AI Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

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Using artificial intelligence tools to automate data extraction for living evidence syntheses.

PloS one
Living evidence synthesis (LES) involves repeatedly updating a systematic review or meta-analysis at regular intervals to incorporate new evidence into the summary results. It requires a considerable amount of human time investment in the article sea...

Machine learning for automated electrical penetration graph analysis of aphid feeding behavior: Accelerating research on insect-plant interactions.

PloS one
The electrical penetration graph (EPG) is a well-known technique that provides insights into the feeding behavior of insects with piercing-sucking mouthparts, mostly hemipterans. Since its inception in the 1960s, EPG has become indispensable in study...

Advancing enterprise risk management with deep learning: A predictive approach using the XGBoost-CNN-BiLSTM model.

PloS one
Enterprise risk management is a key element to ensure the sustainable and steady development of enterprises. However, traditional risk management methods have certain limitations when facing complex market environments and diverse risk events. This s...

Positive relationship between education level and risk perception and behavioral response: A machine learning approach.

PloS one
This paper aims to examine the influence mechanism of education level as a key situational factor in the relationship between risk perception and behavioral response, encompassing both behavioral intention and preparatory behavior. Utilizing non-para...

Enlightened prognosis: Hepatitis prediction with an explainable machine learning approach.

PloS one
Hepatitis is a widespread inflammatory condition of the liver, presenting a formidable global health challenge. Accurate and timely detection of hepatitis is crucial for effective patient management, yet existing methods exhibit limitations that unde...

Evaluating how different balancing data techniques impact on prediction of premature birth using machine learning models.

PloS one
Premature birth can be defined as birth before 37 weeks of gestation, which is a significant global health issue, being the main cause for neonatal deaths. In this work, we evaluate machine learning models for predicting premature birth using Brazili...

Understanding patterns of loneliness in older long-term care users using natural language processing with free text case notes.

PloS one
Loneliness and social isolation are distressing for individuals and predictors of mortality, yet data on their impact on publicly funded long-term care is limited. Using recent advances in natural language processing (NLP), we analysed pseudonymised ...

Barriers and enablers for the deployment of large language model-based conversational robots for older adults: A protocol for a systematic review of qualitative studies.

PloS one
BACKGROUND: Artificial intelligence-powered conversational agents have immense potential to provide social companionship and support for older adults. However, the deployment of large language model (LLM)-based conversational robots for seniors faces...

A machine learning computational approach for the mathematical anthrax disease system in animals.

PloS one
OBJECTIVES: The current research investigations present the numerical solutions of the anthrax disease system in animals by designing a machine learning stochastic procedure. The mathematical anthrax disease system in animals is classified into susce...

Can we use lower extremity joint moments predicted by the artificial intelligence model during walking in patients with cerebral palsy in the clinical gait analysis?

PloS one
Several studies have highlighted the advantages of employing artificial intelligence (AI) models in gait analysis. However, the credibility and practicality of integrating these models into clinical gait routines remain uncertain. This study critical...