Practice Management

Information Technology

Latest AI and machine learning research in information technology for healthcare professionals.

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Clinical implementation of AI-based screening for risk for opioid use disorder in hospitalized adults.

Adults with opioid use disorder (OUD) are at increased risk for opioid-related complications and rep...

A Quantitative Study of Factors Influencing Myasthenia Gravis Telehealth Examination Score.

INTRODUCTION/AIMS: The adoption of telemedicine is generally considered as advantageous for patients...

Multimodal learning-based speech enhancement and separation, recent innovations, new horizons, challenges and real-world applications.

With the increasing global prevalence of disabling hearing loss, speech enhancement technologies hav...

Leveraging large language models to mimic domain expert labeling in unstructured text-based electronic healthcare records in non-english languages.

BACKGROUND: The integration of big data and artificial intelligence (AI) in healthcare, particularly...

The interpretable machine learning model for depression associated with heavy metals via EMR mining method.

Limited research exists on the association between depression and heavy metal exposure. This study a...

Optimal cybersecurity framework for smart water system: Detection, localization and severity assessment.

The digital transformation of water distribution systems has streamlined monitoring and control thro...

DeePMD-GNN: A DeePMD-kit Plugin for External Graph Neural Network Potentials.

Machine learning potentials (MLPs) have revolutionized molecular simulation by providing efficient a...

[Therapeutic patient education and telemedicine in the age of artificial intelligence].

Since the promulgation of the July 21, 2009 law on hospital reform and patients, health and territor...

Future horizons in diabetes: integrating AI and personalized care.

Diabetes is a global health crisis with rising incidence, mortality, and economic burden. Traditiona...

Improving diagnosis-based quality measures: an application of machine learning to the prediction of substance use disorder among outpatients.

OBJECTIVE: Substance use disorder (SUD) is clinically under-detected and under-documented. We built ...

Population Health in Neurology and the Transformative Promise of Artificial Intelligence and Large Language Models.

This manuscript examines the expanding role of population health strategies in neurology, emphasizin...

Identification of heart failure subtypes using transformer-based deep learning modelling: a population-based study of 379,108 individuals.

BACKGROUND: Heart failure (HF) is a complex syndrome with varied presentations and progression patte...

: Towards Autonomous Electronic Health Record Navigation.

Clinicians spend large amounts of time on clinical documentation, and inefficiencies impact quality ...

Effectiveness of machine learning methods in detecting grooming: a systematic meta-analytic review.

This study presents a systematic review (SR) and meta-analysis (MA) on the use of machine learning (...

Deep representation learning for clustering longitudinal survival data from electronic health records.

Precision medicine requires accurate identification of clinically relevant patient subgroups. Electr...

Harnessing Electronic Health Records and Artificial Intelligence for Enhanced Cardiovascular Risk Prediction: A Comprehensive Review.

Electronic health records (EHR) have revolutionized cardiovascular disease (CVD) research by enablin...

Toward a conceptual model to improve the user experience of a sustainable and secure intelligent transport system.

The rapid advancement of automotive technologies has spurred the development of innovative applicati...

Application of the LDA model to identify topics in telemedicine conversations on the X social network.

The evolution experienced by global society, in the post-COVID 19 era, is marked by the quite obliga...

Identifying individuals at risk for weight gain using machine learning in electronic medical records from the United States.

AIMS: Numerous risk factors for the development of obesity have been identified, yet the aetiology i...

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