Devices and Vaccines

Integrating graph and reinforcement learning for vaccination strategies in complex networks.

Pandemics like COVID-19 have a huge impact on human society and the global economy. Vaccines are effective in the fight against these pandemics but often in limited supplies, particularly in the early stages. Thus, it is imperative to distribute such crucial public goods efficiently. Identifying and vaccinating key spreaders (i.e., influential nodes) is an effective approach to break down the viru...

Predictive modelling of linear growth faltering among pediatric patients with Diarrhea in Rural Western Kenya: an explainable machine learning approach.

INTRODUCTION: Stunting affects one-fifth of children globally with diarrhea accounting for an estimated 13.5% of stunting. Identifying risk factors for its precursor, linear growth faltering (LGF), is critical to designing interventions. Moreover, developing new predictive models for LGF using more recent data offers opportunity to enhance model accuracy, interpretability and capture new insights....

Integrating Interpretability in Machine Learning and Deep Neural Networks: A Novel Approach to Feature Importance and Outlier Detection in COVID-19 Symptomatology and Vaccine Efficacy.

In this study, we introduce a novel approach that integrates interpretability techniques from both traditional machine learning (ML) and deep neural n...

Machine learning-enhanced immunopeptidomics applied to T-cell epitope discovery for COVID-19 vaccines.

Next-generation T-cell-directed vaccines for COVID-19 focus on establishing lasting T-cell immunity against current and emerging SARS-CoV-2 variants. ...

LRMAHpan: a novel tool for multi-allelic HLA presentation prediction using Resnet-based and LSTM-based neural networks.

INTRODUCTION: The identification of peptides eluted from HLA complexes by mass spectrometry (MS) can provide critical data for deep learning models of...

-targeted AI-driven vaccines: a paradigm shift in gastric cancer prevention.

, a globally prevalent pathogen Group I carcinogen, presents a formidable challenge in gastric cancer prevention due to its increasing antimicrobial r...

A deep learning approach predicting the activity of COVID-19 therapeutics and vaccines against emerging variants.

Understanding which viral variants evade neutralization is crucial for improving antibody-based treatments, especially with rapidly evolving viruses l...

Performance of Artificial Intelligence Chatbots in Answering Clinical Questions on Japanese Practical Guidelines for Implant-based Breast Reconstruction.

BACKGROUND: Artificial intelligence (AI) chatbots, including ChatGPT-4 (GPT-4) and Grok-1 (Grok), have been shown to be potentially useful in several ...

DEEP LEARNING-DRIVEN SEGMENTATION OF DENTAL IMPLANTS AND PERI-IMPLANTITIS DETECTION IN ORTHOPANTOMOGRAPHS: A NOVEL DIAGNOSTIC TOOL.

INTRODUCTION AND OBJECTIVE: Dental implants are well-established for restoring partial or complete tooth loss, with osseointegration being essential f...

The translation of in-house imaging AI research into a medical device ensuring ethical and regulatory integrity.

This manuscript delineates the pathway from in-house research on Artificial Intelligence (AI) to the development of a medical device, addressing criti...

Advancement of post-market surveillance of medical devices leveraging artificial intelligence: Patient monitors case study.

BackgroundHealthcare institutions throughout the world rely on medical devices to provide their services reliably and effectively. However, medical de...

Revolutionizing cardiovascular disease classification through machine learning and statistical methods.

BACKGROUND: Cardiovascular diseases (CVDs) include abnormal conditions of the heart, diseased blood vessels, structural problems of the heart, and blo...

Gender disparities in rural motorcycle accidents: A neural network analysis of travel behavior impact.

Rural road accidents involving motorcycle riders present a formidable challenge to road safety globally. This study offers a comprehensive gender-base...

Comparison Between Conventional and Artificial Intelligence-Assisted Setup for Digital Implant Planning: Accuracy, Time-Efficiency, and User Experience.

OBJECTIVES: To investigate the reliability and time efficiency of the conventional compared to the automatic artificial intelligence (AI) segmentation...

AI-Aided Gait Analysis with a Wearable Device Featuring a Hydrogel Sensor.

Wearable devices have revolutionized real-time health monitoring, yet challenges persist in enhancing their flexibility, weight, and accuracy. This pa...

Convolutional neural network for colorimetric glucose detection using a smartphone and novel multilayer polyvinyl film microfluidic device.

Detecting glucose levels is crucial for diabetes patients as it enables timely and effective management, preventing complications and promoting overal...

Machine learning algorithms for prediction of measles one vaccination dropout among 12-23 months children in Ethiopia.

INTRODUCTION: Despite the availability of a safe and effective measles vaccine in Ethiopia, the country has experienced recurrent and significant meas...

Dynamic navigation-guided robotic placement of zygomatic implants.

OBJECTIVES: To assess the feasibility and accuracy of a new prototype robotic implant system for the placement of zygomatic implants in edentulous max...

Pterygoid implant-based maxillary full-arch rehabilitation using an autonomous robot system: A case report.

Pterygoid implant placement has been proven to be a viable option in full-arch implant rehabilitation for extremely atrophic maxillae. Nevertheless, t...

SNPs and blood inflammatory marker featured machine learning for predicting the efficacy of fluorouracil-based chemotherapy in colorectal cancer.

Fluorouracil-based chemotherapy responses in colorectal cancer (CRC) patients vary widely, highlighting the role of pharmacogenomics in developing bet...