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Artificial Intelligence-Based Pharmacovigilance in the Setting of Limited Resources.

With the rapid development of artificial intelligence (AI) technologies, and the large amount of pha...

Applying Machine Learning in Distributed Data Networks for Pharmacoepidemiologic and Pharmacovigilance Studies: Opportunities, Challenges, and Considerations.

Increasing availability of electronic health databases capturing real-world experiences with medical...

Artificial Intelligence Based on Machine Learning in Pharmacovigilance: A Scoping Review.

INTRODUCTION: Artificial intelligence based on machine learning has made large advancements in many ...

Industry Perspective on Artificial Intelligence/Machine Learning in Pharmacovigilance.

TransCelerate reports on the results of 2019, 2020, and 2021 member company (MC) surveys on the use ...

Artificial Intelligence in Pharmacovigilance: An Introduction to Terms, Concepts, Applications, and Limitations.

The tools of artificial intelligence (AI) have enormous potential to enhance activities in pharmacov...

Artificial Intelligence and Machine Learning for Safe Medicines.

Authors' views on the role of artificial intelligence and machine learning in pharmacovigilance. (MP...

Automatic characterization of human embryos at day 4 post-insemination from time-lapse imaging using supervised contrastive learning and inductive transfer learning techniques.

BACKGROUND: Embryo morphology is a predictive marker for implantation success and ultimately live bi...

LEOD-Net: Learning Line-Encoded Bounding Boxes for Real-Time Object Detection.

This paper proposes a learnable line encoding technique for bounding boxes commonly used in the obje...

A Post-training Quantization Method for the Design of Fixed-Point-Based FPGA/ASIC Hardware Accelerators for LSTM/GRU Algorithms.

Recurrent Neural Networks (RNNs) have become important tools for tasks such as speech recognition, t...

iProm-Zea: A two-layer model to identify plant promoters and their types using convolutional neural network.

A promoter is a short DNA sequence near the start codon, responsible for initiating the transcriptio...

Identification of hand-foot syndrome from cancer patients' blog posts: BERT-based deep-learning approach to detect potential adverse drug reaction symptoms.

Early detection and management of adverse drug reactions (ADRs) is crucial for improving patients' q...

The clinical effects of brain-computer interface with robot on upper-limb function for post-stroke rehabilitation: a meta-analysis and systematic review.

PURPOSE: Many recent clinical studies have suggested that the combination of brain-computer interfac...

Using Robot-Based Variables during Upper Limb Robot-Assisted Training in Subacute Stroke Patients to Quantify Treatment Dose.

In post-stroke motor rehabilitation, treatment dose description is estimated approximately. The aim ...

Robot-assisted and traditional intensive rehabilitation therapy in the treatment of post-acute stroke patient: the experience of a standard rehabilitation ward.

Multimodal treatment efficacy differs in dependence of core symptom profiles in adult Attention-Deficit/Hyperactivity Disorder: An analysis of the randomized controlled COMPAS trial.

There is broad consensus that to improve the treatment of adult Attention-Deficit/Hyperactivity Diso...

Deep learning for locally advanced nasopharyngeal carcinoma prognostication based on pre- and post-treatment MRI.

PURPOSE: We aimed to predict the prognosis of advanced nasopharyngeal carcinoma (stage Ⅲ-Ⅳa) using P...

Deep learning-based image reconstruction and post-processing methods in positron emission tomography for low-dose imaging and resolution enhancement.

Image processing plays a crucial role in maximising diagnostic quality of positron emission tomograp...

Continence definition and prognostic factors for early urinary continence recovery in posterior rhabdosphincter reconstruction after robot-assisted radical prostatectomy. Post-hoc analysis of a randomised controlled trial.

INTRODUCTION: Urinary incontinence after radical prostatectomy (RP) is an adverse event with high im...

On the Post Hoc Explainability of Optimized Self-Organizing Reservoir Network for Action Recognition.

This work proposes a novel unsupervised self-organizing network, called the Self-Organizing Convolut...

On the interpretability of machine learning methods in crash frequency modeling and crash modification factor development.

Machine learning (ML) model interpretability has attracted much attention recently given the promisi...

Fully automated intracardiac 4D flow MRI post-processing using deep learning for biventricular segmentation.

OBJECTIVES: 4D flow MRI allows for a comprehensive assessment of intracardiac blood flow, useful for...