Global healthcare has become dynamics due to the changes in human lifespan. Nowadays, people are living longer, but until now there are limited equipment and resources specialized in the management of the complex health care challenges that come with long term management of conditions such as cancer, dementia, or Chronic Obstructive Pulmonary Disease (COPD). In the medical field, doctors have found a wide range of application of artificial intelligence. Artificial intelligence helps doctors assess the health risks of a patient and then uses the intelligence to not only improve the quality of care, but also monitor and advice patients on the side effects of certain medications. The impact of Artificial intelligence across the globe is disruptive, with technologically advanced tools enabling better decision-making, diagnosis, and treatment of chronic and acute illnesses. For instance, IBM Watson, an Artificial Intelligence enabled tool is currently widely used in the Middle East and other parts of the world for effective diagnosis of certain cancers. Artificial intelligence is a revolution in the global healthcare system especially in Kuwait and the Middle East region as the region has demonstrated the acceptance of the change through the huge investment and implementation of this technology. The implementation of the technology in healthcare in the Middle East has disrupted the current situation to follow the global evolution of healthcare where technology assists in early disease detection, early diagnosis, and effective diseases management and treatment.
Artificial intelligence allows doctors and other medical professionals to make more accurate and faster diagnosis. In medicine, Artificial intelligence uses mathematical algorithms and data-science from the human body to make diagnosis, better than doctors can do. This gives specialists the ability to take immediate actions for diseases that may otherwise become severe. Smarr (2016) notes that a person’s body can produce about 1 trillion of important data that aid in diagnosis and treatment including DNA, blood type results, and weight. Artificial intelligence has the ability of storing patients’ information and act as the primary source of information of patients from across the globe through the efficiency of accessing important information including existing condition, medical history, family history, and prior diagnosis. Also, it has been used in disease analysis by immediate recognition of pathological areas in an electrocardiography, ultrasound, X-rays, and more different types of scans. Researchers concur that analyses reliant on artificial intelligence can ensure accurate and fast diagnosis of some diseases including malignant melanoma and eye problems. This is because the technology allows the doctors to know exactly how the human body looks like, hence giving them an opportunity to even compare the results with prior cases for effectiveness of the treatment plan devised. This reduces the time the patients have to wait before getting treatment, as well as ensuring that they get the treatment that can address their problems within the shortest time possible.
The role Artificial Intelligence in the early diagnosis of diseases and prevention premature deaths is invaluable in saving lives of patients diagnosed late. Patients whose chronic diseases such as Colloid Cyst, cancer, hypertension, and diabetes among others are detected early have the advantage of getting early treatment, hence giving them an opportunity of a better long term survival compared to those whose diseases are detected late. Unfortunately, in many health centers, effective screening tests for cancer and other diseases such as Colloid Cyst may not be conducted until the disease has progressed to late stages (Al-Hashel et al., 2015). Despite the progress in quality of medical care in Kuwait, many people still die because of late diagnosis of diseases, with the country recording a greater increase in cancer fatalities in young adults, mainly aged between 18 and 32 years in 2013 (Kuwait Times, 2017). One case that exemplifies the importance of early diagnosis is that of 22-year-old healthy lady in Kuwait who succumbed to Colloid Cyst days after her admission while being treated for acute headaches (Al-Hashel et al., 2015). Given the sudden onset of headaches that became persistent even with treatment, early detection of the fatal illnesses could have been avoided if the patient had been tested using early brain imaging. Mainly, the diagnosis dilemma at the initial stages of her illnesses contributed to her death as this delayed her diagnosis for several hours, upon which she died. In terms of preventing late diagnosis of cancer in the country, Kuwait marked the 2017 annual Word Cancer Day on the promise of playing a great role in creating awareness of the seriousness of the disease and other fatal diseases in alignment with the global commitment of fighting against cancer (Kuwait Times, 2017). The application of Artificial Intelligence in the case of the young lady who died in Kuwait, as well as other patients with similar fates can address the issue by effectively and accurately reviewing the image in the CT and MRI scans so that doctors can learn of the potential findings of the scan immediately for early onset of treatment. This will also prevent the overload of data available for doctors when making a diagnosis, hence preventing cases of initial diagnosis dilemma (Patnaik and Yang, 2012).
Artificial intelligence improves the sensitive of the doctors, thereby reducing the cases of human errors. This technology has remarkable effect on both the patients and the doctors by improving efficiency and quality of care as a result of minimal cases of human errors that limit the attainment of optimal health outcomes. The technology benefits the patients by reducing the number of patients that die annually due to diagnostic errors as it offers reliable data that prevent surgical complications, diagnostic errors, and other infections (Celi, 2016). This is despite the fact that there are concerns over losing the patient-physician relationship since the doctors no longer have to strive for medical data through interaction with the patients. Nevertheless, it is worth noting that computers cannot replace the presence of doctors since the human care industry is more of a service industry where the presence of doctors and other medical professionals is key to attainment of optimal health outcomes. It is worth noting that the medical profession is very sensitive as a small mistake can result in extensive damages in the human body, including deaths. As such, the technology is vital in giving the doctors essential precision required to ensure that the patients are handled with utmost precision. The AI has a crucial element that checks for any cases of occurrence of human errors that may endanger the life of the patient of negatively impact the level of safety of the patients.
