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Medical literature

Publications associées (32)

Iron-carbohydrate complexes treating iron anaemia: Understanding the nano-structure and interactions with proteins through orthogonal characterisation

Antonia Neels, Marianne Liebi, Tiberiu Totu

Intravenous (IV) iron-carbohydrate complexes are widely used nanoparticles (NPs) to treat iron deficiency anaemia, often associated with medical conditions such as chronic kidney disease, heart failure and various inflammatory conditions. Even though a ple ...

Elsevier2024

Classification of patients with cardiac amyloidosis using machine learning models on Italian electronic clinical health records

Silvestro Micera, Sara Mazzucato

Amyloidosis refers to a range of medical conditions in which misshapen proteins accumulate in various organs and tissues, forming insoluble fibrils. Cardiac amyloidosis is frequently linked to the buildup of misfolded transthyretin (TTR) or immunoglobulin ...

New York2023

From Nano to Macro An overview of the IEEE Bio Image and Signal Processing Technical Committee

Michaël Unser, Dimitri Nestor Alice Van De Ville, Michael Stefan Daniel Liebling

The Bio Image and Signal Processing (BISP) Technical Committee (TC) of the IEEE Signal Processing Society (SPS) promotes activities within the broad technical field of biomedical image and signal processing. Areas of interest include medical and biological ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

Explainability as fig leaf? An exploration of experts’ ethical expectations towards machine learning in psychiatry

The increasing implementation of programs supported by machine learning in medical contexts will affect psychiatry. It is crucial to accompany this development with careful ethical considerations informed by empirical research involving experts from the fi ...

2023

Machine learning and its impact on psychiatric nosology: Findings from a qualitative study among German and Swiss experts

The increasing integration of Machine Learning (ML) techniques into clinical care, driven in particular by Deep Learning (DL) using Artificial Neural Nets (ANNs), promises to reshape medical practice on various levels and across multiple medical fields. Mu ...

2023

Medical and Personal Characteristics Can Predict the Risk of Lung Metastasis

Michele De Palma, Nahal Mansouri

Aims: Understanding the correlations between underlying medical and personal characteristics of a patient with cancer and the risk of lung metastasis may improve clinical management and outcomes. We used machine learning methodologies to predict the risk o ...

2023

A Rapidly Responsive Sensor for Wireless Detection of Early and Mature Microbial Biofilms

Hubert Girault, Wanderson Oliveira Da Silva, Andreas Stephan Lesch, Bhawna Nagar

Biofilm-associated infections, which are able to resist antibiotics, pose a significant challenge in clinical treatments. Such infections have been linked to various medical conditions, including chronic wounds and implant-associated infections, making the ...

WILEY-V C H VERLAG GMBH2023

Design and Preparation of Sensing Surfaces for Capacitive Biodetection

Sandrine Gerber, Perrine Agnes Edith Robin

Despite their high sensitivity and their suitability for miniaturization, biosensors are still limited for clinical applications due to the lack of reproducibility and specificity of their detection performance. The design and preparation of sensing surfac ...

2022

Gel-Free Wearable Electroencephalography (EEG) with Soft Graphene Textiles

Ata Jedari Golparvar

Attaching rigid wearables to ones skin may be socially challenging to be accustomed since their wearers may feel vulnerable with compromising their privacy, especially if the device is for tracking neurological or medical conditions. The development of fle ...

IEEE2021

MedCo(2): Privacy-Preserving Cohort Exploration and Analysis

Jean-Pierre Hubaux, Juan Ramón Troncoso-Pastoriza, Jean Louis Raisaro, David Jules Froelicher, Mickaël Misbach

Medical studies are usually time consuming, cumbersome and extremely costly to perform, and for exploratory research, their results are also difficult to predict a priori. This is particularly the case for rare diseases, for which finding enough patients i ...

IOS PRESS2020

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