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Ethical, legal, and regulatory landscape of artificial intelligence in Australian healthcare and ethical integration in radiography: A narrative review.

This narrative review explores the ethical, legal, and regulatory landscape of AI integration in Aus...

Generative Artificial Intelligence Tools in Gastroenterology Training.

The consequences of AI training on human decision-making.

AI is now an integral part of everyday decision-making, assisting us in both routine and high-stakes...

LightNet: A Novel Lightweight Convolutional Network for Brain Tumor Segmentation in Healthcare.

Diagnosis, treatment planning, surveillance, and the monitoring of clinical trials for brain disease...

Mobile applications on app stores for deprescribing: A scoping review.

Deprescribing is an evidence-based intervention to reduce potentially inappropriate medication use. ...

EEG-VTTCNet: A loss joint training model based on the vision transformer and the temporal convolution network for EEG-based motor imagery classification.

Brain-computer interface (BCI) is a technology that directly connects signals between the human brai...

Random effects during training: Implications for deep learning-based medical image segmentation.

BACKGROUND: A single learning algorithm can produce deep learning-based image segmentation models th...

Implementing AI in Hospitals to Achieve a Learning Health System: Systematic Review of Current Enablers and Barriers.

BACKGROUND: Efforts are underway to capitalize on the computational power of the data collected in e...

BrainNPT: Pre-Training Transformer Networks for Brain Network Classification.

Deep learning methods have advanced quickly in brain imaging analysis over the past few years, but t...

Evolution of white matter hyperintensity segmentation methods and implementation over the past two decades; an incomplete shift towards deep learning.

This systematic review examines the prevalence, underlying mechanisms, cohort characteristics, evalu...

Modeling the Impact of Ergonomic Interventions and Occupational Factors on Work-Related Musculoskeletal Disorders in the Neck of Office Workers with Machine Learning Methods.

BACKGROUND: Modeling with methods based on machine learning (ML) and artificial intelligence can hel...

Deep mutational scanning and machine learning for the analysis of antimicrobial-peptide features driving membrane selectivity.

Many antimicrobial peptides directly disrupt bacterial membranes yet can also damage mammalian membr...

The changing landscape of text mining: a review of approaches for ecology and evolution.

In ecology and evolutionary biology, the synthesis and modelling of data from published literature a...

Characterizing the Effects of Adding Virtual and Augmented Reality in Robot-Assisted Training.

Extended reality (XR) technology combines physical reality with computer synthetic virtuality to del...

The impact of high-order features on performance of radiomics studies in CT non-small cell lung cancer.

High-order radiomic features have been shown to produce high performance models in a variety of scen...

Cross-Species Prediction of Transcription Factor Binding by Adversarial Training of a Novel Nucleotide-Level Deep Neural Network.

Cross-species prediction of TF binding remains a major challenge due to the rapid evolutionary turno...

Training high-performance deep learning classifier for diagnosis in oral cytology using diverse annotations.

The uncertainty of true labels in medical images hinders diagnosis owing to the variability across p...

Additional Rehabilitative Robot-Assisted Gait Training for Ambulation in Geriatric Individuals with Guillain-Barré Syndrome: A Case Report.

We present a case of a 75-year-old Asian woman with Guillain-Barré syndrome (GBS) who underwent a 1-...

Integrating Artificial Intelligence-Driven Wearable Technology in Oncology Decision-Making: A Narrative Review.

BACKGROUND: Clinical decision-making in oncology is a complex process influenced by numerous disease...

Comprehensive review of deep learning in orthopaedics: Applications, challenges, trustworthiness, and fusion.

Deep learning (DL) in orthopaedics has gained significant attention in recent years. Previous studie...

Understanding natural language: Potential application of large language models to ophthalmology.

Large language models (LLMs), a natural language processing technology based on deep learning, are c...