Natural Language Processing in Healthcare: A Predictive Model for Disease Diagnosis

During the pandemic period medical healthcare is needed but modern life presents difficulties in identifying typical illnesses. Modern Artificial Intelligence systems with Natural Language Processing features allow people to recognize early disease signs by recognizing subtle symptoms leading to less expensive AI diagnostic outcomes. Symptom processing in the model begins with text pre-processing along with Count Vectorizer vectorization prior to applying Multinomial Naïve Bayes classification. The diagnostic process runs more smoothly while the first disease detection system expands its scope by applying this method. Research demonstrates that Natural Language Processing (NLP)-powered Artificial Intelligence (AI) models involve healthcare diagnosis operations and medical institution access development. Medical systems receive a positive evolution through AI advancements which enables early disease detection to decrease health risks and achieve better patient outcomes and mortality reduction.