Information Technology

Sustainability and minimization of carbon footprint in ophthalmology: what can we change in the outpatient clinic routine?

Ophthalmological care has significant potential to consume energy, utilize resources, and generate waste, thereby contributing to a substantial portion of greenhouse gas emissions. Although awareness is increasing, many clinicians still lack knowledge about the actions that can be taken to address climate change. The literature about sustainability in ophthalmology has focused on surgery and the o...

Can we identify individuals at risk to develop multiple myeloma? A machine learning-based predictive model.

Multiple myeloma evolves unnoticed over years, and when diagnosed, organ damage is common. Electronic health records (EHR) can help in developing predictive models identifying 'healthy' people at risk. MM patients from Clalit Health Services (2002-2019) were matched with healthy controls. Stage I: EHR from 5 years prior to MM diagnosis were reviewed and >200 parameters were compared (patients vs. ...

A scoping review of self-supervised representation learning for clinical decision making using EHR categorical data.

The widespread adoption of Electronic Health Records (EHRs) and deep learning, particularly through Self-Supervised Representation Learning (SSRL) for...

A Post-Quantum Blockchain and Autonomous AI-Enabled Scheme for Secure Healthcare Information Exchange.

Secure healthcare information exchange (HIE) is critical to improving medical services, enabling data interoperability, and ensuring patient privacy. ...

Pretrained patient trajectories for adverse drug event prediction using common data model-based electronic health records.

BACKGROUND: Pretraining electronic health record (EHR) data using language models has enhanced performance across various medical tasks. Despite the p...

Digital Therapeutics for Cognitive Impairment: Exploring Innovations, Challenges, and Future Prospects.

Recent advancements in cognitive neuroscience and digital technology have significantly accelerated the adoption of digital therapeutics for cognitive...

MPSE identifies newborns for whole genome sequencing within 48 h of NICU admission.

Identifying critically ill newborns who will benefit from whole genome sequencing (WGS) is difficult and time-consuming due to complex eligibility cri...

Empirical evaluation of artificial intelligence distillation techniques for ascertaining cancer outcomes from electronic health records.

Phenotypic information for cancer research is embedded in unstructured electronic health records (EHR), requiring effort to extract. Deep learning mod...

Early Alzheimer's Detection Through Voice Analysis: Harnessing Locally Deployable LLMs via , a privacy-preserving diagnostic system.

Diagnosing Alzheimer's Disease (AD) early and cost-effectively is crucial. Recent advancements in Large Language Models (LLMs) like ChatGPT have made ...

Enhancing Healthcare Data Integration: A Machine Learning Approach to Harmonizing Laboratory Labels.

Variations in laboratory test names across healthcare systems-stemming from inconsistent terminologies, abbreviations, misspellings, and assay vendors...

Determining the Importance of Clinical Modalities for NeuroDegenerative Disorders and Risk of Patient Injury Using Machine Learning and Survival Analysis.

Falls among the elderly and especially those with NeuroDegenerative Disorders (NDD) reduces life expectancy. The purpose of this study is to explore t...

Machine reading and recovery of colors for hemoglobin-related bioassays and bioimaging.

Despite advances in machine learning and computer vision for biomedical imaging, machine reading and learning of colors remain underexplored. Color co...

Trajectory-Ordered Objectives for Self-Supervised Representation Learning of Temporal Healthcare Data Using Transformers: Model Development and Evaluation Study.

BACKGROUND: The growing availability of electronic health records (EHRs) presents an opportunity to enhance patient care by uncovering hidden health r...

Closing the AI generalisation gap by adjusting for dermatology condition distribution differences across clinical settings.

BACKGROUND: Generalisation of artificial intelligence (AI) models to a new setting is challenging. In this study, we seek to understand the robustness...

Research on insider threat detection based on personalized federated learning and behavior log analysis.

As the cybersecurity landscape becomes increasingly challenging, insider threat detection has emerged as a critical research area. Traditional methods...

Detecting cyber attacks in vehicle networks using improved LSTM based optimization methodology.

The growing adoption of intelligent transportation systems and connected vehicle networks has raised significant cybersecurity concerns due to their v...

Revolutionizing diabetes care: the role of artificial intelligence in prevention, diagnosis, and patient care.

UNLABELLED: Millions of people worldwide have diabetes, a disease that is becoming more common and has substantial socioeconomic costs. Artificial int...

Distributed denial of service (DDoS) classification based on random forest model with backward elimination algorithm and grid search algorithm.

Distributed Denial of Service (DDoS) attacks pose significant threats to network security, disrupting critical services by overwhelming targeted syste...

Advancing Musculoskeletal Care Using AI and Digital Health Applications: A Review of Commercial Solutions.

Artificial intelligence (AI) and digital health (DH) solutions are reshaping musculoskeletal (MSK) care across diagnostics, treatment planning, workfl...

An Explainable Multimodal Artificial Intelligence Model Integrating Histopathological Microenvironment and EHR Phenotypes for Germline Genetic Testing in Breast Cancer.

Genetic testing for pathogenic germline variants is critical for the personalized management of high-risk breast cancers, guiding targeted therapies a...