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Using Artificial Intelligence And Robotics in the Healthcare

For the longest time, artificial intelligence was considered the subject of the future.

Well, we are now living in the world we once called "futuristic."

Artificial intelligence has a wide range of applications in the current times.

However, in this blog, we'll focus on how AI and robotics are used in the healthcare industry.

You will also learn how they are likely to be a major part of the healthcare industry in the coming future.

What Is Artificial Intelligence?

AI can be defined as a computer system that has been programmed to carry out specific tasks or operations with minimal human intervention.

AI systems are thought of as "smart" or "intelligent." They are capable of learning, problem-solving, reasoning, and self-correction.

One of the major areas where AI is being used by healthcare organizations is in the classification of data. This makes it easier to identify patterns that can be analyzed about their clinical significance.

Using AI also helps in automating cumbersome tasks involved in billing processes. For example, medical coders can reduce their daily workload by spending fewer hours manually classifying physician notes.

Using AI also helps in the early detection of hospital-acquired infections. Studies show that the use of natural language processing (NLP) can enable accurate detection in real-time or near real-time, which can lead to faster containment and reduced burden.

What Is the History of Artificial Intelligence in Healthcare?

The use of artificial intelligence in healthcare first happened in the 1960s and 1970s. The first artificial intelligence method was developed in the academic environment, where the creation of expert systems was carried out with government funding.

In January 2016, IBM's Watson supercomputer beat two former winners of "Jeopardy!" on the American quiz show. It was an achievement that marked a significant milestone in AI, as IBM was able to make Watson learn on its own.

For the first time, healthcare providers had access to a computer with human-like insight and cognitive capabilities.

Though many people associate AI with IBM's supercomputer Watson, the term artificial intelligence has existed since 1956. It was, then, defined as "the science and engineering of making intelligent machines, especially intelligent computer programs". It is an umbrella term that encompasses all technologies that enable machines to replicate human intelligence.

The massive increase in the availability of data means that the amount of knowledge available today has far exceeded the skill levels and capabilities of individual humans.

AI enables us to utilize this outside knowledge to make more informed decisions for better, more informed healthcare across all sectors.

What Is the Use of Artificial Intelligence in the Healthcare Sector?

• AI and Diagnosis :
  

  An application that uses AI to identify different types of cancer cells in medical images is currently being tested for its clinical value. The algorithm was trained using two million images, which were annotated by pathologists, and learned features automatically. It can help reduce the time needed to diagnose certain types of cancers.

  Among the advantages are high-level pattern recognition, speed, and accuracy. The downside is the reliability of the algorithm has not been proven yet in clinical trials for its ability to accurately diagnose patients, some experts say.

• AI and Imaging :

  AI has turned imaging into a big data problem. Imaging specialists can sort through terabytes of medical images, only presenting the radiologist with the information most relevant to their task at hand.

  AI has turned imaging into a big data problem. Imaging specialists can sort through terabytes of medical images, only presenting the radiologist with the information most relevant to their task at hand.

• AI and Oncology :

  In oncology, researchers have been studying genetic markers for some time as a way to personalize treatment by targeting the specific cancer mutations with drugs, but it has been challenging due to the heterogeneity of tumors and patients' genomes.

  With AI tools that can analyze large amounts of genomic data from multiple patients, researchers hope they can personalize treatment even further.

• AI and Treatment :

  AI can be used to design new therapies. An example of this is pharmacogenomics which involves using genetic information to personalize drug dosing or predict how well a patient will respond to a certain drug. Furthermore, AI can help discover cures faster by analyzing DNA, RNA, and proteins to study how certain genes are expressed.

  AI can be used to design new therapies. An example of this is pharmacogenomics which involves using genetic information to personalize drug dosing or predict how well a patient will respond to a certain drug. Furthermore, AI can help discover cures faster by analyzing DNA, RNA, and proteins to study how certain genes are expressed.

  AI-powered software can also help analyze large sets of patient data—including their family history, the results of diagnostic procedures, and the efficacy of particular treatment protocols.

  These technologies can then identify which patients most urgently need specific therapies, determine an optimal course of treatment for each patient, and predict how specific mutations may react to different drugs.


• AI in Drug Development :

  Sophisticated computational tools are used in virtually every phase of drug discovery and development. For example, pharmacokinetic models can be used to predict the optimal dosage and timing of drug administration to achieve the desired effect while minimizing negative side effects.

