine?

Thanks to AI algorithms and machine learning models there are a lot of possibilities in which professionals are able to use them. Currently the most common roles of AI in this field are supporting clinical decisions and imaging analysis. The idea of clinical decision programs is to help specialist make decisions about the treatment, medications and other things that patients need. Whereas the imaging analysis is intended to analyse X-rays scans and many others to provide the information faster and more accurate. It also speeds up some process considering developing new medicine.

Recent Applications of AI in Medicine

1.Diagnose Diseases

The diagnosis part of treatment is the most crucial one. It takes years of medical training to do them correctly. What’s more it is time-consuming process, which might directly influence patients that are waiting for the treatment. That why machine learning is particularly helpful in this area. However not all diseases can be diagnosed by machines, because lack of digitalized data. Luckily there are few that AI and doctors decided to start with, here are some examples:

2.Personalized treatment

There are many different patients and they respond differently to drugs and the ways of treatment. Actually it’s not an easy task to decide what medicine will work the best in your scenario. So that specialist came up with an idea of personalized treatment method. They use the machine learning algorithms to automate the process of discovering characteristic that a specific patient will have a good response to a particular treatment. The system learns this by cross-referencing similar cases with the outcome of the treatment. It all makes much more easier work for doctors.

3. Remote medicine

Ai in this industry isn’t only meant for doctors and specialists. It is also deployed for patients directly. Since the outbreak of the Covid-19 pandemic there has been a significant growth of Ai chatbots in hospitals and small clinics to help patients recognize their health problems. They have also significantly reduced challenges people had to overcome while searching for help.

There are also applications in which you can define what are your symptoms and the algorithm will automatically say what disease are you struggling with. It will also advise you to go to see the doctor if necessary. It was especially useful during pandemic to reduce number of patients coming for appointments.

Video:

To sum up, Ai is already helping us in many aspects of medicine. There are lot more things that it optimizes and helps with. But it is just the beginning , the more we digitize medical data the more we can use AI to search new patterns. It surely is the future of our Medicine.

If you want to learn something more I advise you watching the video below. Let me know what do you think about such algorithms.

Sources:

IBM: https://www.ibm.com/topics/artificial-intelligence-medicine

Data revenue: https://www.datarevenue.com/en-blog/artificial-intelligence-in-medicine

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