Improving Clinical Decision Making with AI


The Artificial intelligence are methods that particularly machine learning and reinforcement learning and deep learning are uniquely suited to addressing both types of data and emerging the healthcare questions. The AI can help clinicians with the complex task of stratifying and patients by risk for surgery and identifying those most at risk of imminent decompensation and evaluating many small outcomes to optimize overall the patient outcomes. The involvement of physicians in model and development and physician training in this area will mean a further paradigm shift in the medical education. The complexity of AI methods are varies widely and which in turn affects the ease with which the clinician can understand and interpret the results. The Doctors often use decision trees as tools and they are actually connected to the original tree and are therefore somewhat static. The deep learning models such as convolutional neural networks are more difficult to interpret and can complicate causality. The development of such models requires the active participation of the clinicians. The Large healthcare systems recognized the importance of this data early on and created data and repositories that are now used both for research purposes and to guide evidence and based clinical practice. These data warehouses contain not only EHR data, but are often powered by claims data, image data and omics data and data collected from a handheld device which home vital signs monitoring and physical activity status are from smartphones and watches.

Greater Diagnostic Accuracy

The One of the most critical issues facing healthcare professionals and healthcare organizations is the risk of the patient misdiagnosis. The misdiagnosis can not only be costly but deadly in medical industry. The Research shows that misdiagnosis directly contributes to higher mortality and longer hospital stays and particularly among patients in the emergency room. The AI can help diagnose life and threatening conditions in patients early and notify doctors in time. The patients can get immediate help. It aims to help the doctors identify early signs of sepsis and one of the leading causes of death in hospitals worldwide. The Sepsis Watch can identify patients who are the moderate to high risk and those who already meet the criteria for developing an infection.

Make More Informed Decisions

The AI can help physicians make more informed decisions in very less time. The AI and powered CDSS can suggest best practices for post and surgical discharge and recommend medications and dosages and order regular assessments and follow the up tests to ensure optimal patient care. It can help patients make more decisions about alternative treatments or rehabilitation and can play an important role in reducing the medical errors. The AI can help reduce medical error in decision and making by offering a support system for healthcare and professionals to review their decisions or request a recommendation.

Help and Support from Doctors

The AI can also alleviate the common problem of stress and related clinical burnout that occurs when the clinicians are made aware on a daily basis of the wide range of potential complications to patient outcomes.

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