COVID-19

extract in combination with lytic phage cocktails: a promising therapeutic approach against biofilms of multi-drug resistant .

Antimicrobial resistance (AMR) poses a significant global threat to public health systems, rendering antibiotics ineffective in treating infectious diseases. Combined use of bio compounds, including bacteriophages and plant extracts, is an attractive approach to controlling antibiotic resistance. In this study, the combination of phage cocktail (Isf-Pm1 and Isf-Pm2) and crude extract (AME) was in...

Evaluating generative artificial intelligence's limitations in health policy identification and interpretation.

Policy epidemiology utilizes human subject-matter experts (SMEs) to systematically surface, analyze, and categorize legally-enforceable policies. The Analysis and Mapping of Policies for Emerging Infectious Diseases project systematically collects and assesses health-related policies from all United Nations Member States. The recent proliferation of generative artificial intelligence (GAI) tools p...

The native Iranian soil bacteria with high potential to produce extracellular methionine gamma-lyase.

This study aimed to screen native methionine gamma-lyase (L-methioninase) producing bacteria from soil samples and optimize the culture media for enha...

Generative Adversarial Network-Based Augmentation With Noval 2-Step Authentication for Anti-Coronavirus Peptide Prediction.

The virus poses a longstanding and enduring danger to various forms of life. Despite the ongoing endeavors to combat viral diseases, there exists a ne...

Automatic identification of clinically important species by artificial intelligence-based image recognition: proof-of-concept study.

While morphological examination is the most widely used for identification in clinical laboratories, PCR-sequencing and MALDI-TOF MS are emerging tec...

Comparative study of DCNN and image processing based classification of chest X-rays for identification of COVID-19 patients using fine-tuning.

The conventional detection of COVID-19 by evaluating the CT scan images is tiresome, often experiences high inter-observer variability and uncertainty...

Ensemble intelligence prediction algorithms and land use scenarios to measure carbon emissions of the Yangtze River Delta: A machine learning model based on Long Short-Term Memory.

Land use in urban agglomerations is the main source of carbon emissions, and reducing them and improving land use efficiency are the keys to achieving...

Genomic analysis, culturing optimization, and characterization of bacteriophage OSYSP, previously studied as effective pathogen control on fresh produce.

Advances in bacteriophage genome sequencing and regulatory approvals of some bacteriophages in various applications have renewed interest in these ant...

Integrating Sentinel-1 data and machine learning for effective paddy field monitoring in Cauvery Delta Zone, Tamil Nadu, India.

Paddy crop mapping is essential for agricultural monitoring, ensuring food security, and enhancing resource allocation. This study observes the Cauver...

UDA-GS: A cross-center multimodal unsupervised domain adaptation framework for Glioma segmentation.

Gliomas are the most common and malignant form of primary brain tumors. Accurate segmentation and measurement from MRI are crucial for diagnosis and t...

Enhancing groundwater quality prediction through ensemble machine learning techniques.

Groundwater quality is assessed by conducting water sampling and laboratory analysis. Field-based measurements are costly and time-consuming. This stu...

Detection of Apple Proliferation Disease Using Hyperspectral Imaging and Machine Learning Techniques.

Apple proliferation is among the most important diseases in European fruit production. Early and reliable detection enables farmers to respond appropr...

Identification of ageing-associated gene signatures in heart failure with preserved ejection fraction by integrated bioinformatics analysis and machine learning.

The incidence of heart failure with preserved ejection fraction (HFpEF) increases with the ageing of populations. This study aimed to explore ageing-a...

Semantic Mask Reconstruction and Category Semantic Learning for few-shot image generation.

Few-shot image generation aims at generating novel images for the unseen category when given K images from the same category. Despite significant adva...

MIRD Pamphlet No. 31: MIRDcell V4-Artificial Intelligence Tools to Formulate Optimized Radiopharmaceutical Cocktails for Therapy.

Radiopharmaceutical cocktails have been developed over the years to treat cancer. Cocktails of agents are attractive because 1 radiopharmaceutical is ...

Artificial intelligence enabled smart mask for speech recognition for future hearing devices.

In recent years, Lip-reading has emerged as a significant research challenge. The aim is to recognise speech by analysing Lip movements. The majority ...

MNet: A multi-scale network for visible watermark removal.

Superimposing visible watermarks on images is an efficient way to indicate ownership and prevent potential unauthorized use. Visible watermark removal...

Identification of diagnostic biomarkers and molecular subtype analysis associated with m6A in Tuberculosis immunopathology using machine learning.

Tuberculosis (TB), ranking just below COVID-19 in global mortality, is a highly complex infectious disease involving intricate immunological molecules...

Accurate Lung Nodule Segmentation With Detailed Representation Transfer and Soft Mask Supervision.

Accurate lung lesion segmentation from computed tomography (CT) images is crucial to the analysis and diagnosis of lung diseases, such as COVID-19 and...

Applications of Artificial Intelligence in Choroid Visualization for Myopia: A Comprehensive Scoping Review.

Numerous artificial intelligence (AI) models, including deep learning techniques, are being developed to segment choroids in optical coherence tomogra...