Start learning 50% faster. Sign in now
Predictive analytics in healthcare primarily aims to forecast patient outcomes, such as disease progression, recovery times, and potential complications. By leveraging data, including medical history, genetic information, lifestyle factors, and treatment responses, predictive models can offer personalized treatment plans and allow healthcare providers to intervene before conditions worsen. The goal is to provide timely interventions that improve patient outcomes, reduce unnecessary hospital admissions, and optimize recovery paths. While classification and resource optimization are important, the central aim in healthcare analytics remains the prediction of individual patient trajectories for better care management. Why Other Options Are Incorrect: • A: Classifying patients into risk categories is a part of predictive analytics, but the main objective is to predict specific patient outcomes based on data, rather than just categorization. • C: While predicting healthcare costs is an important aspect of healthcare analytics, it does not directly contribute to improving individual patient care. • D: Optimizing hospital resource allocation is crucial for efficiency, but predictive analytics in healthcare is more concerned with patient-specific outcomes rather than logistical or resource issues. • E: Analyzing historical data for research purposes can help improve healthcare, but predictive analytics focuses on future patient outcomes rather than retrospective research.
The population census is a Union subject under which of the following Articles of India Constitution?
Which entity recently launched the second international banking centre in Chennai to cater to the financial needs of global Indians?
Which state launched the Gemini-powered agricultural network in collaboration with Google Cloud?
Memorandum of Understanding (MoU) was signed between NIELIT and ITI Egypt to enhance workforce skills, promote employment, address skill gaps, and foste...