AI technology is redefining the traditional framework of healthcare's 4Ps: predictive, preventive, personalised, and participatory medicine. Making it easier for healthcare professionals to diagnose issues and treat patient

Artificial intelligence (AI) is at the forefront of a healthcare revolution, fundamentally altering patient care, diagnosis, and treatment. The evolving landscape of AI technology is not only enhancing patient outcomes but also redefining the traditional framework of healthcare's 4Ps: predictive, preventive, personalised, and participatory medicine. 

AI-driven predictive analytics, preventive care, personalised medicine, and participatory medicine have changed the course of the healthcare sector for the better. Machine learning algorithms can now forecast disease outbreaks, identify vulnerable populations, and predict patient health deterioration. 

Leveraging extensive datasets, machine learning can analyse an individual's health data and genetic information to identify potential health risks. AI plays an important role in medication research, finding potential drugs and their efficacy for individual patients. This level of personalisation means that therapies are not only more effective but also have fewer unfavourable side effects, resulting in better patient outcomes. 

Using artificial intelligence, patients take an active role in their healthcare decisions. Individuals can get real-time health data and personalised advice through health monitoring applications, wearable devices, and virtual assistants. Patients are urged to participate actively in their healthcare journey by making educated decisions, measuring progress, and cooperating with healthcare practitioners. This collaborative approach improves patient satisfaction and treatment plan adherence, ultimately contributing to better outcomes. 

Through health monitoring apps, wearable devices, and virtual assistants, individuals gain access to real-time health data and personalised recommendations. Patients are encouraged to be active participants in their healthcare journey, making informed choices, tracking progress, and collaborating with healthcare providers. This collaborative approach enhances patient satisfaction and bolsters adherence to treatment plans, ultimately contributing to improved outcomes. 

Experts from the healthcare sector delved into the evolving role of AI in healthcare, particularly in cancer detection and prevention. Dr Prof U S Vishal Rao, Director, Head Neck Surgical Oncology & Robotic Surgery & Dean, Centre of Academics & Research, HealthCare Global (HCG) Cancer Centre, Mr. Rajesh Khanna, CBO, Lupin Digital Health, Shivtosh Kumar, Co-Founder, SugarFit and Mr Siva Teja, Kakileti, Director, Principal Research Scientist, Founding Team Member, Niramai Health Analytix, shared their insights during a panel discussion. 

Dr Vishal emphasised that while AI holds promise, data reliability remains a significant challenge in India. The quality of healthcare data, especially longitudinal patient data, is essential for building reliable algorithms. Insufficient data standards hinder the development of effective AI solutions. 

Whereas, Shiva highlighted the importance of data accuracy in training AI models. He stressed that AI models in cancer diagnosis heavily rely on accurate ground truth data, such as histopathology or biopsy results. Combining multiple imaging modalities and radiomics can enhance accuracy, providing doctors with valuable insights. 

Rajesh Khanna shared an intriguing case of a 33-year-old heart attack survivor who maintained a fit lifestyle but succumbed to excessive stress. He highlighted the critical role of sleep and its impact on overall health, underscoring the need for improved awareness and tracking. 

AI, however, has the ability to forecast cardiac events as well. For example, AI can analyse ECGs and accurately determine a patient's gender and age. The next step is to use ECG data from childhood to forecast when a person is in danger of a cardiac incident in the future. Wearable gadgets are crucial to AI-driven preventive wellbeing. These devices continuously monitor vital signs, providing real-time data that can assist consumers in making educated health and lifestyle decisions. 

Patients can expect more accurate diagnoses, personalised treatment regimens, and increased engagement in their healthcare decisions as AI technologies improve. 

This seismic change has the potential not only to improve patient outcomes but also to reshape the future of healthcare delivery. Data dependability, particularly in India, is a challenge, as are the ethical implications. The potential of artificial intelligence in healthcare is transformational, but tackling data reliability and ensuring ethical healthcare delivery will be critical to its full realisation.