Clinical Trials

Operational safety risk modeling in a naval organization.

INTRODUCTION: Following numerous mishaps and near-misses, the U.S. Naval Surface Force established the Operational Surface Risk Indicators (OSRI) project to explore a robust proactive risk analysis and reduction capability. The OSRI model leverages multisource enterprise-wide data to forecast potential risks for individual warships to help leaders make informed operational decisions and ultimately...

Young doctors' attrition and retention in the GP scheme: a national cohort study from Norway.

AIMS: Several countries struggle with general practitioner (GP) burnout, recruitment and retention. The reasons are not well understood. The aim of this study was to predict the tenure of young GPs in the GP scheme and detect important predictors for remaining or leaving. METHODS: Using data from Norwegian registries, LASSO Cox regression models were applied to identify variables, including the pe...

A multimodal approach to depression diagnosis: insights from machine learning algorithm development in primary care.

General practitioners play an essential role in identifying depression and are often the first point of contact for patients. Current diagnostic tools...

Dynamic HRV Monitoring and Machine Learning Predict NYHA Improvements in Acute Heart Failure Patients.

Heart failure (HF) is marked by significant morbidity, mortality, and readmission rates, highlighting a critical need for accurate assessment of treat...

Fine-Tuned Deep Transfer Learning Models for Large Screenings of Safer Drugs Targeting Class A GPCRs.

G protein-coupled receptors (GPCRs) remain a focal point of research due to their critical roles in cell signaling and their prominence as drug target...

Power-free knee rehabilitation robot for home-based isokinetic training.

Robot-assisted isokinetic training has been widely adopted for knee rehabilitation. However, existing rehabilitation facilities are often heavy, bulky...

An ultra-sensitive, intelligent platform for food safety monitoring: Label-free detection of illegal additives using self-assembled SERS substrates and machine learning.

To overcome the limitations of SERS in food safety monitoring, particularly significant interference from citrate ions, this study introduces an intel...

Continuous nursing symptom management in cancer chemotherapy patients using deep learning.

To assess the efficacy of a deep learning platform for managing symptoms in chemotherapy patients, aiming to enhance their quality of life. A non-rand...

Comparison of an AI Chatbot With a Nurse Hotline in Reducing Anxiety and Depression Levels in the General Population: Pilot Randomized Controlled Trial.

BACKGROUND: Artificial intelligence (AI) chatbots have been customized to deliver on-demand support for people with mental health problems. However, t...

Modeling crash avoidance behaviors in vehicle-pedestrian near-miss scenarios: Curvilinear time-to-collision and Mamba-driven deep reinforcement learning.

Interactions between vehicle-pedestrian at intersections often lead to safety-critical situations. This study aims to model the crash avoidance behavi...

Discovery of mutations predictive of survival benefit from immunotherapy in first-line NSCLC: A retrospective machine learning study of IMpower150 liquid biopsy data.

Predictive biomarker identification in cancer treatment has traditionally relied on pre-defined analyses, limiting discoveries to expected biomarkers ...

Prospective Clinical Implementation of Paige Prostate Detect Artificial Intelligence Assistance in the Detection of Prostate Cancer in Prostate Biopsies: CONFIDENT P Trial Implementation of Artificial Intelligence Assistance in Prostate Cancer Detection.

PURPOSE: Pathologists diagnose prostate cancer (PCa) on hematoxylin and eosin (HE)-stained sections of prostate needle biopsies (PBx). Some laboratori...

Does the alternating timing of rTMS combined with soft-hand rehabilitation robot affect the recovery of hand function in patients after stroke? A study protocol for a multicentre randomised controlled trial.

INTRODUCTION: Combining repetitive transcranial magnetic stimulation (rTMS) with robotic training could result in more significant improvements in mot...

Efficacy and Safety of a Medical Robot for Non-Face-to-Face Nasopharyngeal Swab Specimen Collection: Nonclinical and Clinical Trial Findings for COVID-19 Testing.

ObjectivesTo meet the high demand for polymerase chain reaction (PCR) tests to diagnose COVID-19 and rapidly control the outbreak, an efficient and sa...

AI-driven evidence synthesis: data extraction of randomized controlled trials with large language models.

The advancement of large language models (LLMs) presents promising opportunities to enhance evidence synthesis efficiency, particularly in data extrac...

Joint Driver State Classification Approach: Face Classification Model Development and Facial Feature Analysis Improvement.

Driver drowsiness remains a critical factor in road safety, necessitating the development of robust detection methodologies. This study presents a dua...

Is it necessary? A framework for assessing the utility of A.I. in HRM practices.

Artificial Intelligence is expected to be a value-adding intervention in HRM processes; however, there is still a large gap between its perception of ...

Optimizing Quality Tolerance Limits Monitoring in Clinical Trials Through Machine Learning Methods.

The traditional clinical trial monitoring process, which relies heavily on site visits and manual review of accumulative patient data reported through...

SynthMol: A Drug Safety Prediction Framework Integrating Graph Attention and Molecular Descriptors into Pre-Trained Geometric Models.

Drug safety is affected by multiple molecular properties and safety assessment is critical for clinical application. Evaluating a drug candidate's the...

Inductive reasoning with large language models: A simulated randomized controlled trial for epilepsy.

INTRODUCTION: To investigate the potential of using artificial intelligence (AI), specifically large language models (LLMs), for synthesizing informat...