How Artificial Intelligence is improving healthcare outcomes

Artificial Intelligence in Healthcare
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Abstract
Medical robots are a recurring theme in the health community today. This is due to the advancement of artificial intelligence being introduced in the healthcare sector. Consequently, the presence of AI has shaped the process of medical diagnosis, treatment, drug development, and patient monitoring using algorithms and software that analyse, interpret and assess complex data. Artificial intelligence has produced systems and robotics that are capable of outperforming humans at specific activities that are high profile. As such, AI has become handy in sophisticated medical procedures such as treatment of cancer, neurology, and radiology. Furthermore, its significant play is the advancement in deep learning machines used in neuron simulation. Conversely, the success of artificial intelligence is centred on its ability to process and analyze extensive data. As such, healthcare institutions operating in large medical data benefit a lot from the artificial intelligence system. The system has, therefore, helped transform health care in numerous ways.
Keywords: Artificial Intelligence, Radiology, Neurology, Data
Artificial Intelligence in Healthcare
The fourth industrial revolution is being experienced where a new range of technologies is being fused in all sectors of the economy, industry and biological world, challenging even the idea of human creation and meaning of life. Healthcare is one of the many sectors affected by this revolution, and the primary catalyst of change is artificial intelligence.

The creation of artificial intelligence AI is projected as the most significant impact on healthcare. It can advance the capacity to process, interpret, analyse and store massive data, which can be translated into functional tools. AI is considered the solution to the unprecedented increase in digital capacity, which has produced volumes of patients’ healthcare data. Today, the artificial intelligence is making tentative inroads through robotics, cognitive care, diagnostics, smart devices, and Telemedicine to transform the healthcare market.
Although not yet fully empowered, the effect of artificial intelligence can be felt in the health sector. A number of healthcare-related companies are developing or aligning their operations to suit the new technology. For instance, new technologies powered by AI such as the smartphone used for digital imaging, consumer-operated diagnostic and built-in heartbeat monitor are infiltrating the medical world. This shows a new alleviation in the healthcare sector where medical diagnosis, data management, and consumer-physicians operation will be enhanced. In the description, artificial intelligence is a technology that has transformed machines by giving them the ability to learn, adjust and perform human-like activities. Furthermore, AI enables computers to recognise speech, learn, plan and solve complex task with minimal human influence or supervision. Introducing such a technology in the healthcare sector will not only transform it but also build a system that is self-sufficient and efficient.
Artificial Intelligence and Drug Discovery
A new dawn is underway where big pharmaceutical and biotechnology companies are embracing artificial intelligence in drug discovery and production. The breakthrough in artificial intelligence has reinforced new developments in drug products, which are aimed at reducing cost, improving quality and quantity as well as boost preclinical and clinical drugs. According to the research study by Lee (2017), AI is used to help predict the properties of new drugs, their composition, and effectiveness of the human race. Major pharmaceutical and biotechnology companies such as Merck, the Astellas, AstraZeneca, and Evotec are in line changing their phase of drug discovery using Artificial intelligence. Conversely, discoveries such as the immune-oncology therapies, which are a constituent of bispecific small molecule treatment drug, are being created by the Evotec Company in partnership with other small pharma companies to help on therapeutic treatment of two different cancers.
AI is shaping the healthcare sector through improved drug discoveries that help control the widespread risk of diseases. New drug discoveries in immuno-oncology, cancer therapy and metabolic disease such as diabetes are being discovered with the help of AI. Furthermore, these innovations have open ways to new treatment especially for diseases that have eluded drug abilities. AI has identified new treatments for critical medical conditions like heart failure, psychiatric illnesses, and arrhythmias among others. This has improved the general health and boosted the process of care through finding a solution to diverse medical conditions.
Artificial Intelligence and Cognitive Care
The healthcare industry is experiencing the benefits of advanced cognitive technology through artificial intelligence. The era of cognitive system in healthcare has helped people expand their knowledge, expertise and improve their level of productivity. Cognitive care provides an efficient workflow across departments and teams of healthcare providers by assisting in a better inform care decisions, choices and activities to help improve the overall outcome. Ammatuna and Changcoco (2017) in their study claim that artificial intelligence helps patients understand their condition and state of health and the effective means of managing their treatment or condition, and any potential consequences in the process. Nonetheless, the advent of artificial intelligence in healthcare has improved the efficiency of cognitive care by enabling physicians to access real-life evidence that can be used in treatment and decision-making during diagnosis. Furthermore, cognitive care has enhanced medical systems that harness information such as medical imaging, genetics and other test results from patients. This has reduced the loss of data and other crucial information within the medical care.
