Infectious Disease

The groundbreaking impact of digitalization and artificial intelligence in sheep farming.

The integration of digitalization and Artificial Intelligence (AI) has marked the onset of a new era of efficient sheep farming in multiple aspects ranging from the general well-being of sheep to advanced web-based management applications. The resultant improvement in sheep health and consequently better farming yield has already started to benefit both farmers and veterinarians. The predictive an...

Inference of annealed protein fitness landscapes with AnnealDCA.

The design of proteins with specific tasks is a major challenge in molecular biology with important diagnostic and therapeutic applications. High-throughput screening methods have been developed to systematically evaluate protein activity, but only a small fraction of possible protein variants can be tested using these techniques. Computational models that explore the sequence space in-silico to i...

Investigation of bacterial DNA gyrase Inhibitor classification models and structural requirements utilizing multiple machine learning methods.

Infections from multidrug-resistant (MDR) bacteria have emerged as a paramount global health concern, and the therapeutic effectiveness of current tre...

Application of artificial intelligence in diagnosis of pulmonary tuberculosis.

Combined substituent number utilized machine learning for the development of antimicrobial agent.

The utilization of machine learning has a potential to improve the environment of the development of antimicrobial agents. For practical use of machin...

Neuroimaging data repositories and AI-driven healthcare-Global aspirations vs. ethical considerations in machine learning models of neurological disease.

Neuroimaging data repositories are data-rich resources comprising brain imaging with clinical and biomarker data. The potential for such repositories ...

Immunization against inhibin DNA vaccine as an alternative therapeutic for improving follicle development and reproductive performance in beef cattle.

The objective of the present study was to investigate the potential role of immunization against INH on follicular development, serum reproductive hor...

Machine learning models to evaluate mortality in pediatric patients with pneumonia in the intensive care unit.

OBJECTIVES: This study aimed to predict mortality in children with pneumonia who were admitted to the intensive care unit (ICU) to aid decision-making...

Meta-lasso: new insight on infection prediction after minimally invasive surgery.

Surgical site infection (SSI) after minimally invasive lung cancer surgery constitutes an important factor influencing the direct and indirect economi...

Unlocking human-robot synergy: The power of intent communication in warehouse robotics.

As autonomous mobile robots (AMR) are introduced into workspace environments shared with people, effective human-robot communication is critical to th...

Efficient leukocytes detection and classification in microscopic blood images using convolutional neural network coupled with a dual attention network.

Leukocytes, also called White Blood Cells (WBCs) or leucocytes, are the cells that play a pivotal role in human health and are vital indicators of dis...

Low-force human-human hand interactions induce gait changes through sensorimotor engagement instead of direct mechanical effects.

Physical human-robot interactions (pHRI) often provide mechanical force and power to aid walking without requiring voluntary effort from the human. Al...

Anticandidal effectiveness of greenly synthesized zinc oxide nanoparticles against candidal pathogens.

Drug resistance of pathogenic candidal strains to conventional antifungal agents represents a significant health issue contributing to high morbidity ...

Drug-target identification in COVID-19 disease mechanisms using computational systems biology approaches.

INTRODUCTION: The COVID-19 Disease Map project is a large-scale community effort uniting 277 scientists from 130 Institutions around the globe. We use...

TB-DROP: deep learning-based drug resistance prediction of Mycobacterium tuberculosis utilizing whole genome mutations.

The most widely practiced strategy for constructing the deep learning (DL) prediction model for drug resistance of Mycobacterium tuberculosis (MTB) in...

Replication and Injury Associated With SARS-CoV-2 in Cultured Hepatocytes.

BACKGROUND: Liver dysfunction is one of the hallmarks of SARS-CoV-2 infection. The mechanism(s) of hepatic injury in SARS-CoV-2 infection remains cont...

Differential privacy preserved federated learning for prognostic modeling in COVID-19 patients using large multi-institutional chest CT dataset.

BACKGROUND: Notwithstanding the encouraging results of previous studies reporting on the efficiency of deep learning (DL) in COVID-19 prognostication,...

A high-speed microscopy system based on deep learning to detect yeast-like fungi cells in blood.

Blood-invasive fungal infections can cause the death of patients, while diagnosis of fungal infections is challenging. A high-speed microscopy detec...

Toward the novel AI tasks in infection biology.

Machine learning and artificial intelligence (AI) are becoming more common in infection biology laboratories around the world. Yet, as they gain tract...

Deep learning model to differentiate Crohn's disease from intestinal tuberculosis using histopathological whole slide images from intestinal specimens.

Crohn's disease (CD) and intestinal tuberculosis (ITB) share similar histopathological characteristics, and differential diagnosis can be a dilemma fo...