Intelligent Cognitive Clinician

In healthcare delivery, patients are diagnosed, medical tests are taken to be analysed to provide better treatment and test results are based on providing treatment to patients. Drug recommendation systems are widely used by medical professionals as medico-assisted systems, but recommendations are mute to surgeries or therapies. This paper presents a novel approach to designing an intelligent cognitive clinician (IC2) that diagnoses the patient using NLP algorithms for a speech of the patient to text translation or textual data for symptoms extraction and predict the disease and possible medical tests to be taken. Once the test results are available, the system recommends the drugs, therapies, or surgeries and patient feedback improves the treatment recommendation. So, IC2 is a drug, surgery, or therapy recommendation system based on symptoms, test results, and patient feedback.