A scoping review shows machine learning models may help predict response to biologic and targeted synthetic DMARDs in ...
Through machine learning-based feature selection, the team identified 13 core immune-related genes (IL18BP, RSAD2, G0S2, SIGLEC1, SFRP2, IFI44L, ISG20, IFIT1, OLR1, SAMHD1, HK3, PTAFR, CSF1) that play ...
Researchers with City of Hope and Memorial Sloan Kettering (MSK) Cancer Center have created a tool that uses machine learning to assess a non-Hodgkin lymphoma (NHL) patient's likely response to ...
Predictive Model of Objective Response to Nivolumab Monotherapy for Advanced Renal Cell Carcinoma by Machine Learning Using Genetic and Clinical Data: The SNiP-RCC Study The use of real-world data ...
Experts are increasingly turning to machine learning to predict antibiotic resistance in pathogens. With its help, resistance ...
Researchers with City of Hope and MSK have created a tool that uses machine learning to assess a non-Hodgkin lymphoma (NHL) patient’s likely response to chimeric antigen receptor (CAR) T cell therapy ...
Experts are increasingly turning to machine learning to predict antibiotic resistance. The results should be treated with ...
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