Cognitive computing in healthcare system helps in dispensing diagnosis and treatment. AI has introduced software that assists in data analysis and search. This has allowed for physicians to access vast information across the globe, which assists in medical research, treatment, and diagnosis. Additionally, clinical trials decipher, and protocols for patients are easily obtained with the help of advanced cognitive computing (Ammatuna & Changcoco, 2017). This system has enabled physicians to scan or survey clinical data to identify the appropriate clinical trial for each patient. Conversely, AI is shaping the future of cognitive computing which will optimise the process of care through improving information, save cost and boost coordination between patients and their physicians for better outcomes.
Artificial Intelligence and Diagnostics in Healthcare
AI is transforming medical diagnosis of illness from theoretical to the real world. Medical diagnosis is a vital process in a health system that is prone to imprecision if not life-threatening mistakes. However, the advancement of artificial technology has helped advance the whole process of medical diagnosis. AI has introduced the diagnostic tools, systems and devises that help physicians, patients and the entire medical staff in prolific and precise medical diagnosis. AI has provided computing technologies that are highly specialised in assess and diagnosing of different illness. This has helped reduce the possibility of human error and any consequences caused by poor decision-making and judgement during the process of diagnosis.
In the domain of medical diagnosis, AI has helped develop tools that aid in reading, analysis and interpreting numerous variables that affect the process of decision-making. In fact, during diagnosis, there are many uncertain risks, which make the whole process complex. However, AI has introduced expert system frameworks that aid in medical diagnosis. This technology is designed to assess people’s health without even a specialism presence. For instance, today cheap wearable technology sensors that are connected to smartphones are developed to help detect the heart rhythm and diagnose the cardiovascular system of an individual (Lee, 2017). These AI technologies are not only easy to read and access but have shaped the process of medical operation by reducing cost, improving medical accuracy and congestion. Besides, complex diagnoses such as neurology are easy to perform, and risks of errors have been reduced drastically due to the advancement of AI in medical diagnosis.
Artificial Intelligence and Radiology
There are radical changes in radiology following the digitalisation of medical systems through artificial intelligence. AI has promised to create a revolution for radiologist through amplifying human expertise, skills, and information in handling complex medical cases. For very long years, the art of analysing and interpreting medical images has faced significant challenges among radiologists. However, AI is changing the course of image interpretation through advance algorithm techniques and tools that can be used by a radiologist. AI has introduced systems such as the Swarm AI that is applied in radiology. This system is used to recognise disease patterns, outline masses, measurements and identify detail algorithms during radiology report. Further still, this AI tool is fashioned to aid in clinical decision making for radiologist during their diagnosis. This has made radiology an integral part if medical operation and reduced cost as well as errors in radiology report.
Additionally, AI has introduced radiology tools for image analysis and process such as the Blackford Workflow Server. The system has helped radiologist to capture, store, interpret, view, and share images across a more comprehensive platform, making the process of decision making effective. Nonetheless, the presence of artificial intelligence in medical radiology has provided the radiologist with a new approach to accessing, analysis and searching for information that aid in faster and accurate diagnosis. Sensmeier’s (2017) book “Harnessing the Power of AI” reiterates that the use of radiology explorer and Context-Flow Intelligence system has improved data-driven diagnosis in radiology. This has allowed for a holistic approach to accessing patient information and comparing radiology images for easier diagnosis and radiology report. Imaging software and analytic software systems are taking shape in radiology with the help of artificial intelligence. These technologies are helping radiologists further their search and understanding of human physiology and anatomy system as well as boost medical diagnosis.
Artificial Intelligence in Decision Management and Analytics
Decision-making and management is one critical area of health care that determine the outcomes of many variables such as the wellness of patients. Therefore, hospitals have invested extensively in AI to improve the process of decision management and analytics to improve their performance. Artificial intelligence has introduced hyper-intelligence systems that aid in the process of decision making in healthcare. Furthermore, AI is aimed at containing the vast medical knowledge that for years has outstripped even the best physicians. This is possible through the advent of supercomputers that can analyse, access, interpret and transform complex data into workable solutions. Consequently, these technologies have brought a breakthrough in predictive analysis, clinical decision management, genomics and medical diagnosis.
