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Foundation models in gastrointestinal endoscopic AI: Impact of architecture, pre-training approach and data efficiency.

Pre-training deep learning models with large data sets of natural images, such as ImageNet, has beco...

Diversity matters: Cross-head mutual mean-teaching for semi-supervised medical image segmentation.

Semi-supervised medical image segmentation (SSMIS) has witnessed substantial advancements by leverag...

Training and Comparison of nnU-Net and DeepMedic Methods for Autosegmentation of Pediatric Brain Tumors.

BACKGROUND AND PURPOSE: Tumor segmentation is essential in surgical and treatment planning and respo...

Impact of training data composition on the generalizability of convolutional neural network aortic cross-section segmentation in four-dimensional magnetic resonance flow imaging.

BACKGROUND: Four-dimensional cardiovascular magnetic resonance flow imaging (4D flow CMR) plays an i...

Robust and Privacy-Preserving Decentralized Deep Federated Learning Training: Focusing on Digital Healthcare Applications.

Federated learning of deep neural networks has emerged as an evolving paradigm for distributed machi...

Measurable residual disease (MRD) dynamics in multiple myeloma and the influence of clonal diversity analyzed by artificial intelligence.

Minimal residual disease (MRD) assessment is a known surrogate marker for survival in multiple myelo...

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...

Estimating highest capacity propulsion performance using backward-directed force during walking evaluation for individuals with acquired brain injury.

There are over 5.3 million Americans who face acquired brain injury (ABI)-related disability as well...

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...

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...

Single-cell and bulk RNA-sequence identified fibroblasts signature and CD8 + T-cell - fibroblast subtype predicting prognosis and immune therapeutic response of bladder cancer, based on machine learning: bioinformatics multi-omics study.

BACKGROUND: Cancer-associated fibroblasts (CAFs) are found in primary and advanced tumours. They are...

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...

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...

Machine learning-guided co-optimization of fitness and diversity facilitates combinatorial library design in enzyme engineering.

The effective design of combinatorial libraries to balance fitness and diversity facilitates the eng...

Evaluating GenAI systems to combat mental health issues in healthcare workers: An integrative literature review.

BACKGROUND: Mental health issues among healthcare workers remain a serious problem globally. Recent ...

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-...

Improving quantitative prediction of protein subcellular locations in fluorescence images through deep generative models.

Machine learning has been employed in recognizing protein localization at the subcellular level, whi...

Accounting for minimum data required to train a machine learning model to accurately monitor Australian dairy pastures using remote sensing.

Precision in grazing management is highly dependent on accurate pasture monitoring. Typically, this ...