In terms of preventing or reducing fatalities from medical errors, application of AI is fundamental in ensuring that doctors do not make wrong decisions, especially for diagnosis of cancers. This will prevent cases where patients with health problems that are asymptomatic for cancer are diagnosed with something temporary, but end up having cancer, which is mostly diagnosed in later stages. Evidence shows that 1.3 million people are diagnosed with cancer annually. However, research conducted by Baltimore’s The Johns Hopkins Hospital using a sample of 6,000 patients diagnosed with cancer revealed that out of 71 cases diagnosed, there was a case of diagnosis. For instance, patients with cancer were diagnosed with a temporary illness when the cancer was advancing in the body. In some cases, a cancerous biopsy was diagnosed as cancerous when it was not. Moreover, the results of the study showed that one in five of the cancer types was mis-categorized (Warburg and Nguyen, 2015). Making mistakes in the diagnosis of cancer in terms of misjudging how far the cancer has spread or how fast it is in spreading to other organs has a potentially dramatic impact on the patient’s care. When a cancer diagnosis is wrong, it can lead to a doctor devising a wrong form of treatment. This is because the degree to which the cancer has spread can influence whether the patient gets radiation or surgery or no treatment at all. Moreover, if the patient is to get radiation or surgery, administration of the right type depends on the right diagnosis. There are different areas in biopsy where mistakes can occur, mainly the prostate, female reproductive organs, prostate or the skin. Moreover, since pathologists specialize in different types of cancer, what looks like breast cancer to one pathologist may look like lung cancer to another pathologist based on the slides they are using. That is why it is highly recommended that one should always seek for second opinion when diagnosed with cancer or other illnesses, especially those associated with persistent pain or headaches. This helps give the patients the peace of mind of knowing that the diagnosis is right (Warburg and Nguyen, 2015).
To prevent misdiagnosis or cancer or doctors making mistakes in the diagnosis of different types of cancer, AI can help in ensuring that the right diagnosis is mad for purposes of ensuring that the most effective and timely intervention method is sought so that the patients achieve the best health outcome. One of the most effective form of AI gaining interest in the diagnosis of cancer in the world and in the Middle East is IBM Watson. This technology aims at ensuring that the doctors have access to a vast volume of data on how to treat certain types of data on certain individuals, hence ensuring that doctors are knowledgeable of the best treatment method within the shortest time possible (Manojbhai, Pradipkumar, and Amenakshi, 2016s). The technology works by going deep into the medical literature on the different types of illnesses and the medical reports of a certain patient for purposes of providing advice on the best treatment plan for the patient. The AI technology, dubbed Watson for Oncology has access to millions of medical data, either journals or textbooks. The technology is devised to make the most effective treatment recommendations for cancer using an input of the patient’s descriptions. The technology works in the same way as training cancer specialists in terms of assessment of patients’ recorded, notes made by the doctor, and lab results, and then making informed decisions regarding the most appropriate treatment plan to pursue. The recommendations made are backed up by evidence that is easily available so that the doctors using the information can access the information on the recommended treatment to see the extent to which the diagnosis matches the recommended treatment, as well as the medical evidence that supports it (Seidman et al., 2015).
A combination of AI and robotics in medicine has achieved massive interest in the Middle East, especially in Kuwait, where although AI is not meant to replace human clinician, it has been acclaimed as an evolutionally trend in healthcare. According to a study published by PwC, many patients in the Middle East are increasingly willing to receive health services from advanced technologies if that would lead to potentially advanced transformation of the health system and hence, better health outcomes. Over 55% of the respondents sampled in the study, majorly from the Middle East, Europe and Africa felt that the combination of AI and robots was the answer to the many health dilemmas including performing medical tests, diagnosing diseases and making effective treatment recommendations (Bar-Cohen and Hanson, 2009). In terms of the application of a combination of AI and robots in the diagnosis and treatment of diseases, some of the margining themes that are important in the evolution of health care in the Middle East region include: getting better access to healthcare; getting accurate and high speed diagnosis of diseases, which plays a critical role in the promotion of willingness to accept the new technology; and a high level of trust in the combination of new technology, which has led to widespread adoption and use in the Middle East. Despite the fact that the combination of AI and robots reduces the human touch in a much conservative region like the Middle East, many people are increasingly finding this technology a fundamental element in the experience of healthcare.
