Risk Management

eHealth Assistant AI Chatbot Using a Large Language Model to Provide Personalized Answers through Secure Decentralized Communication.

In this paper, we present the implementation of an artificial intelligence health assistant designed to complement a previously built eHealth data acquisition system for helping both patients and medical staff. The assistant allows users to query medical information in a smarter, more natural way, respecting patient privacy and using secure communications through a chat style interface based on th...

Deep learning reconstruction algorithm and high-concentration contrast medium: feasibility of a double-low protocol in coronary computed tomography angiography.

OBJECTIVE: To evaluate radiation dose and image quality of a double-low CCTA protocol reconstructed utilizing high-strength deep learning image reconstructions (DLIR-H) compared to standard adaptive statistical iterative reconstruction (ASiR-V) protocol in non-obese patients.

Opportunity and Opportunism in Artificial Intelligence-Powered Data Extraction: A Value-Centered Approach.

Radiologists' traditional role in the diagnostic process is to respond to specific clinical questions and reduce uncertainty enough to permit treatmen...

Revised Tool for the Quality Assessment of Diagnostic Accuracy Studies Using AI (QUADAS-AI): Protocol for a Qualitative Study.

BACKGROUND: Quality assessment of diagnostic accuracy studies (QUADAS), and more recently QUADAS-2, were developed to aid the evaluation of methodolog...

Generative artificial intelligence and ethical considerations in health care: a scoping review and ethics checklist.

The widespread use of Chat Generative Pre-trained Transformer (known as ChatGPT) and other emerging technology that is powered by generative artificia...

From whole-slide image to biomarker prediction: end-to-end weakly supervised deep learning in computational pathology.

Hematoxylin- and eosin-stained whole-slide images (WSIs) are the foundation of diagnosis of cancer. In recent years, development of deep learning-base...

SpeechBrain-MOABB: An open-source Python library for benchmarking deep neural networks applied to EEG signals.

Deep learning has revolutionized EEG decoding, showcasing its ability to outperform traditional machine learning models. However, unlike other fields,...

Mobil Monitoring Doppler Ultrasound (MoMDUS) study: protocol for a prospective, observational study investigating the use of artificial intelligence and low-cost Doppler ultrasound for the automated quantification of hypertension, pre-eclampsia and fetal growth restriction in rural Guatemala.

INTRODUCTION: Undetected high-risk conditions in pregnancy are a leading cause of perinatal mortality in low-income and middle-income countries. A key...

Artificial intelligence in human resource development: An umbrella review protocol.

The recent surge in artificial intelligence (AI) has significantly transformed work dynamics, particularly in human resource development (HRD) and rel...

Leveraging AI and patient metadata to develop a novel risk score for skin cancer detection.

Melanoma of the skin is the 17th most common cancer worldwide. Early detection of suspicious skin lesions (melanoma) can increase 5-year survival rate...

Evaluating the impact of artificial intelligence-assisted image analysis on the diagnostic accuracy of front-line clinicians in detecting fractures on plain X-rays (FRACT-AI): protocol for a prospective observational study.

INTRODUCTION: Missed fractures are the most frequent diagnostic error attributed to clinicians in UK emergency departments and a significant cause of ...

Enhancing Facial Expression Recognition through Light Field Cameras.

In this paper, we study facial expression recognition (FER) using three modalities obtained from a light field camera: sub-aperture (SA), depth map, a...

An artificial intelligence handheld sensor for direct reading of nickel ion and ethylenediaminetetraacetic acid in food samples using ratiometric fluorescence cellulose paper microfluidic chip.

User-friendly in-field sensing protocol is crucial for the effective tracing of intended analytes under less-developed countries or resources-limited ...

Machine learning-derived phenotypic trajectories of asthma and allergy in children and adolescents: protocol for a systematic review.

INTRODUCTION: Development of asthma and allergies in childhood/adolescence commonly follows a sequential progression termed the 'atopic march'. Recent...

Pilot deployment of a cloud-based universal medical image repository in a large public health system: A protocol study.

This paper outlines the protocol for the deployment of a cloud-based universal medical image repository system. The proposal aims not only at the depl...

Consumer-priced wearable sensors combined with deep learning can be used to accurately predict ground reaction forces during various treadmill running conditions.

Ground reaction force (GRF) data is often collected for the biomechanical analysis of running, due to the performance and injury risk insights that GR...

Deep Learning-Enhanced Accelerated 2D TSE and 3D Superresolution Dixon TSE for Rapid Comprehensive Knee Joint Assessment.

OBJECTIVES: The aim of this study was to evaluate the use of a multicontrast deep learning (DL)-reconstructed 4-fold accelerated 2-dimensional (2D) tu...

The simplification of the symptom Checklist-90 scale utilizing machine learning techniques.

The Symptom Checklist-90 (SCL-90), widely utilized for psychological assessments, faces challenges due to its extensive nature. Streamlining the SCL-9...

Artificial Intelligence-Driven Prognosis of Respiratory Mechanics: Forecasting Tissue Hysteresivity Using Long Short-Term Memory and Continuous Sensor Data.

Tissue hysteresivity is an important marker for determining the onset and progression of respiratory diseases, calculated from forced oscillation lung...

Deep Learning and fMRI-Based Pipeline for Optimization of Deep Brain Stimulation During Parkinson's Disease Treatment: Toward Rapid Semi-Automated Stimulation Optimization.

OBJECTIVE: Optimized deep brain stimulation (DBS) is fast becoming a therapy of choice for the treatment of Parkinson's disease (PD). However, the pos...