Devices and Vaccines

3D printed biomimetic cochleae and machine learning co-modelling provides clinical informatics for cochlear implant patients.

Cochlear implants restore hearing in patients with severe to profound deafness by delivering electrical stimuli inside the cochlea. Understanding stimulus current spread, and how it correlates to patient-dependent factors, is hampered by the poor accessibility of the inner ear and by the lack of clinically-relevant in vitro, in vivo or in silico models. Here, we present 3D printing-neural network ...

Machine Learning-Based Single Cell and Integrative Analysis Reveals That Baseline mDC Predisposition Correlates With Hepatitis B Vaccine Antibody Response.

Vaccination to prevent infectious disease is one of the most successful public health interventions ever developed. And yet, variability in individual vaccine effectiveness suggests that a better mechanistic understanding of vaccine-induced immune responses could improve vaccine design and efficacy. We have previously shown that protective antibody levels could be elicited in a subset of recipient...

A systematic review of sutureless vascular anastomosis technologies.

Vascular anastomoses typically involve a handsewn technique requiring significant surgical training, expertise, and time. The aim of our systematic re...

Deep-Learning-Based CT Imaging in the Quantitative Evaluation of Chronic Kidney Diseases.

This study focused on the application of deep learning algorithms in the segmentation of CT images, so as to diagnose chronic kidney diseases accurate...

Automated segmentation by deep learning of loose connective tissue fibers to define safe dissection planes in robot-assisted gastrectomy.

The prediction of anatomical structures within the surgical field by artificial intelligence (AI) is expected to support surgeons' experience and cogn...

Efficient Prediction of Missed Clinical Appointment Using Machine Learning.

Public health and its related facilities are crucial for thriving cities and societies. The optimum utilization of health resources saves money and ti...

Should we replace radiologists with deep learning? Pigeons, error and trust in medical AI.

The sudden rise in the ability of machine learning methodology, such as deep neural networks, to identify and predict with great accuracy instances of...

Connecting MHC-I-binding motifs with HLA alleles via deep learning.

The selection of peptides presented by MHC molecules is crucial for antigen discovery. Previously, several predictors have shown impressive performanc...

Deep learning for bone marrow cell detection and classification on whole-slide images.

Bone marrow (BM) examination is an essential step in both diagnosing and managing numerous hematologic disorders. BM nucleated differential count (NDC...

Comparing the Prognostic Value of Stress Myocardial Perfusion Imaging by Conventional and Cadmium-Zinc Telluride Single-Photon Emission Computed Tomography through a Machine Learning Approach.

We compared the prognostic value of myocardial perfusion imaging (MPI) by conventional- (C-) single-photon emission computed tomography (SPECT) and ca...

A Deep Learning Approach for Predicting Antigenic Variation of Influenza A H3N2.

Modeling antigenic variation in influenza (flu) virus A H3N2 using amino acid sequences is a promising approach for improving the prediction accuracy ...

Development of a paper-based analytical device for the colourimetric detection of alanine transaminase and the application of deep learning for image analysis.

A paper-based colourimetric assay for the detection of alanine transaminase has been developed. In the presence of alanine transaminase, 2,4-dinitroph...

Development of monoclonal antibodies for quantification of bovine tumor necrosis factor-α.

The expression of the proinflammatory cytokine tumor necrosis factor-α (TNF-α) is associated with production losses in dairy cows and is a hallmark of...

SenSARS: A Low-Cost Portable Electrochemical System for Ultra-Sensitive, Near Real-Time, Diagnostics of SARS-CoV-2 Infections.

A critical path to solving the SARS-CoV-2 pandemic, without further socioeconomic impact, is to stop its spread. For this to happen, pre- or asymptoma...

Twisting and Braiding Fluid-Driven Soft Artificial Muscle Fibers for Robotic Applications.

Research on soft artificial muscles (SAMs) is rapidly growing, both in developing new actuation ideas and improving existing structures with multifunc...

Vertical Deviation Caused by Tightening Torque on Implant Scan Body: An In Vitro Study.

PURPOSE: This study evaluated the effects of manipulator level (ML) on implant scan body (ISB) seating. It also investigated ISB vertical deviation wi...

Automating classification of osteoarthritis according to Kellgren-Lawrence in the knee using deep learning in an unfiltered adult population.

BACKGROUND: Prevalence for knee osteoarthritis is rising in both Sweden and globally due to increased age and obesity in the population. This has subs...

A Novel Interference Avoidance Based on a Distributed Deep Learning Model for 5G-Enabled IoT.

The co-existence of fifth-generation (5G) and Internet-of-Things (IoT) has become inevitable in many applications since 5G networks have created stead...

Comparison of visibility of in-stent restenosis between conventional- and ultra-high spatial resolution computed tomography: coronary arterial phantom study.

PURPOSE: The purposes of this experimental study were to compare the quantitative and qualitative visibility of in-stent restenosis between convention...

An Agent-based Decision Support for a Vaccination Campaign.

We explore the Covid-19 diffusion with an agent-based model of an Italian region with a population on a scale of 1:1000. We also simulate different va...