The integration of AI and robots is not only effective in the diagnosis of diseases, but also in disease management. After identification of the health problems that may be at risk of cancer or other health conditions, AI and robots can help in devising a robust and comprehensive plan for disease management that help patients get the most effective treatment, and comply with the recommended health care plans for purposes of achieving coordinated and efficient care. For instance, AiCure is one of the most remarkable applications of AI that have made remarkable success in helping patients manage long term illnesses. The program has been designed in a way that it allows patients with long term diseases to monitor their conditions, while helping them comply with their medication intake and other lifestyle changes including exercise, diet and stress management (Shafner et al. 2016). Through the application of a visual recognition system, the technology is able to identify the face of the patient, the condition they have and the medication they are taking. Consequently, they can confirm whether the patient has taken the medication or not. The care giver gets the patient’s data from the system or the pharmaceutical company filling the patient’s prescription. The development and upgrade of robots today has widened the scope and complexity of the functions and tasks that they perform including simple laboratory tasks to complex surgical procedures. Some of these robots can execute simple to complex tasks on their own while the others aid surgeons and physicians in their work. Other than aiding in surgical procedures, robots are used in other treatment and disease management care plans including physical therapy, disease rehabilitation and also in conducting repetitive tasks (Kutner, et al. 2010). In the Middle East, the embrace and implementation of AI in health care in the innovation era has seen more implementation of robots in care delivery.
Despite these benefits, the application of artificial intelligence in healthcare has its limitations. The implementation of this technology has been a controversial topic with critics in social and ethical challenges. First, there are concerns that computers will replace doctors in the hospitals (Bostrom and Yudkowsky, 2014). Moreover, in the Middle East, the use of human data by computers is seen as a disrespected and disregard to the human body, which is seen as a “source of data” from where information is extracted, has characterized debate on the use of this technology. Since patients do not consent to the data gotten by the doctors, it leads to infringement of patients’ right to privacy. Worth noting is the fact that artificial intelligence needs to be understood by the average people, in order for the technology to be adopted by the masses especially in the Middle East where the technology is yet to take shape in the medical field. As such, the information in the systems can be repressed to curtail patient’s freedom of speech. Nevertheless, proponents of AI has come put strongly to argue that AI is a promising technological advancement that promises a revolution in the healthcare system for a better future in the industry. For instance, Practo, the Bangalore-based online healthcare, is one of the leading investors in AI in medicine in the Middle East, arguing that AI technology will only be an assisting tool for the doctors to make better decisions.
The Middle East is still experiencing some glimmers of application of AI in the healthcare field. More people continue to embrace technological application in medicine despite the traditionally valued human touch in care. AI has proven to have positive impact on reduction in mortality rates by improving the efficiency of disease diagnosis, disease management and treatment. AI is a promising technological advancement that promises a revolution in the healthcare system for a better future in the industry. However, it is worth noting that since AI is mainly run through computers, which are machines, there are susceptible to vulnerabilities including breakdown or malfunctioning. There is also the problem of threat of data being accessed maliciously by third parties. Worth noting is the fact that AI has a bright future in healthcare. The technology is a revolution in the global healthcare system as its benefits by far outweigh the potential challenges and fears. Currently, AI in combination with robots has led to positive changes in care, without a replacement of the human doctors and nurses. As such, its application has shown that the technology is only an ingenious complement to doctors as opposed to replacing them. With the positive reception of AI in the Middle East, and particularly in Kuwait, the future of this technology is very promising.
Al-Hashel, Jasem Y., et al. “Diagnostic Dilemma in a Young Woman with Acute Headache: Delayed Diagnosis of Third Ventricular Colloid Cyst with Hydrocephalus.” Case reports in neurological medicine 2015 (2015).
Bar-Cohen, Yoseph, Hanson, David. The Coming Robot Revolution: Expectations and Fears About Emerging Intelligent, Humanlike Machines, Springer. 2009. Print.
Bostrom, Nick, and Eliezer Yudkowsky. “The ethics of artificial intelligence.” The Cambridge Handbook of Artificial Intelligence (2014): 316-334.
Celi, Leo (2016). Machine learning that matters in healthcare: breaking down the silos. [Web] Accessed February 16, 2017 https://mediasite.chla.usc.edu/Mediasite/Play/032abc7ef7164937bf5e611143b1be911d
Kutner, Nancy G., et al. Quality-of-Life Change Associated With Robotic-Assisted Therapy to Improve Hand Motor Function in Patients With Subacute Stroke: A Randomized Clinical Trial/Invited Commentary/Author Response. Physical therapy 90.4 (2010): 493.
Manojbhai, D. D., Pradipkumar, K. K., and Amenakshi, R. R. Big image analysis for identifying tumor pattern similarities. In Advanced Communication Control and Computing Technologies (ICACCCT), 2016 International Conference on (2016, May). (pp. 39-43). IEEE.S
Patnaik, Srikanta, Yang, Yeon-Mo. Soft Computing Techniques in Vision Science, Springer-Verlag Berlin Heidelberg. 2012. Print.
Seidman, A. D., Pilewskie, M. L., Robson, M. E., Kelvin, J. F., Zauderer, M. G. Andrew S. Epstein, Kris, M. G., Gucalp, A. Integration of multi-modality treatment planning for early stage breast cancer (BC) into Watson for Oncology, a Decision Support System: Seeing the forest and the trees. (2015), J Clin Oncol 33,.
Shafner, Laura, et al. Evaluating the Use of an Artificial Intelligence (AI) Platform on Mobile Devices to Measure and Support Tuberculosis Medication Adherence. Takeda Development Center Americas, Inc., Deerfield, IL, USA, 2016.
Smarr, Larry (2016).