Diseases are accountable for inducing chronic symptoms, drastic complications and severe manifestations and have been the leading causes of deaths in India.
There are vital triggers and risk factors for unfavorable advancement of the diseases such as age, gender, BMI, comorbidities, history, ESR, symptoms, imaging factors, hemoglobin and others.
Nowadays, differential diagnosis and symptomatic treatment pattern is carried out as there is dearth and lack of definite and specific diagnostic and therapeutic criteria and regime including factors, targets and markers.
Complications and recurrence can also occur after therapy leading to extended hospital stays, adverse clinical outcomes and higher medical costs that need to be accurately evaluated.
Hence, a need arises for management and early diagnosis of diseases to reduce deferred identification, gradual adverse effect on quality of life and morbidity. It necessitates the identification of vital and essential risk factors for the development of disease to improve prognosis, early diagnosis, precise treatment and complications after therapy.
In 2023, Government of India has launched various schemes to eliminate life threatening diseases focusing on prediction and early detection and incorporation of Artificial Intelligence (AI).
Inclusion of AI in healthcare for early diagnosis and prediction is the need of the hour as quoted by reputed healthcare experts in India.
In the current scenario, the progressive utilization of AI and Machine Learning (ML) techniques is being implemented for developing predictive models for prognosis, risk assessment, early diagnosis, personalized treatment and disease recurrence.
AI represents the methods imitating human intelligence. ML is a subset of AI that focuses on creating algorithms for assisting computers to learn and execute definite tasks by assembling data patterns. ML uses regression and classification creating training and testing data and generating computerised algorithms that learn from the target attribute of training data and aid in producing outcome of testing data.
