COVID-19

Deep learning in forensic gunshot wound interpretation-a proof-of-concept study.

While the applications of deep learning are considered revolutionary within several medical specialties, forensic applications have been scarce despite the visual nature of the field. For example, a forensic pathologist may benefit from deep learning-based tools in gunshot wound interpretation. This proof-of-concept study aimed to test the hypothesis that trained neural network architectures have ...

Distinguishing between recent balancing selection and incomplete sweep using deep neural networks.

Balancing selection is an important adaptive mechanism underpinning a wide range of phenotypes. Despite its relevance, the detection of recent balancing selection from genomic data is challenging as its signatures are qualitatively similar to those left by ongoing positive selection. In this study, we developed and implemented two deep neural networks and tested their performance to predict loci u...

Prediction of PCR amplification from primer and template sequences using recurrent neural network.

We have developed a novel method to predict the success of PCR amplification for a specific primer set and DNA template based on the relationship betw...

Semi-supervised learning for an improved diagnosis of COVID-19 in CT images.

Coronavirus disease 2019 (COVID-19) has been spread out all over the world. Although a real-time reverse-transcription polymerase chain reaction (RT-P...

Machine learning is the key to diagnose COVID-19: a proof-of-concept study.

The reverse transcription-polymerase chain reaction (RT-PCR) assay is the accepted standard for coronavirus disease 2019 (COVID-19) diagnosis. As any ...

Machine Learning as a Precision-Medicine Approach to Prescribing COVID-19 Pharmacotherapy with Remdesivir or Corticosteroids.

PURPOSE: Coronavirus disease-2019 (COVID-19) continues to be a global threat and remains a significant cause of hospitalizations. Recent clinical guid...

Automated optimization of double heater convective polymerase chain reaction devices based on CFD simulation database and artificial neural network model.

This paper presents a framework for automated optimization of double-heater convective PCR (DH-cPCR) devices by developing a computational fluid dynam...

Graph of graphs analysis for multiplexed data with application to imaging mass cytometry.

Imaging Mass Cytometry (IMC) combines laser ablation and mass spectrometry to quantitate metal-conjugated primary antibodies incubated in intact tumor...

Using the antibody-antigen binding interface to train image-based deep neural networks for antibody-epitope classification.

High-throughput B-cell sequencing has opened up new avenues for investigating complex mechanisms underlying our adaptive immune response. These techno...

Attention-Based Temporal Encoding Network with Background-Independent Motion Mask for Action Recognition.

Convolutional neural network (CNN) has been leaping forward in recent years. However, the high dimensionality, rich human dynamic characteristics, and...

Mask-Guided Attention Network and Occlusion-Sensitive Hard Example Mining for Occluded Pedestrian Detection.

Pedestrian detection relying on deep convolution neural networks has made significant progress. Though promising results have been achieved on standar...

AI-assisted tracking of worldwide non-pharmaceutical interventions for COVID-19.

The Coronavirus disease 2019 (COVID-19) global pandemic has transformed almost every facet of human society throughout the world. Against an emerging,...

Prognostication of patients with COVID-19 using artificial intelligence based on chest x-rays and clinical data: a retrospective study.

BACKGROUND: Chest x-ray is a relatively accessible, inexpensive, fast imaging modality that might be valuable in the prognostication of patients with ...

Deep learning diagnostic and risk-stratification pattern detection for COVID-19 in digital lung auscultations: clinical protocol for a case-control and prospective cohort study.

BACKGROUND: Lung auscultation is fundamental to the clinical diagnosis of respiratory disease. However, auscultation is a subjective practice and inte...

Combining a parallel 2D CNN with a self-attention Dilated Residual Network for CTC-based discrete speech emotion recognition.

A challenging issue in the field of the automatic recognition of emotion from speech is the efficient modelling of long temporal contexts. Moreover, w...

Disentangling the Contribution of Each Descriptive Characteristic of Every Single Mutation to Its Functional Effects.

Mutational effects predictions continue to improve in accuracy as advanced artificial intelligence (AI) algorithms are trained on exhaustive experimen...

Machine learning-based reclassification of germline variants of unknown significance: The RENOVO algorithm.

The increasing scope of genetic testing allowed by next-generation sequencing (NGS) dramatically increased the number of genetic variants to be interp...

The characteristics and evolution of pulmonary fibrosis in COVID-19 patients as assessed by AI-assisted chest HRCT.

The characteristics and evolution of pulmonary fibrosis in patients with coronavirus disease 2019 (COVID-19) have not been adequately studied. AI-assi...

A Few-Shot U-Net Deep Learning Model for COVID-19 Infected Area Segmentation in CT Images.

Recent studies indicate that detecting radiographic patterns on CT chest scans can yield high sensitivity and specificity for COVID-19 identification....

Hyperparameter Optimization for COVID-19 Pneumonia Diagnosis Based on Chest CT.

Convolutional Neural Networks (CNNs) have been successfully applied in the medical diagnosis of different types of diseases. However, selecting the ar...