Conversely, Artificial Intelligence has introduced machine learning and natural language processing NLP that are quickly transforming the process of decision management and analytics. These programs have prioritised the process of making choices that are centred on positive outcomes (Gordon, 2011). In fact, the incorporation of AI in decision management is based on data, which help for future reference. It provided logic and probability of sustaining highest outcome success repeatedly over a long duration. Therefore, the matrix of obtaining favourable outcomes in any healthcare process is maintained through the help of artificial intelligence. Significantly, the process of decision management has helped shape the process of medical service by reducing cost, improving efficiency and reducing risks associated with errors or misinformation. AI is bringing a new phase in the process of health care service when it comes to making medical decisions and choices. It has also helped in the ethical process of creating systems that enable physicians to make a justified and concrete decision that focuses on the positive patient outcome.
Artificial Intelligence and Records Management
Just like any other business-operating environment, healthcare data management is vital, and the process of storing and access information records requires proper security system and integration. In hospitals, there is widespread use of data across departments, physicians, and entire medical institution. As such, new bread or record management system has been introduced by artificial intelligence system. The AI system of record management is aimed at improving the access, storage, auto records, and sharing of data or files across the medical fraternity. This will enhance the security of data and reduce the burdensome of access files despite their size or location.
AI has been incorporated in cloud service where big data are stored and managed vastly. Health care records are integrated into the cloud system making its accessible to various parties and increasing protection to crucial information such as personal information. Artificial intelligence introduced the automatic electronic record management system that helped in storage, management, and assessment of patients’ data in a clinical setting. This system helps patients send messages to staff efficiently, avoiding the need for lengthy phone calls and having to hold calls just to get a message through the AI system. In a process that is as simple as writing an email, patients can send messages, absolving staff of the task of re-recording the message. Radick (2017) argues that digital health records systems reduce the frequency and time patients and staffs spend on the phone and reduces the amount of visits patients make to the hospital as they can send messages through the portal.
The integration of AI in health care helps patients enjoy the convenience of accessing their health records wherever they are. Patients also appreciate the ability to check their past prescriptions and making orders when they deplete their drugs. In addition to making work easier for staff, all the patients need to do is log into their account in the portal and make refill requests (Radick, 2017). Artificial Intelligence health record systems also eliminate the need for patients to fill out large stacks of paper before seeing a physician. Therefore, it saves time because the patients fill the forms online, removing the need for staff to transcribe the information from handwritten papers.
Conclusion
In summation, artificial intelligence in healthcare has solved a variety of problems for patients, physicians, and the entire health institution. It has helped in the analysis, interpreting and accessing complex medical data and process. Taking a closer look at the benefit of AI in health care, issues such as cost management, efficiency, exploring new and advance medical procedure are documents. Furthermore, this system has enabled the machines to perform an administrative function such as data management, decision-making and other clinical tasks, which are outlined and boost the overall outcome of healthcare. The use of artificial intelligence today is expected to transform the health system through AI programs that aid in diagnosis, treatment, drug development, patient monitoring and personalised care. Nonetheless, looking at the horizon of the health industry in the next five years, AI technology shall have taken over in all sectors of healthcare delivery. The integration of AI in healthcare without a doubt will help boost the outcome of health care in all its aspects.
References
Ammatuna, G., & Changcoco, R. (2017). Which Trends Will Most Affect Talent Developers in the Healthcare Industry? TD: Talent Development, 71(4), 60-63.
Gordon, B. M. (2011). Artificial Intelligence: Approaches, Tools, and Applications. New York: Nova Science Publishers, Inc.
Lee, W. M. (2017). The Sentient Machine: The Coming Age of Artificial Intelligence. Library Journal, 142(20), 121.
Radick, L. E. (2017). Artificial Intelligence in Healthcare: The Current, Compelling Wave of Interest. Healthcare Executive, 32(5), 21-28.
Sensmeier, J. (2017). Harnessing the power of artificial intelligence. Nursing Management, 48(11), 14-19. doi: 10.1097/01.NUMA.0000526062.69220.41