Sentence examples for clinical label from inspiring English sources

We presented the HHCRF, an array-CGH analysis method for jointly classifying tumors by clinical label, extracting copy number profiles, and identifying clinically relevant genes.

We considered convenient, twenty years later, to realize an updating of the developed aspects by leaving a clinical label which, without being paradigmatic, illustrate the topic.

Though many pain specialists have established clinical procedures for diagnosing fibromyalgia, the clinical label does not explain what is happening neurologically and it does not reflect the full individuality of patients' suffering.

By building a generative model with an HMM, we estimate the likelihood of the input features of rs-fMRI as belonging to the corresponding status, i.e., MCI or normal healthy control, based on which we identify the clinical label of a testing subject.

Persistent β-cell function outside the honeymoon period in those with clinical label of type 1 diabetes was used to identify candidates for MODY testing.

We reviewed all patients who had a suggestion of autoimmune hepatitis on their biopsies and who were ever given a clinical label of Autoimmune Hepatitis.

Some psychiatrists argue C should never have had to go to court, and that doctors remain over-keen to give clinical labels to behaviour that is deeply unconventional but no more.

Assessment of limb apraxia is still suffering from Liepmann's legacy and performance in gesture-processing tests is generally rendered by classifying patients' profile according to the classic clinical labels of ideomotor and ideational apraxia.

We don't put clinical labels on them at this point but we can actually present some more advanced information to clinicians today," he adds.

Temporomandibular disorders (TMD), musculoskeletal disorders of the masticatory system, are common clinical labels for pain in the orofacial area.

These features are then ranked according to their Pearson correlation with respect to the clinical labels, and are further sieved to select the most discriminant subset of features using an SVM-based feature selection algorithm.