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FREMONT, CA: Researchers are developing solutions to integrate artificial intelligence (AI) in the clinical setting. AI is relevant in medical applications like disease prediction, diagnosis, and prognosis. Data from patients in medical images, texts, and electronic records provide enough information for machine learning (ML) to undertake automation certain functions with accuracy and reliability.
AI is applied in the following areas:
Cardiology: Cardiovascular diseases is a major cause of morbidity and mortality, globally. It is an expensive treatment that requires expensive treatments. AI in cardiology improves prediction and diagnosis of cardiac events. AI can personalize medical care for patients. ML can improve given the vast records of data available. It assists cardiologists in choosing the right treatment by analyzing relevant data.
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Neurology: In neurology AI detects and improves the management of neurological conditions like strokes. ML algorithms identify factors leading to a stroke and its reoccurrence. ML predicts the occurace of ischemic stroke by studying collateral circulations. Algorithms can accurately determine a patient’s degree of collateral flow. It is an important consideration reperfusion procedures.
Oncology: AI assists with collecting and analyzing data, matches it with prior information and expertise to choose diagnostic treatment plans. Formal methods (FM) has a precision of 100 percent in detecting the metastases of liver which is undetectable using traditional methods.
Hematology: Researchers are interest in benign and malign hematology settings to apply AI in the diagnosis and prognosis of the forms of leukemia, lymphoma, anemias, and genetic blood disorders. Recently, researchers have employed algorithms using multilayer perceptron ANN predict the overall survival of patients with mantle cell lymphoma (MCL). The AI tool identified the five genes that contributed to mortality.
Nephrology: AI is assisting in investigations for the early detection and prediction of acute kidney injury (AKI). It helps clinicians intervene in preventing permanent kidney damage. Early intervention can leave patients with a time window that would enable early treatment and improve outcomes.
Gastroenterology and Hepatology: Researchers are developing better assessments for celiac disease that has negative connotatos despite maintaining a gluten-free diet. There is a higher chances for gluten allergy to have adverse reactions such as pancreatic exocrine dysfunction, microscopic colitis, and enteropathy-associated lymphoma. ML algorithms enable precise endomysial autoantibody (EmA) test to diagnose celiac disease.
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