Devices and Vaccines

An architecture for COVID-19 analysis and detection using big data, AI, and data architectures.

The COVID-19 epidemic is affecting individuals in many ways and continues to spread all over the world. Vaccines and traditional medical techniques are still being researched. In diagnosis and therapy, biological and digital technology is used to overcome the fear of this disease. Despite recovery in many patients, COVID-19 does not have a definite cure or a vaccine that provides permanent protect...

Mass Spectrometric and Artificial Intelligence-Based Identification of the Secretome of Plasmodium falciparum Merozoites to Provide Novel Candidates for Vaccine Development Pipeline.

PURPOSE: Merozoites are the only extracellular form of blood stage parasites, making it a worthwhile target. Multiple invasins that are stored in the merozoite apical organelles, are secreted just prior to invasion, and mediates its interaction with RBC. A comprehensive identification of all these secreted invasins is lacking and this study addresses that gap.

COVID-19 prevention and control effect of non-pharmaceutical interventions-fuzzy-sets qualitative comparative analysis based on 69 countries in the world.

INTRODUCTION: Coronavirus disease 2019 occurred unexpectedly in late December 2019, it was difficult to immediately develop an effective vaccine or pr...

BiRNN-DDI: A Drug-Drug Interaction Event Type Prediction Model Based on Bidirectional Recurrent Neural Network and Graph2Seq Representation.

Research on drug-drug interaction (DDI) prediction, particularly in identifying DDI event types, is crucial for understanding adverse drug reactions a...

Comprehensive review of deep learning in orthopaedics: Applications, challenges, trustworthiness, and fusion.

Deep learning (DL) in orthopaedics has gained significant attention in recent years. Previous studies have shown that DL can be applied to a wide vari...

Neural activity shaping in visual prostheses with deep learning.

The visual perception provided by retinal prostheses is limited by the overlapping current spread of adjacent electrodes. This reduces the spatial res...

Reliable prediction of implant size and axial alignment in AI-based 3D preoperative planning for total knee arthroplasty.

The size and axial alignment of prostheses, when planned during total knee replacement (TKA) are critical for recovery of knee function and improvemen...

Artificial Intelligence-Enabled Electrocardiography Predicts Future Pacemaker Implantation and Adverse Cardiovascular Events.

Medical advances prolonging life have led to more permanent pacemaker implants. When pacemaker implantation (PMI) is commonly caused by sick sinus syn...

Deep learning reconstruction for coronary CT angiography in patients with origin anomaly, stent or bypass graft.

PURPOSE: To develop and validate a deep learning (DL)-model for automatic reconstruction for coronary CT angiography (CCTA) in patients with origin an...

Development of a machine learning approach for prediction of red blood cell transfusion in patients undergoing Cesarean section at a single institution.

Despite recent advances in surgical techniques and perinatal management in obstetrics for reducing intraoperative bleeding, blood transfusion may occu...

Construction of a clinical prediction model for complicated appendicitis based on machine learning techniques.

Acute appendicitis is a typical surgical emergency worldwide and one of the common causes of surgical acute abdomen in the elderly. Accurately diagnos...

Leveraging artificial intelligence in vaccine development: A narrative review.

Vaccine development stands as a cornerstone of public health efforts, pivotal in curbing infectious diseases and reducing global morbidity and mortali...

Advancing medical imaging: detecting polypharmacy and adverse drug effects with Graph Convolutional Networks (GCN).

Polypharmacy involves an individual using many medications at the same time and is a frequent healthcare technique used to treat complex medical disor...

AI as a Medical Device Adverse Event Reporting in Regulatory Databases: Protocol for a Systematic Review.

BACKGROUND: The reporting of adverse events (AEs) relating to medical devices is a long-standing area of concern, with suboptimal reporting due to a r...

Enhancing agriculture through real-time grape leaf disease classification via an edge device with a lightweight CNN architecture and Grad-CAM.

Crop diseases can significantly affect various aspects of crop cultivation, including crop yield, quality, production costs, and crop loss. The utiliz...

Vaccine design and development: Exploring the interface with computational biology and AI.

Computational biology involves applying computer science and informatics techniques in biology to understand complex biological data. It allows us to ...

Accuracy of artificial intelligence in implant dentistry: A scoping review with systematic evidence mapping.

STATEMENT OF PROBLEM: The use of artificial intelligence (AI) in dentistry has grown. However, the accuracy of clinical applications in implant dentis...

A comprehensive investigation of morphological features responsible for cerebral aneurysm rupture using machine learning.

Cerebral aneurysms are a silent yet prevalent condition that affects a significant global population. Their development can be attributed to various f...

Utilizing Deep Feature Fusion for Automatic Leukemia Classification: An Internet of Medical Things-Enabled Deep Learning Framework.

Acute lymphoblastic leukemia, commonly referred to as ALL, is a type of cancer that can affect both the blood and the bone marrow. The process of diag...

Artificial intelligence and mixed reality for dental implant planning: A technical note.

AIM: The aim of this work is to present a new protocol for implant surgical planning which involves the combined use of artificial intelligence (AI) a...