Clinical Trials

Baseline Moderators of Response to Naltrexone and Bupropion in the Treatment of Methamphetamine Use Disorder: An ADAPT-2 Study.

OBJECTIVES: Extended-release naltrexone and once-daily bupropion (NTX-BUP) reduced methamphetamine (MA) use in the Accelerated Development of Additive Pharmacotherapy Treatment for Methamphetamine Use Disorder (ADAPT-1, ADAPT-2) trials. Using a proof-of-concept machine learning technique, we created a classification rule using baseline characteristics to identify individuals who would benefit more...

Structural health monitoring and evaluation method for an immersed tunnel based on deep learning.

The health monitoring of the subsea-immersed tunnels is essential for the early detection of anomalies and the assurance of their long-term operational safety. This research examines sensor data to evaluate variations in critical parameters and their effects on structural integrity. It also compares the efficacy of two deep learning algorithms, Long Short-Term Memory (LSTM) and Transformer, in pre...

Machine learning assisted adjustment boosts efficiency of exact inference in randomized controlled trials.

In this work, we proposed a novel inferential procedure assisted by machine learning based adjustment for randomized control trials. The method was de...

Current Research and Development in the Field of Magnetic Resonance Contrast Media.

The next-generation, high relaxivity, gadolinium-based contrast agents (GBCAs) are discussed, together with new studies of safety, improvements in MR ...

Carbon co-benefits of digital economy and green finance: empirical evidence from China.

Addressing the carbon co-benefits of policy tools requires simultaneous improvements in both the quantity and quality of carbon abatement to achieve l...

Research on predicting the risk level of coal mine roof accident based on machine learning.

Coal mine roof accidents are one of the main types of accidents leading to the decline of coal mine safety productivity, accounting for about 20% of t...

Impact of generative AI interaction and output quality on university students' learning outcomes: a technology-mediated and motivation-driven approach.

This study investigates the influence of generative artificial intelligence (GAI) on university students' learning outcomes, employing a technology-me...

Generative artificial intelligence in entrepreneurship education enhances entrepreneurial intention through self-efficacy and university support.

This study investigates how Generative Artificial Intelligence Supported Entrepreneurship Education (GAISEE) influences university students' entrepren...

Effects of device-assisted practice of activities of daily living in a close-to-normal pattern on upper extremity motor recovery in individuals with moderate to severe stroke: study protocol of a randomized control trial.

BACKGROUND: The majority of individuals with chronic stroke have residual upper extremity (UE) disability which they cite as their greatest barrier to...

The Impact of Machine Learning Mortality Risk Prediction on Clinician Prognostic Accuracy and Decision Support: A Randomized Vignette Study.

BackgroundMachine learning (ML) algorithms may improve the prognosis for serious illnesses such as cancer, identifying patients who may benefit from e...

Divide-and-conquer strategy with engineered ossification center organoids for rapid bone healing through developmental cell recruitment.

Current approaches for bone repair predominantly target localized delivery of growth factors that are aimed at the coupling of angiogenesis and osteog...

Characteristics of brain network connectome and connectome-based efficacy predictive model in bipolar depression.

Aberrant functional connectivity (FC) between brain networks has been indicated closely associated with bipolar disorder (BD). However, the previous f...

Artificial Intelligence-Enabled ECGs for Atrial Fibrillation Identification and Enhanced Oral Anticoagulant Adoption: A Pragmatic Randomized Clinical Trial.

BACKGROUND: Atrial fibrillation (AF) is often underdiagnosed and undertreated by noncardiologists. This study evaluated whether artificial intelligenc...

Developing Nationwide Estimates of Built Environment Quality Characteristics Using Street-View Imagery and Computer Vision.

Environmental health studies commonly rely on urban composition measures for built environment exposure assessment. However, quality measures are equa...

Using Machine Learning to Predict Treatment Outcome in a Concatenated Dataset of Youth Anxiety Treatments.

Machine Learning (ML) is a promising approach for predicting outcomes of youth anxiety treatments. To this end, data from nine randomized controlled t...

Artificial Intelligence to Improve Clinical Coding Practice in Scandinavia: Crossover Randomized Controlled Trial.

BACKGROUND: Clinical coding is critical for hospital reimbursement, quality assessment, and health care planning. In Scandinavia, however, coding is o...

Optic nerve sheath diameter in the prognosis of patients with traumatic optic neuropathy: Evaluation and predictive efficacy.

The purpose of this study was to evaluate and predict visual prognosis in patients with traumatic optic neuropathy by measuring the optic nerve sheath...

Enhancing gas concentration prediction and ventilation efficiency in deep coal mines: a hybrid DL-Koopman and Fuzzy-PID framework.

With the increasing depth of coal mining operations, traditional ventilation systems are becoming insufficient to address the growing safety and opera...

Automated grading of rectocele with an MRI radiomics model.

To develop an automated grading model for rectocele (RC) based on radiomics and evaluate its efficacy. This study retrospectively analyzed a total of ...

The construction of HMME-PDT efficacy prediction model for port-wine stain based on machine learning algorithms.

Hematoporphyrin monomethyl ether-photodynamic therapy (HMME-PDT) is a safe and effective treatment for port-wine stain (PWS). Comprehensive methods fo...