Infectious Disease

DeepHisCoM: deep learning pathway analysis using hierarchical structural component models.

Many statistical methods for pathway analysis have been used to identify pathways associated with the disease along with biological factors such as genes and proteins. However, most pathway analysis methods neglect the complex nonlinear relationship between biological factors and pathways. In this study, we propose a Deep-learning pathway analysis using Hierarchical structured CoMponent models (De...

Prediction of HIV sensitivity to monoclonal antibodies using aminoacid sequences and deep learning.

MOTIVATION: Knowing the sensitivity of a viral strain versus a monoclonal antibody is of interest for HIV vaccine development and therapy. The HIV strains vary in their resistance to antibodies, and the accurate prediction of virus-antibody sensitivity can be used to find potent antibody combinations that broadly neutralize multiple and diverse HIV strains. Sensitivity prediction can be combined w...

DNAffinity: a machine-learning approach to predict DNA binding affinities of transcription factors.

We present a physics-based machine learning approach to predict in vitro transcription factor binding affinities from structural and mechanical DNA pr...

Lessons in machine learning model deployment learned from sepsis.

In three recent and related publications, researchers from Johns Hopkins University and Bayesian Health report results from implementing and prospecti...

Advances in the diagnosis of herpes simplex stromal necrotising keratitis: A feasibility study on deep learning approach.

PURPOSE: Infectious keratitis, especially viral keratitis (VK), in resource-limited settings, can be a challenge to diagnose and carries a high risk o...

Two-Phase Deep Learning Algorithm for Detection and Differentiation of Ewing Sarcoma and Acute Osteomyelitis in Paediatric Radiographs.

BACKGROUND/AIM: Ewing sarcoma is a highly malignant tumour predominantly found in children. The radiological signs of this malignancy can be mistaken ...

CNGOD-An improved convolution neural network with grasshopper optimization for detection of COVID-19.

The world is facing the pandemic situation due to a beta corona virus named Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). The disease ...

DeePVP: Identification and classification of phage virion proteins using deep learning.

BACKGROUND: Many biological properties of phages are determined by phage virion proteins (PVPs), and the poor annotation of PVPs is a bottleneck for m...

Construction of classification models for pathogenic bacteria based on LIBS combined with different machine learning algorithms.

Bacteria, especially foodborne pathogens, seriously threaten human life and health. Rapid discrimination techniques for foodborne pathogens are still ...

Comparative analysis of machine learning algorithms on the microbial strain-specific AMP prediction.

The evolution of drug-resistant pathogenic microbial species is a major global health concern. Naturally occurring, antimicrobial peptides (AMPs) are ...

Effector-GAN: prediction of fungal effector proteins based on pretrained deep representation learning methods and generative adversarial networks.

MOTIVATION: Phytopathogenic fungi secrete effector proteins to subvert host defenses and facilitate infection. Systematic analysis and prediction of c...

Same-Day Discharge Protocol for Robot-Assisted Radical Prostatectomy: Experience of a High-Volume Referral Center.

As the coronavirus disease 2019 (COVID-19) global pandemic continues, there is increased value in performing same-day discharge (SDD) protocols to mi...

Diagnosis of coronavirus disease 2019 and the potential role of deep learning: insights from the experience of Cairo University Hospitals.

OBJECTIVES: Early detection of coronavirus disease 2019 (COVID-19) is crucial for patients and public health to ensure pandemic control. We aimed to c...

A Cough-based deep learning framework for detecting COVID-19.

This paper presents a deep learning framework for detecting COVID-19 positive subjects from their cough sounds. In particular, the proposed approach c...

Wasserstein GAN based Chest X-Ray Dataset Augmentation for Deep Learning Models: COVID-19 Detection Use-Case.

The novel coronavirus infection (COVID-19) is still continuing to be a concern for the entire globe. Since early detection of COVID-19 is of particula...

Comparative Analysis of Current Deep Learning Networks for Breast Lesion Segmentation in Ultrasound Images.

Automatic lesion segmentation in breast ultrasound (BUS) images aids in the diagnosis of breast cancer, the most common type of cancer in women. Accur...

Joint Embedding of Structural and Functional Brain Networks with Graph Neural Networks for Mental Illness Diagnosis.

Multimodal brain networks characterize complex connectivities among different brain regions from both structural and functional aspects and provide a ...

Transfer Learning for Automated COVID-19 B-Line Classification in Lung Ultrasound.

Lung ultrasound (LUS) as a diagnostic tool is gaining support for its role in the diagnosis and management of COVID-19 and a number of other lung path...

Teleoperated Probe Manipulator for Prone-Position Echocardiography Examination.

Echocardiography probe manipulation is a strenuous task. During a procedure, the operator must hold the probe, extend their arm, bend their elbow, and...

Cerebral Palsy Prediction with Frequency Attention Informed Graph Convolutional Networks.

Early diagnosis and intervention are clinically con-sidered the paramount part of treating cerebral palsy (CP), so it is essential to design an effici...