Objectives: This survey aims at reviewing the literature related to Clinical Information
Systems (CIS), Hospital Information Systems (HIS), Electronic Health Record (EHR) …

Introduction The authors of this work propose an unsupervised machine learning model that
has the ability to identify real-world latent infectious diseases by mining social media data. In …

The multi-modal and unstructured nature of observational data in Electronic Health Records
(EHR) is currently a significant obstacle for the application of machine learning towards risk …

Biomedical event trigger detection is a heated research topic since its important role in
biomedical event extraction. Previous studies show that syntactic features are very crucial for …

Nowadays, large amounts of data are generated in the medical domain. Various
physiological signals generated from different organs can be recorded to extract interesting …

Healthcare professionals have long envisioned using the enormous processing powers of
computers to discover new facts and medical knowledge locked inside electronic health …

There is an urgent need to develop an efficient system for accurate recognition of epileptic
seizure type that could play a significant role in reducing the adversial effects of the disease …

Outlier detection is an important problem occurring in a wide range of areas. Outliers are the
outcome of fraudulent behaviour, mechanical faults, human error, or simply natural …

This article describes a detailed methodology for the A-phase classification of the cyclic
alternating patterns (CAPs) present in sleep electroencephalography (EEG). CAPs are a …

Книга посвящена актуальной проблеме своевременной диагностики двигательных
расстройств в виде диспраксии, неудовлетворительной мелкой моторики и статико …