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Deep Aramaic: Towards a synthetic data paradigm enabling machine learning in epigraphy.

Epigraphy is witnessing a growing integration of artificial intelligence, notably through its subfie...

Application of artificial intelligence technology in monitoring students' health: Preliminary results of Syiah Kuala Integrated Medical Monitoring (SKIMM).

Health promoting university is a holistic approach to health that uses higher education settings to ...

Improving multiple sclerosis lesion segmentation across clinical sites: A federated learning approach with noise-resilient training.

Accurately measuring the evolution of Multiple Sclerosis (MS) with magnetic resonance imaging (MRI) ...

Predicting treatment plan approval probability for high-dose-rate brachytherapy of cervical cancer using adversarial deep learning.

Predicting the probability of having the plan approved by the physician is important for automatic t...

Contrastive Prototype-Guided Generation for Generalized Zero-Shot Learning.

Generalized zero-shot learning (GZSL) aims to recognize both seen and unseen classes, while only sam...

Robotic assisted and exoskeleton gait training effect in mental health and fatigue of multiple sclerosis patients. A systematic review and a meta-analysis.

PURPOSE: Robotic and Exoskeleton Assisted Gait Training (REAGT) has become the mainstream gait train...

Semantically redundant training data removal and deep model classification performance: A study with chest X-rays.

Deep learning (DL) has demonstrated its innate capacity to independently learn hierarchical features...

Combining Artificial Intelligence and Simplified Image Processing for the Automatic Detection of Mycobacterium tuberculosis in Acid-fast Stain : A Cross-institute Training and Validation Study.

Tuberculosis (TB) poses a significant health threat in Taiwan, necessitating efficient detection met...

Unsupervised robot-assisted rehabilitation after stroke: feasibility, effect on therapy dose, and user experience.

BACKGROUND: Unsupervised robot-assisted rehabilitation is a promising approach to increase the dose ...

Thank you artificial intelligence: Evidence-based just-in-time training via a large language model.

Machine learning approaches to predict TAS2R receptors for bitterants.

Bitter taste involves the detection of diverse chemical compounds by a family of G protein-coupled r...

Understanding Bias in Artificial Intelligence: A Practice Perspective.

In the fall of 2021, several experts in this space delivered a Webinar hosted by the American Societ...

Prediction of polyspecificity from antibody sequence data by machine learning.

Antibodies are generated with great diversity in nature resulting in a set of molecules, each optimi...

Navigating the inevitable convergence of artificial intelligence and surgical training programs.

Investigation of out-of-distribution detection across various models and training methodologies.

Machine learning-based algorithms demonstrate impressive performance across numerous fields; however...

ROBot-assisted physical training of older patients during acUte hospitaliSaTion-study protocol for a randomised controlled trial (ROBUST).

BACKGROUND: During hospitalisation, older patients spend most of their time passive in bed, which in...

The radiologist as a physician - artificial intelligence as a way to overcome tension between the patient, technology, and referring physicians - a narrative review.

BACKGROUND: Large volumes of data increasing over time lead to a shortage of radiologists' time. The...

SC-SSL: Self-Correcting Collaborative and Contrastive Co-Training Model for Semi-Supervised Medical Image Segmentation.

Image segmentation achieves significant improvements with deep neural networks at the premise of a l...

Data reduction for SVM training using density-based border identification.

Numerous classification and regression problems have extensively used Support Vector Machines (SVMs)...

Author's reply: The importance of professional training to foster the implementation of Artificial Intelligence in the clinical setting of liver diseases.

Randomized controlled trial of the CMR immersive virtual reality (IVR) headset training compared to e-learning for operating room configuration of the CMR versius robot.

Robotic surgery offers potential advantages over laparoscopic procedures, but the training for confi...