Journal of infection in developing countries
32045381
Streptococcus gallolyticus (S. gallolyticus) bacteremia is commonly associated with endocarditis and diseases of gastrointestinal tract, especially with colorectal carcinoma. On the other side, it is rarely connected to liver disease, especially alco...
Research in the domain of psychopathology has been hindered by hidden variables-variables that are important to understanding and treating psychopathological illnesses but are unmeasured. Recent methodological advances in machine learning have culmin...
BACKGROUND: In the United States, 13% of adults are estimated to have alcohol use disorder (AUD). Most studies examining the neurobiology of AUD treat individuals with this disorder as a homogeneous group; however, the theories of the neurocircuitry ...
BACKGROUND AND OBJECTIVES: Clinical staff providing addiction treatment predict patient outcome poorly. Prognoses based on linear statistics are rarely replicated. Addiction is a complex non-linear behavior. Incorporating non-linear models, Machine L...
Biological psychiatry. Cognitive neuroscience and neuroimaging
30982583
The incidence of alcohol use disorder (AUD) in human immunodeficiency virus (HIV) infection is twice that of the rest of the population. This study documents complex radiologically identified, neuroanatomical effects of AUD+HIV comorbidity by identif...
Salivary miRNA can be easily accessible biomarkers of alcohol dependence (AD). The miRNA transcriptome in the saliva of 56 African-Americans (AAs; 28 AD patients/28 controls) and 64 European-Americans (EAs; 32 AD patients/32 controls) was profiled ...
BACKGROUND: Current modes of identifying alcohol misuse in hospitalized patients rely on self-report questionnaires and diagnostic codes that have limitations, including low sensitivity. Information in the clinical notes of the electronic health reco...
BACKGROUND AND AIMS: Clinical staff are typically poor at predicting alcohol dependence treatment outcomes. Machine learning (ML) offers the potential to model complex clinical data more effectively. This study tested the predictive accuracy of ML al...
European neuropsychopharmacology : the journal of the European College of Neuropsychopharmacology
32418843
At present, risk assessment for alcohol withdrawal syndrome relies on clinical judgment. Our aim was to develop accurate machine learning tools to predict alcohol withdrawal outcomes at the individual subject level using information easily attainable...