Devices and Vaccines

Liquid-bodied antibiofilm robot with switchable viscoelastic response for biofilm eradication on complex surface topographies.

Recalcitrant biofilm infections pose a great challenge to human health. Micro- and nanorobots have been used to eliminate biofilm infections in hard-to-reach regions inside the body. However, applying antibiofilm robots under physiological conditions is limited by the conflicting demands of accessibility and driving force. Here, we introduce a liquid-bodied antibiofilm robot constructed by a dynam...

Modifiable risk factors of vaccine hesitancy: insights from a mixed methods multiple population study combining machine learning and thematic analysis during the COVID-19 pandemic.

BACKGROUND: Vaccine hesitancy, the delay in acceptance or reluctance to vaccinate, ranks among the top threats to global health. Identifying modifiable factors contributing to vaccine hesitancy is crucial for developing targeted interventions to increase vaccination uptake.

An Optimised Mobilenet V2 Attention Parallel Network for Predicting Drug-Drug Interactions Through Combining Local and Global Features.

Drug-drug interactions (DDIs) are an important concern in the clinical practice and drug development process as these may lead to serious adverse effe...

AI classification of knee prostheses from plain radiographs and real-world applications.

PURPOSE: Total knee arthroplasty (TKA) is considered the gold standard treatment for end-stage knee osteoarthritis. Common complications associated wi...

Utilizing SMOTE-TomekLink and machine learning to construct a predictive model for elderly medical and daily care services demand.

This study aims to construct a prediction model for the demand for medical and daily care services of the elderly and to explore the factors that affe...

Optimization of primary screw stability in Trabecular bone using neural network-based models.

BACKGROUND AND OBJECTIVE: Screw implant stability in bone is crucial to the success of many orthopaedic procedures, yet the relationship between screw...

Automatic detecting multiple bone metastases in breast cancer using deep learning based on low-resolution bone scan images.

Whole-body bone scan (WBS) is usually used as the effective diagnostic method for early-stage and comprehensive bone metastases of breast cancer. WBS ...

Large Language Models in peri-implant disease: How well do they perform?

STATEMENT OF PROBLEM: Artificial intelligence (AI) has gained significant recent attention and several AI applications, such as the Large Language Mod...

Automatic Segmentation of Bone Graft in Maxillary Sinus via Distance Constrained Network Guided by Prior Anatomical Knowledge.

Maxillary Sinus Lifting is a crucial surgical procedure for addressing insufficient alveolar bone mass andsevere resorption in dental implant therapy....

A deep learning framework for automated and generalized synaptic event analysis.

Quantitative information about synaptic transmission is key to our understanding of neural function. Spontaneously occurring synaptic events carry fun...

Detection of obstetric anal sphincter injuries using machine learning-assisted impedance spectroscopy: a prospective, comparative, multicentre clinical study.

To evaluate the clinical performance and safety of the ONIRY system for obstetric anal sphincter injuries (OASI) detection versus three-dimensional en...

Reliability and validity of a novel single-lead portable electrocardiogram device for pregnant women: a comparative study.

BACKGROUND: WenXinWuYang, a novel portable Artificial Intelligence Electrocardiogram (AI-ECG) device, can detect many kinds of abnormal heart disease ...

Rehabilitation of a Terminal Dentition Patient Using an Immediate Loading Protocol With a Virtual Patient-Assisted Workflow: A Case Report.

OBJECTIVES: To demonstrate the implementation of a digital workflow for the rehabilitation of a terminal dentition patient with complete-arch implant-...

OnmiMHC: a machine learning solution for UCEC tumor vaccine development through enhanced peptide-MHC binding prediction.

The key roles of Major Histocompatibility Complex (MHC) Class I and II molecules in the immune system are well established. This study aims to develop...

Using machine learning to predict deterioration of symptoms in COPD patients within a telemonitoring program.

COPD exacerbations have a profound clinical impact on patients. Accurately predicting these events could help healthcare professionals take proactive ...

SmartAPM framework for adaptive power management in wearable devices using deep reinforcement learning.

Wearable devices face a significant challenge in balancing battery life with performance, often leading to frequent recharging and reduced user satisf...

CECRel: A joint entity and relation extraction model for Chinese electronic medical records of coronary angiography via contrastive learning.

Entity and relation extraction from Chinese electronic medical records (EMRs) is a crucial foundation for constructing medical knowledge graphs and su...

Novel Robotic Balloon-Based Device for Wrist-Extension Therapy of Hemiparesis Stroke Patients.

Upper-limb paresis is one of the main complications after stroke. It is commonly associated with impaired wrist-extension function. Upper-limb paresis...

Machine Learning in Intravascular Ultrasound: Validating Automated Lesion Assessment for Complex Coronary Interventions.

BACKGROUND: Intravascular ultrasound (IVUS) is essential for assessing complex coronary lesions, but remains underutilized in part due to difficulties...

Disease diagnostics using machine learning of B cell and T cell receptor sequences.

Clinical diagnosis typically incorporates physical examination, patient history, various laboratory tests, and imaging studies but makes limited use o...