Practice Management

Latest AI and machine learning research in practice management for healthcare professionals.

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Opportunities, Risks, Strengths and Weaknesses of Robotic Systems in Early Neurological Rehabilitation.

Given the conference's focus on innovative healthcare solutions, our investigation into robotic assi...

Deep learning approaches for non-coding genetic variant effect prediction: current progress and future prospects.

Recent advancements in high-throughput sequencing technologies have significantly enhanced our abili...

Using Generative AI to Translate Administrative Claims Data into Narrative Summaries for Palliative Care Needs Assessment: A Case Study.

Community-based palliative care is a useful, but underutilized service to support seriously ill olde...

Artificial Intelligence in Nursing: Perspectives from Norwegian Nurses.

Nurses continue to face challenges in leading health information technology innovations such as Arti...

A comprehensive survey on deep learning-based identification and predicting the interaction mechanism of long non-coding RNAs.

Long noncoding RNAs (lncRNAs) have been discovered to be extensively involved in eukaryotic epigenet...

Towards the development of a FAIR-compliant biomedical ontology for colorectal cancer.

Despite the widespread development of ontologies in many domains of healthcare, the field of colorec...

Highly accurate classification and discovery of microbial protein-coding gene functions using FunGeneTyper: an extensible deep learning framework.

High-throughput DNA sequencing technologies decode tremendous amounts of microbial protein-coding ge...

Development of a Method for Automatic Matching of Unstructured Medical Data to ICD-10 Codes.

Inconsistent disease coding standards in medicine create hurdles in data exchange and analysis. This...

Applications of Natural Language Processing for Automated Clinical Data Analysis in Orthopaedics.

Natural language processing is an exciting and emerging field in health care that can transform the ...

Meta predictive learning model of languages in neural circuits.

Large language models based on self-attention mechanisms have achieved astonishing performances, not...

[Identification of Protein-Coding Gene Markers in Breast Invasive Carcinoma Based on Machine Learning].

Objective To screen out the biomarkers linked to prognosis of breast invasive carcinoma based on the...

Coding genomes with gapped pattern graph convolutional network.

MOTIVATION: Genome sequencing technologies reveal a huge amount of genomic sequences. Neural network...

Assessing Learning of Computer Programing Skills in the Age of Generative Artificial Intelligence.

Generative artificial intelligence (AI) tools such as ChatGPT, Bard, and Claude have recently become...

Artificial intelligence: revolutionizing cardiology with large language models.

Natural language processing techniques are having an increasing impact on clinical care from patient...

Secondary Use of Clinical Problem List Descriptions for Bi-Encoder Based ICD-10 Classification.

Annotated language resources are essential for supervised machine learning methods. In the clinical ...

Edge, Fog, and Cloud Against Disease: The Potential of High-Performance Cloud Computing for Pharma Drug Discovery.

The high-performance computing (HPC) platform for large-scale drug discovery simulation demands sign...

Active Predictive Coding: A Unifying Neural Model for Active Perception, Compositional Learning, and Hierarchical Planning.

There is growing interest in predictive coding as a model of how the brain learns through prediction...

The use of natural language processing in detecting and predicting falls within the healthcare setting: a systematic review.

Falls are a common problem associated with significant morbidity, mortality, and economic costs. Cur...

Smart sleep: what to consider when adopting AI-enabled solutions in clinical practice of sleep medicine.

UNLABELLED: Since the publication of its 2020 position statement on artificial intelligence (AI) in ...

A comprehensive review and evaluation of graph neural networks for non-coding RNA and complex disease associations.

Non-coding RNAs (ncRNAs) play a critical role in the occurrence and development of numerous human di...

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