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Health Care, Medical

Chronic Disease Essay

According to PricewaterhouseCoopers’ chronic diseases and conditions are growing worldwide. “While infectious diseases such as SARS and Ebola, for the propagation of the long global flow do not occur to me. It is because of the significant global increase in the aspect of mobility, it must be in the things of the epidemic in order to reduce the number of those who are in a hurry the infection of which it can be named Despite the significant progress in the fight against infectious diseases, it nevertheless has something of the common effective vaccination, such as tuberculosis, malaria, and HIV.

A few years later, there have been positive advances in diagnosis, treatment, and treatment for fear, such as the chest of certain tumors and cervical cancer, as well as leukemia in children.

The World Health Organization reported the number of chronic diseases is 57%. However, before detecting the disease and helping reduce the costs diagnose and treat chronic diseases. Some of these new information technologies include genomics, the prostate, biology a small chamber, a bedroom door of the organ of each of the lorem chambers, so that nothing is minimally invasive and robotic.

In the last ten years, innovations and medicines are new technologies, including:

“parts of the human body 3D printing, rapid printing proliferation of blood vessel cells and skin wound healing

“Looking artistically look ugly from California, which provides constant

“Remote control, a small, internal, which offers remote control of electrical fluids to alleviate

200% more than the object itself that with the sword they do for employees, a product is already very flexible and can develop at a lower price of things in Lorem applications used for medical devices, such as fabric a lot. Age and cataracts trigger the need for surgery. Artificial blood sugar levels of insulin and faucets in a cake and were reading a sensor and shame. Buprenorphine doses to treat respiratory clients to place pain implants, palates, and narcotic pain. According to VentureBeat, the database industry there are 55 of their community have developed in the 218 an artificial was chosen, it will be free.

From the Abbot Glocestri Ab of the Bishop, the research of Frost in 2016, the IA the health of the market to reach 6.6 billion dollars, and the profit of many different technologies in 2021 This is not surprising is the growth of ‘artificial intelligence. AI is the future of health and forwards to helping doctors, without replacing them.

The birth weight of AI

That the term ‘artificial data’, published in 1956 was that of a conference, at Dartmouth College. Until 1974, AI is difficult to pay not only to communicate natural geometry and Latin. 1987 between 1980 and then there was an increase in the number of questions listed here, whether it is solvent or expert systems, and has responded to specific information problems camera has no less concern for IA from IBM until 1997 when he met great Russian master Garry Kasparov From that day, the same hands, the test vehicle is first home independent or home, the human-robot robot – February 2011, Watson IBM a major hit in two dangers! champions of the game show – last year, a computer program DeepMind artificial intelligence (Google) AL phage a professional game player to play in Go. Currently, games, big, faster computers, and modern machine learning play a role in the development of artificial intelligence.

It does not have a lot of energy consumption, including finance, transport, and health, which will change the industry to determine the diagnosis and treatment of the disease. AI is to identify all people, and the hearing of a manuscript; The portico of the virtual image of reality; the processing of natural language, chat, boots, and translation; E-mail, spam filtering, robotics, and e-mail. According to Tractica analysis, They targeted, the global annual income of 2025 increased by $ 36.8 billion to AI.

Role of AI in Healthcare

Virtual Health Assistant

Virtual health officials (VHAs) can proactively contribute to different forms of the disease. Initially, VHA dementia can help patients go through prescription drugs by sending their warnings. In addition, virtually, service providers can provide advice on general health or treatment of patients with certain provisions of the disease or their diet.

diagnostic

AI is to improve medical diagnosis. For example, medical diagnosis images using the Beijing Infervison artificial intelligence for AI is to improve granular and 10 computer-ray images. The technology used in hospitals in China to detect suspected leaps and nodules in patients with lung cancer. It allows doctors to diagnose the disease early and send the tissue to the laboratory for analysis in order to distribute more than ever before.

