The health care sector ready to embrace artificial intelligence (popularly known as AI) or not is the big question. The healthcare sector deals with sensitive data of a patient’s medical history and related information; artificial intelligence is slowly taking over the healthcare sector to render more accuracy, transparency, and data privacy. Artificial intelligence is firmly establishing its roots across all industry verticals; it is particularly useful in the healthcare sector for patient diagnostics and treatment management. While it implies that it will overtake human discretion in the decision-making process, there is enough evidence and study to prove that artificial intelligence, if used wisely, can help to better the human judgment and improve the efficiency of treatment of diseases.
One might wonder what precisely artificial intelligence entails, and how it benefits the healthcare sector? Let us delve in to know more and touch base on all the curiosity.
Artificial intelligence extensively relies on the database, which the doctors and clinical practitioners use as the diagnostics resources to diagnose and treat the patients. It helps to churn a faster diagnostic output with greater efficiency and accuracy backed by doctors’ and practitioners’ knowledge. Many times, patients show genetic, physical as well as acquired symptoms. Under such circumstances, the diagnosis can be delayed if the symptoms are not identified at the right time. At this time, the AI-powered healthcare practice allows doctors and practitioners to come to quantitative and qualitative conclusions based on the input of the patient’s health condition. It helps to escalate patients’ conditions and provide them with an on-time accurate diagnosis and treatment.
How Does AI Work To Aide And Improve Healthcare Services?
AI’s efficiency depends on the continuous data it receives from the doctors’ and practitioners’ feedback responses. The AI-powered systems continuously learn from these feedback responses and improve their learning abilities by continually enhancing its back-end database. The AI systems provide the doctors with a real-time database always evolving, making it more effective and accurate to work. The ever-evolving data comprises the images from the lab examinations and its electronic recordings, notes from the physical reviews spread across all age groups, and demography that gives the doctors and practitioners an unlimited resource to diagnose and treat patients better. Thus it is a continuous learning process to build a network of reliable diagnosis resources.
What Are The Different Types Of AI That Can Be Integrated Into Healthcare?
When talking about AI, it is an umbrella term comprising various technologies under it. These technologies have headstrong relevance in the healthcare sector. While we touch on AI technology in healthcare, it is imperative to learn about these technologies that make AI briefly.
1. Machine Learning
One of the most commonly used technologies in AI, machine learning, essentially comprises teaching the machines and feeding them with data to learn better and provide an accurate output. One of the surveys conducted by Deloitte in 2018 states that of the 1100 managers in the US who have adopted AI, 63% of the companies were using machine learning at the core of healthcare practice. A large part of machine learning requires training the dataset for which an outcome variable is known, and is popularly known as supervised machine learning.
One of the slightly complex forms of machine learning is a neural network, which has been employed in the healthcare sector for over quite some time now. It encompasses predicting whether or not a patient will acquire a particular disease based on a specific input. Purely based on the principle that a dedicated input weighs against the input variables, a reliable output is generated. It forms the crux of predicting disease based on patients’ existing systems.
Deep learning is one of the most complex aspects of machine learning, which comprises many layers of variables attached to a dedicated input for which a reliable output is desired. One of the most common applications where deep learning is effectively used is identifying cancerous lesions in radiology images. It is used to decipher the clinically relevant features of ideas beyond what can be perceived by the human eye. Deep learning is found most useful in studying the oncology-related images and helps draw accurate conclusions on the diagnosis and its subsequent treatments.
2. Natural Language Processing
This AI field includes speech recognition, text analysis, translation, and other language activities. Natural language processing allows us to have greater accuracy in language and speech recognition based on machine learning. It is widely used to analyze patients’ clinical notes, prepare notes, and decipher patient interaction and conduct.
3. Robotic Process Automation
Unlike the perceived named, robotic process automation does not involve any robotic interaction. It is more of a combination of a well-defined workflow and business rules and the presentation layer integrated with information systems that act as the systems’ partial intelligent user. The AI-powered robotic process automation performs administrative chores based on pre-defined rules and scripts.
These technologies that collectively make up for the AI are increasingly used in conjunction with one another to reap desired and accurate results in the healthcare sector.
What Are The Varied Applications Of AI Closely Related To Healthcare?
As much as it is crucial to understand the various technologies widely used in AI, it is equally important to understand the myriad applications of AI in the healthcare industry. The healthcare industry does use AI to its optimum capacity to streamline diagnosis and improve patient treatment planning. Identifying the processes and applications where AI technology can be effectively put to use in the healthcare industry is one of the primary forms of the IT consulting firms’ significant responsibilities that take in their stride to identify and help implement the AI in the healthcare sector. With the experience at hand, IT consulting firms know the best possible way to transform the AI-powered ones’ legacy processes. Based on experts’ discretion at the IT consulting firms, let us look at some of the applications where AI can be effectively used.
1. Diagnosis And Treatment Application
AI technology is used to diagnose and treat disease with equal or greater efficiency than human discretion. Since the diagnosis and treatment in healthcare are based on feeding statistical data to improvise machine learning, the future of healthcare can expect the probability-based medicinal therapy of patients.
2. Patient Engagement And Adherence Application
The more patients focus on their well being, the better it will be for the healthcare professionals to leverage the resources at hand. AI can be employed to curate a patient’s health care plan to cure chronic disease. It is based on the patients’ determination of how strongly they adhere to the care-plan. This is the aspect where the capabilities if AI can be effectively utilized to draw personalized patient care plan through interactive devices like smartwatches, smartphones, biosensors, and other tools which gives tailor-made recommendations to the patients to tale care of their health.
3. Administrative Application
AI can be employed in the healthcare industry’s administrative tasks to improve various processes like claims processing, clinical documentation, revenue, and medical records management. Chatbots are one of the other examples to ease the administrative tasks and help in the patient interaction for their mental health and wellness, telehealth consultations. Thus, reducing the healthcare administrators’ load and rendering on-time accurate administrative and diagnostics tasks of the healthcare industry.
Concluding Thoughts: The Future Of AI In Healthcare
The advancing feat of AI in healthcare is a reminder that it has a significant role in the future’s healthcare offerings. It is now established and collectively agreed by medical professionals across the globe that accurate diagnosis, treatment, and predictive medicine is the need of the hour. And AI will only help in better diagnosis of human health conditions. Many healthcare industry sectors, like radiology, pathology, and oncology, to name a few, extensively rely on AI technology for effective diagnosis of the patients’ medical condition.
AI can be effectively used when all the stakeholders using the technology are well adopted and taught to use the technology to benefit the patients and the healthcare practice. In hindsight, AI will not replace human capabilities but only compound to their powers of taking better care of patients.