Results 161 to 170 of about 611,997 (371)
Arquivo Brasileiro de Medicina Veterinária e ZootecniaPregnancy can cause several physiologic changes in mares, including modifications in cardiac output and heart positioning. Therefore, these changes could influence electrocardiographic parameters in various stages of pregnancy.
G. Casa +8 more
doaj +1 more source
AGING MEDICINE, EarlyView.This study demonstrated a significant positive correlation between AIP and the prevalence and incidence of hypertension in a nationwide representative middle‐aged and elderly population in China. ABSTRACT Objectives Atherosclerosis is the underlying pathology of cardiovascular disease (CVD), including hypertension.
Xiao Chen +3 more
wiley +1 more source
Retracted: A Comprehensive Review on Metabolic Syndrome
Cardiology Research and Practice, 2019 Cardiology Research and Practice
doaj +1 more source
Telemedicine devices in internal medicine and neurology
Journal of Education, Health and Sport, 2019 Introduction Monitoring of patients systems remotely with feedback send to physician and patient could be applied in many fields of medicine. Telemedicine could presumably lead to improvement of patients care and treatment both in chronic conditions and
Mateusz Domeracki, Monika Prylińska
doaj
Fine-Tuning LLMs on Small Medical Datasets: Text Classification and Normalization Effectiveness on Cardiology reports and Discharge records [PDF]
arXivWe investigate the effectiveness of fine-tuning large language models (LLMs) on small medical datasets for text classification and named entity recognition tasks. Using a German cardiology report dataset and the i2b2 Smoking Challenge dataset, we demonstrate that fine-tuning small LLMs locally on limited training data can improve performance achieving ...
arxiv
Evaluating the Efficacy of Vectocardiographic and ECG Parameters for Efficient Tertiary Cardiology Care Allocation Using Decision Tree Analysis [PDF]
arXivUse real word data to evaluate the performance of the electrocardiographic markers of GEH as features in a machine learning model with Standard ECG features and Risk Factors in Predicting Outcome of patients in a population referred to a tertiary cardiology hospital.
arxiv