  Scientists can also use computational tools such as machine learning and data mining to analyze large datasets, identify biomarkers that could predict a patient's response to treatment, and discover molecular pathways that can lead to new drugs.

  AI can be used in the art of medicines by developing new techniques for the drug discovery process. The use of AI in the pharmacy has drastically disrupted the pharmaceutical industry by allowing companies to get smarter about how they produce, identify, and distribute their products.

  Advances in genomic sequencing have allowed researchers to understand more about individual patients' responses to drugs than ever before. These advancements are expected to give rise to personalized therapies, in which drugs are designed to work with an individual patient's unique genetic makeup.

• AI and Genetics :

  Genetic research has enabled the development of powerful new drugs like immunotherapies that work by stimulating a person's immune system to fight cancer cells or viral infections.

  Computational algorithms allow scientists to gather large amounts of data (DNA sequences, corresponding health records, clinical outcomes, demographics, etc.) and use them to discover patterns that may lead to the development of innovative therapeutics.

• AI in Neuroscience :

  Neurological diseases are notoriously difficult to predict, treat, or cure. However, AI has the potential to revolutionize neuroscience. The use of big data analytics in healthcare is growing rapidly with several companies being created in the past year.

  Advancements in wearable devices have enabled us to monitor our health with unprecedented precision. Wearables equipped with sensors can detect a variety of human activities, including walking, running, and driving. It can also monitor vital signs such as blood pressure and even check an individual's heart rhythm. This has begun to play a significant role in the detection of chronic diseases such as sleep apnea and hypertension.

  Though still in its infancy, AI offers great hope for neuroscientists, who have struggled for decades to understand the complexities of our brain. The technology enables computers to learn without being explicitly programmed, mimicking the way neurons fire and wire together in a human brain as it learns. This method has already allowed AI systems to perform tasks that previously could be accomplished only by primates or other mammals.

• AI and Surgical Procedures :

  AI is also being popularly used in surgical procedures. The healthcare industry is also relying heavily on robotics for surgical procedures such as hysterectomy, prostate surgery, and even dental implant surgeries.

  Other examples of patients benefiting from AI systems in hospitals include a robot developed by Harvard Engineers which can help with brain tumor diagnosis through MRI scans.

  AI is also being used to perform knee replacement surgeries that are more effective than the manual method. In 2017 alone there were over 600,000 knee replacement surgeries performed and the AI system is expected to reduce those numbers even further. AI systems can also greatly help in more advanced neurosurgeries such as brain tumor resection and epilepsy surgery.

What Is the Future of AI in the Healthcare Sector?

Looking at the pace at which AI is becoming popular in the healthcare sector, in a matter of 10 years, it is expected that AI will be helping out physicians at almost every step of the diagnosis and treatment process.

Today, using AI, nurses can monitor patients remotely on wearable devices or smartphones without even having to be in the same room virtually anywhere in the world. A solution like this reduces costs by reducing patient monitoring time required for nurses which mean lower overhead for hospitals.

Additionally, the solution improves patient care by reducing errors due to human error.

AI in healthcare can provide highly accurate recommendations based on machine learning algorithms that are fed with large amounts of data, which has contributed to the field's growing popularity in having AI play a role in healthcare delivery.

Using deep learning technologies, doctors are now able to diagnose cancer with 97% accuracy. The technology is also being used for other purposes such as automated detection of heart sounds to prevent sudden cardiac arrests and intelligent detection of skin cancers.

Another potential application is the use of AI-powered robots that can assist doctors in performing surgeries by using general-purpose autonomous robotics capable of making surgical interventions under the guidance of a surgeon.

Currently, several companies are using AI in surgery including Arterys that has focused on cardiovascular surgery, and Accuray has focused on the use of robotics in surgical procedures for cancer treatment.

Both these companies have developed advanced imaging technology that creates three-dimensional images of the heart or tumors before surgery to analyze the tumor and plan the procedure.

This technology can be further improved by using advanced imaging techniques such as spectral CT, which provides information about metabolism within tissues and improves diagnosis of cancer on top of MRI and ultrasound imaging.

Hence, we can infer that the future of artificial intelligence in the healthcare sector is quite bright.

Conclusion

In this blog, you learned about the use of artificial intelligence in the healthcare sector.

Having said that, just like every coin has two sides, it's only natural that there will be challenges about the AI and robotics assistance in our healthcare system.

Nevertheless, moderation is the key.

If humans learn the limitations of robotics and use it in moderation, we would be able to avoid potential harm to humankind.