AI in next generation healthcare

Chronologically, since the year 2000, Healthcare is continuously evolving from reactive healthcare to preventive healthcare. The digital diagnostics and imaging, combined with electronic health records, are poised to eliminate the requirement of conventional hard copy records. Subsequently, as machine learning and deep learning gained traction and 4G and above information communication technologies expanded, the interconnection of devices and databases started revolutionising the health domain from around 2010 and continues to do so. 

Presently, with the artificial intelligence (AI) proliferating in all fields, a paradigm shift in healthcare diagnostics and treatment are imminent. Fast-upgrading technologies in healthcare are empowering hospitals and medical professionals with high precision diagnostics, powerful imaging tools, AI-powered analysis & prediction, and smart monitoring systems. Besides, the health data generated in healthcare infrastructure, the predominance of wearable IoT devices for real-time physiological and behavioural data monitoring is opening fresh opportunities for continuous availability of updated health databases, and will essentially strengthen the collaboration between humans and AI. 

This new eco-system of healthcare with extensive use of cyber physical systems is facilitating the training of AI models for various healthcare requirements. Eventually, it appears that based on the symptomatic inputs, the machine intelligence may predict ailment and prescribe medication, while advising for necessary precautions to remain disease free. But, the moot point of concern is whether the next generation of healthcare will be relying on constantly improvising AI algorithms for better computational accuracy in prediction & analysis, or something more basic and humane. Also, the suitability of advanced technology deployment and integration as envisaged in Industry 4.0 ought to be assessed in light of a human-centred approach, optimum resource utilization, agility, and resilience as well, instead of merely focusing on technical efficiency. Thus, the Industry 5.0 perspective is required for considering human values and system resilience in the upcoming Healthcare 5.0. 

Present Challenges

Introspection of the present healthcare system demonstrates frequent hardships because of its reactive and hospital-centric nature. Challenges include the increasing fraction of aging population with limited family care, smaller and independent families, increasing chronic diseases calling for continuous interventions, lifestyle disorders, escalating healthcare costs, lack of time to take care, making affordability difficult, absence of precise diagnostic systems everywhere, insufficient preventive care, limited sharing of experiences of clinical processes & practices, exclusivity of healthcare data related to patients. disease, and treatment, etc. Alongside the opaqueness and/or lackadaisical health services, lack of awareness, limited accountability. Inequality in healthcare facilities, varying proficiency of medical professionals, insufficiency of diagnostics, growing number of deaths due to non-communicable disease, uneven access to trained medical professionals, and gaps in interpreting the ailments and prescribing appropriate lines of treatment, etc., keep worrying the public health from time to time, especially the socially disadvantaged and economically marginalized groups. 

In the context of India, there has been a remarkable expansion in medical colleges in both the public sector and private sector under Pradhan Mantri Swasthya Suraksha Yojna, and a good number of medical professionals are rolling out, but the stringent checks on the quality of education and training are essential, failing which it could be disastrous. The healthcare reforms in the last decades under the National Rural Health Mission, Universal Health Coverage, and Ayushman Bharat Yojana have been gamechangers for the less privileged people to a certain extent, which can be much more effective with the digitization of health data of every citizen, healthcare services, and databases.

Many of such challenges can be taken care of to certain extent by the use of contemporary technological interventions that make healthcare proactive, proficient, patient centric, and global. Also, the objective functioning of AI-based healthcare systems may help in establishing a preventive healthcare system for the well-being of people.

Modern Technology in Healthcare

Apart from various high precision technological interventions in sensing, data acquisition, and diagnostics, the capabilities of real-time monitoring and care beyond the formal healthcare framework by IoT gadgets are transforming modern healthcare in the presence of reliable and low-latency communication networks. Eventually, with the potential of machine learning, deep learning, natural language processing, large language models, and computer vision put together are offering AI proficiency in recognizing patterns and offering better diagnostics, analysis, and recommending personalized treatment for not only supporting clinical decision making but also pushing for drug discovery to cure typical ailments. The convergence of modern technologies powered with algorithms to effectively and accurately read data from high-fidelity scans like, CT, MRI, PET, Ultrasound, X-ray, etc., and diagnose complications and predict risks better than a human being. Thus, it is for sure that the AI will be transforming the clinical work flow, reducing delays in detection, providing desired clinical assistance, better documentation, and offering digital therapeutics. While augmenting healthcare using machine learning, these AI doctors can never replace the human doctors because of the human attributes of sensitivity, cognitive & emotional empathy, compassion, reassurance, experience, cultural understanding etc. Also, embedding AI in healthcare has ethical issues of who will be held responsible in case an AI outcome affects the individual adversely, i.e., whether the mishap occurs due to the AI application developer or the person using it, or the doctor. However, the cues can be drawn from the AI in healthcare to make healthcare practices much more responsible, accountable, and transparent. 

Next Generation Healthcare

Next generation healthcare system can be built on the premise of digitizing health data of every person, continued sensing to generate health data, sharing of data, data analysis, feedback, early ailment detection, and an action plan for clinical or otherwise interventions. The convergence of modern technologies to yield AI powered systems and digital twins of the healthcare system could be used for delivering personalized treatment and care to individuals.  Such a technology assisted healthcare system may also essentially facilitate healthcare professionals to corroborate their findings and enable them to look beyond diagnosis with more empathy, healing, faith, and other human considerations of the sufferer. Nevertheless, the clinical deployment of AI in healthcare may have ethical issues, algorithmic biases, demographic biases, absence of accountability, and the loss of privacy as major concerns. These challenges undermine the potential of AI to transform healthcare and create a trust deficit that will have to be circumvented. 

The time is ripe to train the medical professionals to take the next generation healthcare forward by integrating their professional competencies with the precision diagnostics, databases, networking, and potential of AI. Because the use of AI in healthcare calls for a larger understanding of the context behind its recommendations and the ability of medical professionals to make appropriate adjustments. At the same time, healthcare transformations must not be allowed to become purely artificial and mechanical; instead, maintaining strong ethical standards is inevitable for ensuring that the system remains profoundly human. 

END OF ARTICLE