A machine learning model that analyzes patient demographics, electronic health record data, and routine blood test results predicted a patient's risk of hepatocellular carcinoma (HCC), the most common ...
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A machine learning model may enable liver cancer risk prediction with routine clinical information
A machine learning model that analyzes patient demographics, electronic health record data, and routine blood test results ...
Long-term lithium therapy remains the most effective maintenance treatment for bipolar disorder, yet it poses a significant ...
Machine learning algorithms help computers analyse large datasets and make accurate predictions automatically.Classic models ...
Abstract: Machine learning has been successfully applied to drug combination prediction in recent years. However, in some situations, the class imbalance problem still shows highly negative impacts on ...
A decision tree regression system incorporates a set of if-then rules to predict a single numeric value. Decision tree regression is rarely used by itself because it overfits the training data, and so ...
Kidney cancer is a highly heterogeneous oncologic disease with historically poor prognosis. Precise assessment of the risk of distal metastasis can facilitate risk stratification and improve prognosis ...
Acute Type A aortic dissection (ATAAD) is characterized by acute onset and rapid progression, with aortic rupture due to dissection extension being the primary lethal mechanism. Timely identification ...
1 School of Taxation and Public Administration, Shanghai Lixin University of Accounting and Finance, Shanghai, China. 2 School of Business, Computing and Social Sciences, University of Gloucestershire ...
Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Decision-making during the early stages of research and development (R&D) should be ...
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