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Latest AI and machine learning research in surveys for healthcare professionals.

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A comprehensive review of neurotransmitter modulation via artificial intelligence: A new frontier in personalized neurobiochemistry.

The deployment of artificial intelligence (AI) is revolutionizing neuropharmacology and drug develop...

Analysing learning behaviour: A data-driven approach to improve time management and active listening skills in students.

Learning behavior refers to the actions, attitudes, and strategies individuals employ when acquiring...

Risk of bias assessment of post-stroke mortality machine learning predictive models: Systematic review.

BACKGROUND: Stroke is a major cause of mortality and permanent disability worldwide. Precise predict...

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...

Sex bias consideration in healthcare machine-learning research: a systematic review in rheumatoid arthritis.

OBJECTIVE: To assess the acknowledgement and mitigation of sex bias within studies using supervised ...

Using Generative AI to Extract Structured Information from Free Text Pathology Reports.

Manually converting unstructured text pathology reports into structured pathology reports is very ti...

Progressive multi-task learning for fine-grained dental implant classification and segmentation in CBCT image.

With the ongoing advancement of digital technology, oral medicine transitions from traditional diagn...

Enhancing Unconditional Molecule Generation via Online Knowledge Distillation of Scaffolds.

Generating new drug-like molecules is an essential aspect of drug discovery, and deep learning model...

PrOsteoporosis: predicting osteoporosis risk using NHANES data and machine learning approach.

OBJECTIVES: Osteoporosis, prevalent among the elderly population, is primarily diagnosed through bon...

Utilizing SMOTE-TomekLink and machine learning to construct a predictive model for elderly medical and daily care services demand.

This study aims to construct a prediction model for the demand for medical and daily care services o...

Addressing data handling shortcomings in machine learning studies on biochar for heavy metal remediation.

Recent advancements in machine learning (ML) technologies have significantly enhanced their applicat...

Overconfident, but angry at least. AI-Based investigation of facial emotional expressions and self-assessment bias in human adults.

Metacognition and facial emotional expressions both play a major role in human social interactions [...

Equitable machine learning counteracts ancestral bias in precision medicine.

Gold standard genomic datasets severely under-represent non-European populations, leading to inequit...

Analysing how AI-powered chatbots influence destination decisions.

This study aims to explore the role of destination chatbots as innovative tools in travel planning, ...

A survey on open challenges in heart disease prediction models.

Heart disease (HD), is a deadly serious disease, that has received a great deal of consideration in ...

Validity of recurrent neural networks to predict pedal forces and lower limb kinetics in cycling.

Dynamic variables contribute to understand the mechanics of pedalling and can assist with injury pre...

Fine-Tuned Deep Transfer Learning Models for Large Screenings of Safer Drugs Targeting Class A GPCRs.

G protein-coupled receptors (GPCRs) remain a focal point of research due to their critical roles in ...

FedBM: Stealing knowledge from pre-trained language models for heterogeneous federated learning.

Federated learning (FL) has shown great potential in medical image computing since it provides a dec...

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