Researchers at Stanford University have developed an artificial intelligence algorithm that could diagnose and diagnose skin cancer. This technology uses images of molecules, applause, and suggestions that can be found on the mobile phone application someday. Some of them provide, Alphabet, and Google with the image of the work in high-level recognition to detect the use of artificial intelligence programs that, by weight. This program can be done faster than the previous normal way of translating the diagnosis and treatment. Furthermore, in order to analyze the data so that the AI can be found in large quantities, how the disease is and assists them, in order to identify the clinical trials of monitoring.

It can be saved at any time for any living man,

Patients for medical treatment available for the boots are the most important. Boot in health quantitatively mobile applications can help you recover quickly, sending in real-time and messages. They administer the problems of drug and the health benefits of the sick will be answered to chatbots, he provides information on the type of drug and the recommended doses.

Some progress can be equaled in groups;

To study and make human studies

The ideal way to establish relationships with empathic patients

Send a natural language of processing, analysis of the movement, and the government of mourning conversation. Comprehensive image identification tasks to analyze photos, manuscript notes, and barcodes. Other solutions include the field of artificial information, developed in the field of health:

  • Heart Rate Analysis
  • Extra robots for the elderly
  • Medical record mines record
  • Treatment design plans
  • To help with repetitive work
  • Advisers
  • Creating medicines
  • Using avatars for clinical training
  • Advantages of AI in healthcare
  • Achievements in treatment

AI manages health practice, for example, to improve the treatment solution for data analysis to provide better treatment and treatment of controls.

Doctors do not have the ability to identify the disease found to be infectious, such AI, FH, MRI, CT, and ultrasound, and the 10 rays, it is also to do is not easy to diagnose, and speed up, reducing the accuracy of careful and precise. a couple of hours a week waiting period for the patient.

virtual assistants

On an established day, people were with him, and for a moment I want to instantly see the answers, the virtual assistants for the patients’ answers the possibility of doing so in real-time. Medical patients can ask questions, and answers, and more information and acceptance are medication reminders, physiotherapy, and informed other care. Doctors can right of the health care professionals are good for the treatment of being co-workers of a subsequent large order, and of patients.

reduce costs

Cicero Abbate GlocestriAb Bishop says that artificial intelligence could increase by 30-40% and a greater reduction of 50% in costs. Reducing the strength to improve the sensitivity and effectiveness of physiological them that they have to pay for human errors. Doctors can get some information on patients with the disease they fear in their hospital.

According to Accenture, a key used for clinical applications of AI at $ 150 billion a year can be saved for the health of economic health in 2026 in the United States.

treatment plans

Another benefit of AI takes care of treatment, which can develop plans. Doctors can now search the database, for example, a medical assistant, modernize the medicine for collection, and diagnosis, and prescribe patient test data that provide price information.

AI-Risks in Healthcare

Accuracy and safety

As AI is new, it is not as accurate and reliable, so patients are at risk. The BBC article “Real Artificial Risks” addresses this problem:

“Take an education system to be in a hospital to find out that patients with pneumonia are more vulnerable to death and that asthma patients are classified as casualties as endangered. This is a normal condition when the history of pneumonia and Asthma is directly into intensive therapy, Training: Learning machine means that there is asthma + pneumonia = low risk of death.

Moreover, the AI should be sufficiently reliable to store sensitive data, such as mailing and financial information, and health information. Organizations that use confidential medical information should make sure that their exchange policies ensure the safety of their information.

Risk of new/exceptional cases

AI should only be taken to ensure that it is accurate, safe, and modern with new medical care. In other words, the program will be as good as it is. Programs must be trained, or are continuously updated at least, to identify new/exceptional health conditions.

Risk for doctors and patients

AI can also be dangerous for doctors and patients. Since doctors are not ideal, doctors can not have full confidence in AI, and they must continue to make decisions based on their knowledge and experience. Patients are also at risk for the same reason. If the program gives false information, the patients will not be treated properly.

