Devices and Vaccines

Performance of large language models in oral and maxillofacial surgery examinations.

This study aimed to determine the accuracy of large language models (LLMs) in answering oral and maxillofacial surgery (OMS) multiple choice questions. A total of 259 questions from the university's question bank were answered by the LLMs (GPT-3.5, GPT-4, Llama 2, Gemini, and Copilot). The scores per category as well as the total score out of 259 were recorded and evaluated, with the passing score...

A novel virtual robotic platform for controlling six degrees of freedom assistive devices with body-machine interfaces.

Body-machine interfaces (BoMIs)-systems that control assistive devices (e.g., a robotic manipulator) with a person's movements-offer a robust and non-invasive alternative to brain-machine interfaces for individuals with neurological injuries. However, commercially-available assistive devices offer more degrees of freedom (DOFs) than can be efficiently controlled with a user's residual motor functi...

A retrospective study of deep learning generalization across two centers and multiple models of X-ray devices using COVID-19 chest-X rays.

Generalization of deep learning (DL) algorithms is critical for the secure implementation of computer-aided diagnosis systems in clinical practice. Ho...

Improved classification of soil As contamination at continental scale: Resolving class imbalances using machine learning approach.

The identification of arsenic (As)-contaminated areas is an important prerequisite for soil management and reclamation. Although previous studies have...

Novel AI-based automated virtual implant placement: Artificial versus human intelligence.

OBJECTIVES: To assess quality, clinical acceptance, time-efficiency, and consistency of a novel artificial intelligence (AI)-driven tool for automated...

Deep learning-designed implant-supported posterior crowns: Assessing time efficiency, tooth morphology, emergence profile, occlusion, and proximal contacts.

OBJECTIVES: To compare implant supported crowns (ISCs) designed using deep learning (DL) software with those designed by a technician using convention...

Empowering standardization of cancer vaccines through ontology: enhanced modeling and data analysis.

BACKGROUND: The exploration of cancer vaccines has yielded a multitude of studies, resulting in a diverse collection of information. The heterogeneity...

A Paper-Based Multiplexed Serological Test to Monitor Immunity against SARS-COV-2 Using Machine Learning.

The rapid spread of SARS-CoV-2 caused the COVID-19 pandemic and accelerated vaccine development to prevent the spread of the virus and control the dis...

Applications of Machine Learning in Periodontology and Implantology: A Comprehensive Review.

Machine learning (ML) has led to significant advances in dentistry, easing the workload of professionals and improving the performance of various medi...

Deep learning-based approach for 3D bone segmentation and prediction of missing tooth region for dental implant planning.

Recent studies have shown that dental implants have high long-term survival rates, indicating their effectiveness compared to other treatments. Howeve...

Exploring the Impact of the Class on In-the-Wild Human Activity Recognition.

Monitoring activities of daily living (ADLs) plays an important role in measuring and responding to a person's ability to manage their basic physical ...

IoT-based monitoring system and air quality prediction using machine learning for a healthy environment in Cameroon.

This paper is aimed at developing an air quality monitoring system using machine learning (ML), Internet of Things (IoT), and other elements to predic...

Risk prediction of cholangitis after stent implantation based on machine learning.

The risk of cholangitis after ERCP implantation in malignant obstructive jaundice patients remains unknown. To develop models based on artificial inte...

A Machine Learning Approach to Identify Key Residues Involved in Protein-Protein Interactions Exemplified with SARS-CoV-2 Variants.

Human infection with the coronavirus disease 2019 (COVID-19) is mediated by the binding of the spike protein of the severe acute respiratory syndrome ...

Emergence of artificial intelligence for automating cone-beam computed tomography-derived maxillary sinus imaging tasks. A systematic review.

Cone-beam computed tomography (CBCT) imaging of the maxillary sinus is indispensable for implantologists, offering three-dimensional anatomical visual...

Machine learning in infectious diseases: potential applications and limitations.

Infectious diseases are a major threat for human and animal health worldwide. Artificial Intelligence (AI) combined algorithms including Machine Learn...

Accuracy of manual and artificial intelligence-based superimposition of cone-beam computed tomography with digital scan data, utilizing an implant planning software: A randomized clinical study.

OBJECTIVES: To investigate the accuracy of conventional and automatic artificial intelligence (AI)-based registration of cone-beam computed tomography...

Deep learning restores speech intelligibility in multi-talker interference for cochlear implant users.

Cochlear implants (CIs) do not offer the same level of effectiveness in noisy environments as in quiet settings. Current single-microphone noise reduc...

The relationship between design-based lateralization, humeral bearing design, polyethylene angle, and patient-related factors on surgical complications after reverse shoulder arthroplasty: a machine learning analysis.

BACKGROUND: Technological advancements in implant design and surgical technique have focused on diminishing complications and optimizing performance o...

Accuracy of artificial intelligence-based segmentation of the mandibular canal in CBCT.

OBJECTIVES: To investigate the accuracy of artificial intelligence (AI)-based segmentation of the mandibular canal, compared to the conventional manua...