Impact of artificial intelligence on healthcare


  • Joyal Francis KMCT Medical Colleges, Kozhikode, Kerala, India
  • Jithun V. Varghese Apollo Adlux Hospital Ernakulam, Kerala, India
  • Arppana Thomas KMCT Medical Colleges, Kozhikode, Kerala, India



Artificial intelligence, Psychiatry, Cancer research, Cardiology, Dermatology, Ophthalmology, Surgery, Gastroenterology


Artificial intelligence (AI) is revolutionizing various medical practices, making them more affordable, efficient, and faster. Its uses range from diagnosis, management, monitoring, and outcome forecasting to individualized care. AI technology in psychotherapy can help conditions such as dementia, autism spectrum disorder, and schizophrenia, and due to its image processing, segmentation, and reconstruction capabilities, AI has found applications in a wide range of fields, including the diagnosis of cancer, the treatment of skin lesions, the prediction of metastasis of malignancies, the staging of lung nodules, the identification of COVID-19, and the classification of thyroid tissue. In addition to histopathology images, imaging techniques such as CT, MRI, mammography, fundus imaging, and even photographs can be used to diagnose patients. In this study, we tried to address the current status and future scope of AI to bring substantial upliftment to health care. It is anticipated that human intelligence and AI will coexist in the field of medicine in the future. Modern smart devices collect a huge amount of data that can be used for disease prevention, health promotion, monitoring, and diagnosis in medicine. AI will improve as long as we train them. With the development of sophisticated machinery, robotics, and virtual reality, the healthcare industry is likely to undergo revolutionary changes. AI has performance on par with that of human experts, with the added benefits of scalability and automation. Before becoming fully autonomous in nature, AI systems might need tight supervision due to their lack of training, limited knowledge, and limited flexibility in clinical settings.


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