Devices and Vaccines

Advancing clinical utility of artificial intelligence: lessons from developing a model to predict cochlear implant eligibility.

OBJECTIVES: To address the gap between artificial intelligence (AI) model development and clinical implementation by developing a machine-learning model to predict cochlear implant (CI) eligibility based on routine hearing tests, while illustrating 3 practical lessons: reformulation for clinical utility, selection of problem-specific metrics, and handling input data variability. MATERIALS AND METH...

Deviation From AI-Predicted Implant Sizes in Total Hip Arthroplasty Is Associated With Increased Complication Risk.

BACKGROUND: Patient characteristics may predict implant sizes in total hip arthroplasty (THA), but the clinical value and generalizability of such models remain uncertain. This study evaluated the accuracy and relevance of an artificial intelligence (AI)-driven prediction tool for THA sizing in a diverse population. METHODS: We retrospectively reviewed 2410 primary THAs at 2 academic hospitals (20...

Adaptive machine learning models for predictive maintenance in industrial internet of things (IIoT) systems.

The research examines how RL and DRL models can be used to enhance the prediction of maintenance needs in the IIoT setting. The purpose is to assess t...

Enhancing adverse drug event extraction and summarization for cancer drugs through large language models.

PURPOSE: Cancer treatments such as chemotherapy, targeted therapy, and immunotherapy can effectively combat malignant cells but frequently cause serio...

[Deep learning-based assessment of periodontal ligament area changes in maxillary central incisors under different orthodontic regimens using cone-beam CT images].

Objective: To investigate the differences in the changes of periodontal ligament area (PDLA) and related clinical indicators before and after maxillar...

Integrating Artificial Intelligence in Periodontal Diagnosis: A Comparative Evaluation of ChatGPT-4 and Dental Educators.

OBJECTIVE: As artificial intelligence (AI) tools gain traction in healthcare, their role in periodontal diagnostics remains largely unexplored. This s...

Dual-mode 0D/2D spatial asymmetry optoelectronic device enabled by in situ microzone femtosecond laser deposition.

To develop artificial intelligence and humanoid robotics, it is crucial to fabricate advanced vision systems with high efficiency and versatility. A k...

An Automated Framework for Mandibular Reconstruction: Evaluation and Clinical Application.

BACKGROUND: Mandibular reconstruction suffers from limitations in automation and objectivity. This study aimed to develop an automated framework to ad...

Machine learning framework for early detection of polio outbreaks from acute flaccid paralysis surveillance data.

Poliomyelitis remains a global public health concern despite remarkable progress toward eradication. The continued circulation of vaccine-derived poli...

Cross-Cultural Differences in Public Discourse on COVID-19 Vaccination in the United States and South Korea: Cross-Sectional Analysis Using Natural Language Processing.

BACKGROUND: The COVID-19 vaccine was introduced as a crucial tool to combat the pandemic. However, concerns about its effectiveness, side effects, and...

Phenotypic clustering of myocardial infarction complicated by out-of-hospital cardiac arrest using unsupervised machine learning.

BACKGROUND: Patients with myocardial infarction (MI) complicated by out-of-hospital cardiac arrest (OHCA) represent a heterogeneous population with va...

Assessment of socioeconomic and demographic risk factors for low birth weight using model-agnostic explainable ensembles.

BACKGROUND AND OBJECTIVE: Low birth weight (LBW) is a major global public health concern, strongly linked to neonatal morbidity and long-term health c...

Digital breast tomosynthesis and reading with artificial intelligence.

Digital breast tomosynthesis (DBT) increases sensitivity and specificity compared to digital mammography (DM) in the early detection of breast cancer....

Exploring the impact of reimbursement ratios on willingness to vaccinate: A mixed-effects modeling approach using panel data.

Vaccination remains one of the most cost-effective methods for disease prevention. However, utilization of self-paid vaccines, including EV71, varicel...

Automating Virtual Dental Implant Placement: Can AI Match Clinical Expertise?

OBJECTIVES: This study evaluated a validated artificial intelligence (AI) tool for virtual implant planning by comparing its performance with expert-p...

A hybrid SMOTE and Gaussian mixture model based optimized XGBoost framework for bipolar disorder detection.

The identification of bipolar disorder (BD), a severe psychiatric condition characterized by recurrent mood fluctuations, remains challenging due to s...

Potent efficacy of an NA-targeting antibody against a broad spectrum of H5N1 influenza viruses.

For nearly 30 years, Goose/Guangdong-derived highly pathogenic avian influenza H5N1 viruses have posed significant risks to economic stability, food s...

Interpretable machine learning model for predicting the risk of dysphagia in patients after cardiac surgery.

BACKGROUND: Dysphagia is recognized as one of the most common severe complications following cardiac surgery, with the potential to result in adverse ...

MedFusionT5: Cross-Modal Attention Boosts Semantic Quality and Reduces Hallucinations in Dental AI.

INTRODUCTION AND AIMS: Automated dental report generation faces significant challenges in multimodal fusion, often resulting in suboptimal semantic qu...

Optimization of drug diffusion in drug-eluting stents for coronary artery based on deep reinforcement learning.

Drug-eluting stents (DES) are extensively used to treat coronary artery disease, and improving their therapeutic efficacy remains a long-standing rese...