COVID-19

Use of CT and artificial intelligence in suspected or COVID-19 positive patients: statement of the Italian Society of Medical and Interventional Radiology.

The COVID-19 pandemic started in Italy in February 2020 with an exponential growth that has exceeded the number of cases reported in China. Italian radiology departments found themselves at the forefront in the management of suspected and positive COVID cases, both in diagnosis, in estimating the severity of the disease and in follow-up. In this context SIRM recommends chest X-ray as first-line im...

Artificial Intelligence Augmentation of Radiologist Performance in Distinguishing COVID-19 from Pneumonia of Other Origin at Chest CT.

Background Coronavirus disease 2019 (COVID-19) and pneumonia of other diseases share similar CT characteristics, which contributes to the challenges in differentiating them with high accuracy. Purpose To establish and evaluate an artificial intelligence (AI) system for differentiating COVID-19 and other pneumonia at chest CT and assessing radiologist performance without and with AI assistance. Mat...

Classification of COVID-19 patients from chest CT images using multi-objective differential evolution-based convolutional neural networks.

Early classification of 2019 novel coronavirus disease (COVID-19) is essential for disease cure and control. Compared with reverse-transcription polym...

ASAP-SML: An antibody sequence analysis pipeline using statistical testing and machine learning.

Antibodies are capable of potently and specifically binding individual antigens and, in some cases, disrupting their functions. The key challenge in g...

Combination Strategies for Immune-Checkpoint Blockade and Response Prediction by Artificial Intelligence.

The therapeutic concept of unleashing a pre-existing immune response against the tumor by the application of immune-checkpoint inhibitors (ICI) has re...

Caregiver perspectives on a smart home-based socially assistive robot for individuals with Alzheimer's disease and related dementia.

: Innovative assistive technology can address aging-in-place and caregiving needs of individuals with Alzheimer's disease and related dementia (ADRD)....

Predicting COVID-19 Incidence Through Analysis of Google Trends Data in Iran: Data Mining and Deep Learning Pilot Study.

BACKGROUND: The recent global outbreak of coronavirus disease (COVID-19) is affecting many countries worldwide. Iran is one of the top 10 most affecte...

DeLTA: Automated cell segmentation, tracking, and lineage reconstruction using deep learning.

Microscopy image analysis is a major bottleneck in quantification of single-cell microscopy data, typically requiring human oversight and curation, wh...

Abdominal multi-organ auto-segmentation using 3D-patch-based deep convolutional neural network.

Segmentation of normal organs is a critical and time-consuming process in radiotherapy. Auto-segmentation of abdominal organs has been made possible b...

Generative adversarial networks with decoder-encoder output noises.

In recent years, research on image generation has been developing very fast. The generative adversarial network (GAN) emerges as a promising framework...

Predicting the short-term success of human influenza virus variants with machine learning.

Seasonal influenza viruses are constantly changing and produce a different set of circulating strains each season. Small genetic changes can accumulat...

A Machine Learning Approach for High-Dimensional Time-to-Event Prediction With Application to Immunogenicity of Biotherapies in the ABIRISK Cohort.

Predicting immunogenicity for biotherapies using patient and drug-related factors represents nowadays a challenging issue. With the growing ability to...

Covid-19: automatic detection from X-ray images utilizing transfer learning with convolutional neural networks.

In this study, a dataset of X-ray images from patients with common bacterial pneumonia, confirmed Covid-19 disease, and normal incidents, was utilized...

LEAP: Using machine learning to support variant classification in a clinical setting.

Advances in genome sequencing have led to a tremendous increase in the discovery of novel missense variants, but evidence for determining clinical sig...

Extension of Coronavirus Disease 2019 on Chest CT and Implications for Chest Radiographic Interpretation.

PURPOSE: To study the extent of pulmonary involvement in coronavirus 19 (COVID-19) with quantitative CT and to assess the impact of disease burden on ...

How could artificial intelligence aid in the fight against coronavirus?

Environmental Noise Classification Using Convolutional Neural Networks with Input Transform for Hearing Aids.

Hearing aids are essential for people with hearing loss, and noise estimation and classification are some of the most important technologies used in d...

Automated detection algorithm for C4d immunostaining showed comparable diagnostic performance to pathologists in renal allograft biopsy.

A deep learning-based image analysis could improve diagnostic accuracy and efficiency in pathology work. Recently, we proposed a deep learning-based d...

DeepMILO: a deep learning approach to predict the impact of non-coding sequence variants on 3D chromatin structure.

Non-coding variants have been shown to be related to disease by alteration of 3D genome structures. We propose a deep learning method, DeepMILO, to pr...

An Intelligent Optimization Algorithm for Constructing a DNA Storage Code: NOL-HHO.

The high density, large capacity, and long-term stability of DNA molecules make them an emerging storage medium that is especially suitable for the lo...