Results 171 to 180 of about 275,080 (334)
Data science approaches have been increasingly implemented in healthcare big data to evaluate the safety and effectiveness of drugs. Association discovery is a data mining approach that finds potentially associated elements in high‐dimensional data. We present a novel implementation of the association discovery approach in longitudinal healthcare data ...
George S. Q. Tan+6 more
wiley +1 more source
Differentiation of two genetically specific types of depression by the response to antidepressant drugs. [PDF]
C. M. B. Pare, Jennifer W. Mack
openalex +1 more source
Overview of the implemented pharmacogenomics (PGx) process in clinical routine at the Robert Bosch Hospital: from patient enrollment via the hospital information system, DNA detection using a customized TaqMan OpenArray panel and qPCR for CNV assessment, to clinical translation of genotyping results into PGx guideline‐based recommendations using a ...
Roman Tremmel+13 more
wiley +1 more source
Post‐Mortem Identification and Toxicological Findings of Fluetonitazepyne and Isotonitazepyne
In early 2025, five death cases in Finland tested positive for fluetonitazepyne and one for isotonitazepyne in urine drug screening. A peak corresponding to O‐dealkylated fluetonitazepyne, the 4‐OH‐nitazepyne metabolite, was present in all fluetonitazepyne‐positive urine samples and was later used in the identification of isotonitazepynein one fatal ...
Pirkko Kriikku+3 more
wiley +1 more source
A quantitative study of the anticholinergic action of several tricyclic antidepressants on the rat isolated fundal strip [PDF]
J. P. Atkinson, H. Ladinsky
openalex +1 more source
ABSTRACT Objective Telehealth services have become part of many eating disorder (ED) treatment settings; yet, few studies have examined the effectiveness of family‐based treatment (FBT) delivered via telehealth. This study compared in‐person and telehealth FBT in rates of weight restoration, treatment completion, and metrics of treatment progress, and ...
Catherine R. Drury+20 more
wiley +1 more source
Applying Machine Learning to Predict Complex Clinical Course in Youth With Eating Disorders
ABSTRACT Objective To compare the predictive performance of supervised machine learning models to logistic regression in identifying youth with eating disorders at risk of a complex clinical course based on clinical characteristics from the first treatment episode.
Stephanie Ryall+3 more
wiley +1 more source