Infectious Disease

Diagnostic Detection of H7N3 Low Pathogenicity Avian Influenza in a Commercial Game Bird Flock.

Low pathogenicity avian influenza (LPAI) H7N3 was diagnosed in a flock of commercially raised Japanese quail () breeder hens. The birds were submitted with an initial complaint of a drop in egg production and watery droppings. Initial PCR testing of the flock for avian influenza (AI) was negative; however, mortality started increasing drastically, prompting further examination and the submission o...

Developing a Deep Neural Network model for COVID-19 diagnosis based on CT scan images.

COVID-19 is most commonly diagnosed using a testing kit but chest X-rays and computed tomography (CT) scan images have a potential role in COVID-19 diagnosis. Currently, CT diagnosis systems based on Artificial intelligence (AI) models have been used in some countries. Previous research studies used complex neural networks, which led to difficulty in network training and high computation rates. He...

SEINN: A deep learning algorithm for the stochastic epidemic model.

Stochastic modeling predicts various outcomes from stochasticity in the data, parameters and dynamical system. Stochastic models are deemed more appro...

Perspectives on Computation in Plants.

Plants thrive in virtually all natural and human-adapted environments and are becoming popular models for developing robotics systems because of their...

Long-term SARS-CoV-2 neutralizing antibody level prediction using multimodal deep learning: A prospective cohort study on longitudinal data in Wuhan, China.

The ongoing epidemic of SARS-CoV-2 is taking a substantial financial and health toll on people worldwide. Assessing the level and duration of SARS-CoV...

Predictive overfitting in immunological applications: Pitfalls and solutions.

Overfitting describes the phenomenon where a highly predictive model on the training data generalizes poorly to future observations. It is a common co...

Achieving pan-microbiome biological insights via the dbBact knowledge base.

16S rRNA amplicon sequencing provides a relatively inexpensive culture-independent method for studying microbial communities. Although thousands of su...

Structural interaction fingerprints and machine learning for predicting and explaining binding of small molecule ligands to RNA.

Ribonucleic acids (RNAs) play crucial roles in living organisms and some of them, such as bacterial ribosomes and precursor messenger RNA, are targets...

TIMER is a Siamese neural network-based framework for identifying both general and species-specific bacterial promoters.

BACKGROUND: Promoters are DNA regions that initiate the transcription of specific genes near the transcription start sites. In bacteria, promoters are...

iAMPCN: a deep-learning approach for identifying antimicrobial peptides and their functional activities.

Antimicrobial peptides (AMPs) are short peptides that play crucial roles in diverse biological processes and have various functional activities agains...

Reinforcement learning relieves the vaccination dilemma.

The main goal of this paper is to study how a decision-making rule for vaccination can affect epidemic spreading by exploiting the Bush-Mosteller (BM)...

Immune Activation Modulation via Magnetically Localized Bacteria Based Micro/Bio Robot (BBMBR).

Understanding tumor's microenvironment is one of the key factors in the cancer therapy. Especially, from the perspective of immunotherapy, immune dese...

Deep Learning Empowered Fresnel-based Lensless Fluorescence Microscopy.

Miniaturized fluorescence microscopy has revolutionized the way neuroscientists study the brain in-vivo. Recent developments in computational lensless...

Revisiting Transfer Learning Method for Tuberculosis Diagnosis.

Transfer learning (TL) has been proven to be a good strategy for solving domain-specific problems in many deep learning (DL) applications. Typically, ...

Detecting Childhood Pneumonia Using Handcrafted and Deep Learning Cough Sound Features and Multilayer Perceptron.

Pneumonia is one of the leading causes of morbidity and mortality in children. This is especially true in resource poor regions lacking diagnostic fac...

Predicting Mortality in COVID-19 Patients Using 6 Machine Learning Algorithms.

In late 2019, COVID-19 appeared and has since spread worldwide as the new pandemic, causing more than 6 million deaths. In dealing with this global cr...

A Conversational Web-Based Chatbot to Disseminate COVID-19 Advisory Information.

Chatbots are computer programs which integrate Artificial Intelligence (AI) and Natural Language Processing (NLP) technologies to simulate human conve...

Application of Topic Modeling on Artificial Intelligence Studies as a Foundation to Develop Ethical Guidelines in African American Dementia Caregiving.

We applied natural language processing and topic modeling to publicly available abstracts and titles of 263 papers in the scientific literature mentio...

Deployment of machine learning algorithms to predict sepsis: systematic review and application of the SALIENT clinical AI implementation framework.

OBJECTIVE: To retrieve and appraise studies of deployed artificial intelligence (AI)-based sepsis prediction algorithms using systematic methods, iden...

Evolution of the newest diagnostic methods for COVID-19: a Chinese perspective.

Coronavirus disease 2019 (COVID-19) has continued to spread globally since late 2019, representing a formidable challenge to the world's healthcare sy...