Information Technology

Self-Supervised Graph Learning With Hyperbolic Embedding for Temporal Health Event Prediction.

Electronic health records (EHRs) have been heavily used in modern healthcare systems for recording patients' admission information to health facilities. Many data-driven approaches employ temporal features in EHR for predicting specific diseases, readmission times, and diagnoses of patients. However, most existing predictive models cannot fully utilize EHR data, due to an inherent lack of labels i...

Novel architecture for gated recurrent unit autoencoder trained on time series from electronic health records enables detection of ICU patient subgroups.

Electronic health records (EHRs) are used in hospitals to store diagnoses, clinician notes, examinations, lab results, and interventions for each patient. Grouping patients into distinct subsets, for example, via clustering, may enable the discovery of unknown disease patterns or comorbidities, which could eventually lead to better treatment through personalized medicine. Patient data derived from...

Ethics Principles for Artificial Intelligence-Based Telemedicine for Public Health.

The use of artificial intelligence (AI) in the field of telemedicine has grown exponentially over the past decade, along with the adoption of AI-based...

Securing Multimedia Using a Deep Learning Based Chaotic Logistic Map.

Telemedicine and online consultations with doctors has become very popular during the pandemic and involves the transmission of medical data through t...

Protein Design Using Physics Informed Neural Networks.

The inverse protein folding problem, also known as protein sequence design, seeks to predict an amino acid sequence that folds into a specific structu...

The Environmental Conditions, Treatments, and Exposures Ontology (ECTO): connecting toxicology and exposure to human health and beyond.

BACKGROUND: Evaluating the impact of environmental exposures on organism health is a key goal of modern biomedicine and is critically important in an ...

Deep-learning-based prognostic modeling for incident heart failure in patients with diabetes using electronic health records: A retrospective cohort study.

Patients with type 2 diabetes mellitus (T2DM) have more than twice the risk of developing heart failure (HF) compared to patients without diabetes. Th...

DR.BENCH: Diagnostic Reasoning Benchmark for Clinical Natural Language Processing.

The meaningful use of electronic health records (EHR) continues to progress in the digital era with clinical decision support systems augmented by art...

Multiclass skin lesion localization and classification using deep learning based features fusion and selection framework for smart healthcare.

BACKGROUND: The idea of smart healthcare has gradually gained attention as a result of the information technology industry's rapid development. Smart ...

Knowledge Graph Embeddings for ICU readmission prediction.

BACKGROUND: Intensive Care Unit (ICU) readmissions represent both a health risk for patients,with increased mortality rates and overall health deterio...

[Digitalization in healthcare: today and in the future].

Although Germany continues to struggle with the digital transformation of healthcare, there is reason for optimism. The political will to improve heal...

Deep-Learning and Device-Assisted Enteroscopy: Automatic Panendoscopic Detection of Ulcers and Erosions.

: Device-assisted enteroscopy (DAE) has a significant role in approaching enteric lesions. Endoscopic observation of ulcers or erosions is frequent an...

Composition of Hybrid Deep Learning Model and Feature Optimization for Intrusion Detection System.

Recently, with the massive growth of IoT devices, the attack surfaces have also intensified. Thus, cybersecurity has become a critical component to pr...

Digital health-high tech or high touch?

Digital transformation in medicine refers to the implementation of information technology-driven developments in the healthcare system and their impac...

Multimodal Data Matters: Language Model Pre-Training Over Structured and Unstructured Electronic Health Records.

As two important textual modalities in electronic health records (EHR), both structured data (clinical codes) and unstructured data (clinical narrativ...

Considerations for Creating a Restricted Data Environment with Complete Primary Care Electronic Medical Record Data.

Background: Historically, primary care databases have been limited to subsets of the full electronic medical record (EMR) data to maintain privacy. Wi...

A Deep-Learning-Based Collaborative Edge-Cloud Telemedicine System for Retinopathy of Prematurity.

Retinopathy of prematurity is an ophthalmic disease with a very high blindness rate. With its increasing incidence year by year, its timely diagnosis ...

From big data to better patient outcomes.

Among medical specialties, laboratory medicine is the largest producer of structured data and must play a crucial role for the efficient and safe impl...

Proposed algorithm for smart grid DDoS detection based on deep learning.

The Smart Grid's objective is to increase the electric grid's dependability, security, and efficiency through extensive digital information and contro...

MR-KPA: medication recommendation by combining knowledge-enhanced pre-training with a deep adversarial network.

BACKGROUND: Medication recommendation based on electronic medical record (EMR) is a research hot spot in smart healthcare. For developing computationa...