Cleveland Clinic and IBM researchers are using quantum computing to tackle one of the most challenging problems in ...
Internal iliac and obturator lymph nodes are common sites of metastasis in rectal cancer. This study developed a machine learning (ML) model using clinical data to predict lymph node metastasis and ...
Sepsis is one of the most common and lethal syndromes encountered in intensive care units (ICUs), and acute respiratory failure (ARF) represents one of its most critical complications. Once ...
Cost-Effectiveness of Maintaining Higher Stem-Cell Collection Thresholds in the Chimeric Antigen Receptor T-Cell Era for Multiple Myeloma Predicting severe adverse events (SAEs) in oncology is ...
A recent study, “Picking Winners in Factorland: A Machine Learning Approach to Predicting Factor Returns,” set out to answer a critical question: Can machine learning techniques improve the prediction ...
Overall survival is heterogeneous after nephrectomy for non-metastatic RCC, but new models may aid prognostication. A new model, based on factors identified via machine learning, predicts overall ...
A machine learning model analyzing CpG-based DNA methylation accurately predicted the origin of many different cancer types in patients with cancers of unknown primary (CUP), according to research ...
Bottom line: 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), ...
Image courtesy by QUE.com For decades, the search for room-temperature superconductors has been one of physics' most tantalizing and ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results