Challenges for healthy AI

One of the difficulties encountered by AI in the field of healthcare is clinical widespread acceptance. Understanding the value of AI, the health industry must create a recognized workforce under AI so that it is convenient to use AI technologies so that AI “learning” technologies can be smarter.

Doctor / Patient Education

Doctors and AI patients are another problems. Some may find it difficult to learn how to use this technology. Likewise, the information is not available to everyone clearly. In other words, education needs to be addressed by adopting AI technologies.

It is also a problem that legislation for AI is fulfilled in the health sector. Initially, FDA approval is required before the AI device or application is applied to medical care. This is particularly true because AI is in a new phase and is not fully or sustained. Moreover, in the current approval process, AI equipment is more cautious, rather than data. For this reason, AI data is a new regulatory issue for the FDA and should be checked in more detail.

How does AI improve the future with AI?

AI meets many parks. AI has a positive impact on doctors and patients in healthcare. Because of the ability to collect and analyze different data, AI may make a faster and more accurate diagnosis for a wider segment of the population. People who do not have access to highly specialized medical services can avail of this experience through AI. Due to earlier and more accurate diagnoses, the cost of healthcare can be reduced. Accordingly, AI has a risk to the medical profession and patients. As the data pool grows and is more viable, doctors will continue to use their training and experience to ensure that artificial information provides appropriate diagnosis and treatment.

Bibliography

Gulshan, V., Peng, L., Coram, M., Stumpe, M. C., Wu, D., Narayanaswamy, A., et al. (2016). Development and Validation of a Deep Learning Algorithm for the Detection of Diabetic Retinopathy in Retinal Fundus Photographs. Jama, 316(22), 2402. http://doi.org/10.1001/jama.2016.17216

Esteva, A., Kuprel, B., Novoa, R. A., Ko, J., Swetter, S. M., Blau, H. M., & Thrun, S. (2017). Dermatologist-level classification of skin cancer with deep neural networks. Nature, 542(7639), 115– 118. http://doi.org/10.1038/nature21056

https://medium.com/machine-intelligence-report/data-not-algorithms-is-key-to-machine-learning- success-69c6c4b79f33

http://www.datasciencecentral.com/profiles/blogs/10-great-healthcare-data-sets

JASON 2013, A Robust Health Data Infrastructure. JSR-13-Task-007.

JASON 2014, Data for Individual Health. JSR-14-Task-007. https://www.cbinsights.com/research/artificial-intelligence-startups-healthcare/

JASON 2017, Perspectives on Research in Artificial Intelligence and Artificial General Intelligence Relevant to DoD. JSR-16-Task-003.

https://contently.com/strategist/2017/05/23/artificial-intelligence-hype-cycle-5-stats/

  1. Davis, K. Stremikis, C. Schoen, and D. Squires, Mirror, Mirror on the Wall, 2014 Update: How the

U.S. Health Care System Compares Internationally, The Commonwealth Fund, June 2014.

For instance, DirectDerm: https://www.directderm.com/, and PlushCare: https://techcrunch.com/2016

/11/03/plushcare-nabs-8m-series-a-to-prove-telehealth-can-go-mainstream/

Translating Artificial Intelligence into Clinical Care, Andrew L. Beam, Isaac S. Kohane, JAMA 316, 2368, 2016

Opportunities and Obstacles for Deep Learning in Biology and Medicine, CS Greene et al., bioRxiv preprint first posted online May. 28, 2017; doi: http://dx.doi.org/10.1101/142760.

The Parable of Google Flu: Traps in Big Data Analysis, David Lazer, Ryan Kennedy, Gary King, Alessandro Vespignani, SCIENCE 343, 1203, 2014

N.H. Pijls, P. van Schaardenburgh, G. Manoharan, et al. Percutaneous cornonary intervention of functionally nonsignificant stenosis: 5-year follow-up of the DEFER Study. J. Am Coll. Cardio 49, 2105 (2007).

M.R. Patel, et al., Low Diagnostic Yield of Elective Coronary Angiography, The New England Journal of Medicine 362, 886 (2011).

 

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