Research Insights

This section focuses on recent global studies and discoveries in the various fields of healthcare.

Eeg Classification of Traumatic Brain Injury and Stroke From a Nonspecific Population Using Neural Networks

Traumatic Brain Injury TBI and stroke are devastating neurological conditions that affect hundreds of people daily Unfortunately detecting TBI and stroke without specific imaging techniques or access to a hospital often proves difficult

A Comprehensive Wireless Neurological and Cardiopulmonary Monitoring Platform for Pediatrics

Neurodevelopment in the first years of life is a critical time window during which milestones that define an individuals functional potential are achieved Comprehensive multimodal neurodevelopmental monitoring

Increasing Efficiency of Svmp+ for Handling Missing Values in Healthcare Prediction

Missing data presents a challenge for machine learning applications specifically when utilizing electronic health records to develop clinical decision support systems The lack of these values is due in part to the complex nature of clinical data in which the content is personalized to each patient

A Multivariate Genome-wide Association Study of Psycho-cardiometabolic Multimorbidity

Coronary artery disease CAD type diabetes TD and depression are among the leading causes of chronic morbidity and mortality worldwide Epidemiological studies indicate a substantial degree of multimorbidity which may be explained by shared genetic influences

Impacts of Antipsychotic Medication Prescribing Practices in Critically Ill Adult Patients on Health Resource Utilization and New Psychoactive Medication Prescriptions

Antipsychotic medications are commonly prescribed to critically ill adult patients and initiation of new antipsychotic prescriptions in the intensive care unit ICU increases the proportion of patients discharged home on antipsychotics

Autoprognosis 2.0: Democratizing Diagnostic and Prognostic Modeling in Healthcare With Automated Machine Learning

Diagnostic and prognostic models are increasingly important in medicine and inform many clinical decisions Recently machine learning approaches have shown improvement over conventional modeling techniques by better capturing complex interactions between patient covariates in a datadriven manner

Major trauma presentations and patient outcomes in English hospitals during the COVID-19 pandemic: An observational cohort study

Singlecentre studies suggest that successive Coronavirus Disease COVIDrelated lockdown restrictions in England may have led to significant changes in the characteristics of major trauma patients

Functional Screening Of Lysosomal Storage Disorder Genes Identifies Modifiers Of Alpha-synuclein Neurotoxicity

SHeterozygous variants in the glucocerebrosidase GBA gene are common and potent risk factors for Parkinsons disease PD GBA also causes the autosomal recessive lysosomal storage disorder LSD Gaucher disease

Treatment Effect Modification Due To Comorbidity: Individual Participant Data Meta-analyses Of 120 Randomised Controlled Trials

Multimorbidity the presence of or more longterm conditions is a global clinical and public health priority Most people with a given longterm condition also have comorbidities referring to additional longterm conditions in the context of an index condition

Development Of A Dynamic Prediction Model For Unplanned Icu Admission And Mortality In Hospitalized Patients

Frequent assessment of the severity of illness for hospitalized patients is essential in clinical settings to prevent outcomes such as inhospital mortality and unplanned admission to the intensive care unit ICU Classical severity scores have been developed typically using relatively few patient features