With the wide-angle introduction of Chat GPT in 2022, the world has directly fallen in contact with the power of Artificial Intelligence. From curiosity and excitement to fear and concern, AI technological advancements are experiencing humankind all sorts of emotions. Whatever you feel about this one thing is clear you cannot miss the power and potential of AI. Just like any other industry, AI in the Healthcare industry is growing rampant. From cognitive computing, and healthcare robotics, to electronic health records, AI is in use on a large scale here. But at the same time, it is not devoid of ethical and regulatory hurdles. This leads us to wonder about the benefits and challenges of using AI in Healthcare here.
AI in Healthcare: Overview
The global use of artificial intelligence in the healthcare industry is right now sized around $26.69 billion in 2024. But this number is expected to grow at a huge 36.83% CAGR rate to $613.81 by the year 2034. Therefore, there is no doubt that the approach and practices of the healthcare industry are going to change completely with the power of AI in the near future.
With the rapid inclusion of AI in healthcare the automation of many tedious, everyday work becomes possible. From managing huge data of patients or medicines to offering timeless solutions in drudgery, AI is making healthcare tasks faster, more precise and cheaper. AI is continuously moulding and improving itself with more feeding of data. Modern machine learning solutions are providing stellar outcomes in acting, learning, understanding, and anticipating future outcomes.
AI algorithms help in analysing medical images of X-rays and MRIs and provide key understandings that human eyes may often miss. It aids in providing real-time data and recommendations to healthcare professionals, improving their approaches in emergency situations.
However, AI Development Services often has to deal with problems related to privacy, and security potential data breaches. With such a large amount of sensitive medical data, they can become an easy target for cybercriminals. They can use this data in unethical ways to blackmail and manipulate people. Data input poisoning and extraction can also hamper the integrity and faith in the AI models.
Therefore, AI inclusion in the healthcare sector has both positive and negative connotations. An understanding of which is not possible in a few lines. Therefore, let us discuss them in detail in the below segments.
Advantages of artificial intelligence in healthcare
Let us begin with the benefits of using AI in the health sector. The below benefits will give you a clear idea of why AI inclusion is flourishing in this sector.
- Enhancing Accessibility
Lack of accessibility to healthcare facilities often results in increasing mortality rates in developing countries. Ai-backed digital systems can increase the availability of healthcare services to patients in any remote location. On the other hand, it helps medical professionals to access complex data quickly using electronic health records.
- Early Diagnosis
Using AI the diagnosis of present and future health issues of patients becomes very easy. Doctors can accurately point out the disease by skimming through the past history of the patients carefully fed into the database of the AI models. There are several healthcare applications where patients can put their regular health conditions. This helps them notice early signs of a health problem and act accordingly.
- Sharing Information Simply
AI in healthcare can easily locate specific data of the patient from a huge database within a few seconds. This gives enough time for doctors to reflect on their medications and patient care. AI along with wearable devices can develop a healthcare data treasury whose data can be retrieved at any point with ease. AI models help in providing this raw real-time data at needs, thus enhancing the overall patient service to a great extent.
- Unique Assistance in Surgery Through Robotics
Surgeries are the most challenging process in the medical industry. AI and machine learning combined with robotics can make this process simpler with the insurance of utmost accuracy. ROSA robotic surgical assistant is now in use in neurosurgery. Whereas in the case of minimally invasive surgeries Da Vinci Surgical System is effective.
AI in Healthcare: Challenges
Irrespective of its benefits an Enterprise AI Development Company often has to mitigate the issues related to AI integration. As this technology is still in its budding phase, one can witness issues regarding;
- Data Bias
Data bias is a glaring problem in machine learning and analytical algorithms of AI. As a result, any insufficient, inaccurate and biased data fed to the AI model will result in biased results. If developers only provide data of one particular group to the AI, it will fail to predict the problems of others.
- Privacy Risks
The risk of cyberattacks and data breaches is a critical challenge leading to the malpractice of using the sensitive data of patients. With more AI inclusion, the risk of data exploitations will also increase.
- Ethical Concerns
AI inclusion and excessive dependency on it raises ethical concerns regarding its transparency and accountability. If the artificial mind and the arms of the robots take all the actions then who will be responsible in case of any accidental deaths?
- Maintaining Quality and Safety
The question of how much to rely on the merits of the AI also raises concerns. If the model is not tried and tested well before use it may result in the harm of the patients with wrong predictions. Incorrect diagnosis or treatment suggestions of the AI can lead to life risk, which is a key point to consider.
Future of AI in Healthcare
Whatever the challenges of AI in Healthcare may be, one thing is clear: the AI trend is not going to end but only expand day by day. Below are the futuristic trends you may witness in the healthcare sector with AI incorporation;
- AR/VR Solutions
Augmented and virtual reality is going to be in large practice to train medical professionals in an artificial risk-free environment. Trainee surgeons can witness and practice complex operations virtually before opting for actual operations.
- Text-to-image and Image-to-text Processing
AI will be more precisely used in describing an image such as scans, X-ray reports and videos for heightening understanding. Conversely, doctors can make explicit descriptions to instruct AI models to form comprehendible images and diagrams.
- Chatbot for Patient Communication
Chatbots will be more vehemently used to create immediate responses to the queries and grievances of the patient party. Enterprise AI Chatbot Development uses natural language processing and machine learning to create useful simply understandable answers to their questions.
- Ai-based Emotion Detection
In the treatment of mental illness, emotion detection technology of AI will be used to provide solutions to patients solely on their emotional status. To capture and analyse the emotional state, insights from cameras, sensors and microphones will be in more use.
Conclusion
The integration of AI in healthcare is not a trend in the future. It is happening right now at a great pace. AI models and the software holding them are changing the dynamics of patient care in the medical sector. Right from training healthcare professionals to delivering error-free results with utmost efficiency, AI integration has many benefits to offer. However, navigating its challenges is equally necessary to deliver futuristic solutions with the utmost security and data privacy. Therefore, when opting for AI development services you need to look for their reputation and policies to preserve privacy of data.