Infectious Disease

A Bias Network Approach (BNA) to Encourage Ethical Reflection Among AI Developers.

We introduce the Bias Network Approach (BNA) as a sociotechnical method for AI developers to identify, map, and relate biases across the AI development process. This approach addresses the limitations of what we call the "isolationist approach to AI bias," a trend in AI literature where biases are seen as separate occurrences linked to specific stages in an AI pipeline. Dealing with these multiple...

Standardized evaluation of diabetic retinopathy using artificial intelligence and its association with metabolic dysfunction-associated steatotic liver disease in Japan: A cross-sectional study.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is common in patients with obesity and diabetes and can lead to serious complications. This study aimed to evaluate fundus photographs using artificial intelligence to explore the relationships between diabetic retinopathy (DR), MASLD, and related factors. In this cross-sectional study, we included 1,736 patients with a history of di...

Efficacy evaluation of a minimally invasive surgical procedure (oblique lateral interbody fusion) for lumbar spinal tuberculosis-retrospective cohort study.

OBJECTIVE: In the current study, to demonstrate the advantages of oblique lateral interbody fusion (OLIF), we focused on the therapeutics for lumbar s...

Sustainable integration of artificial intelligence and machine learning approaches within the African infectious disease vaccine research and development ecosystem.

Artificial Intelligence and Machine Learning (AI/ML) techniques, including reverse vaccinology and predictive models, have already been applied for de...

Policy brief: Improving national vaccination decision-making through data.

Life course immunisation looks at the broad value of vaccination across multiple generations, calling for more data power, collaboration, and multi-di...

A novel recommender framework with chatbot to stratify heart attack risk.

Cardiovascular diseases are a major cause of mortality and morbidity. Fast detection of life-threatening emergency events and an earlier start of the ...

Coffee Leaf Rust Disease Detection and Implementation of an Edge Device for Pruning Infected Leaves via Deep Learning Algorithms.

Global warming and extreme climate conditions caused by unsuitable temperature and humidity lead to coffee leaf rust () diseases in coffee plantations...

DFASGCNS: A prognostic model for ovarian cancer prediction based on dual fusion channels and stacked graph convolution.

Ovarian cancer is a malignant tumor with different clinicopathological and molecular characteristics. Due to its nonspecific early symptoms, the major...

Mandatory surveillance of bacteremia conducted by automated monitoring.

Except for a few countries, comprehensive all-cause surveillance for bacteremia is not part of mandatory routine public health surveillance. We argue ...

Investigation of the efficiency of different reprocessing methods on disposable laryngeal masks contaminated with HBV DNA.

BACKGROUND: The use of laryngeal masks (LM) has increased widely today, both in anesthesia and in emergency cases. LM are available as reusable and di...

Analysis of HIV infection among voluntary blood donors based on HIV ELISA and nucleic acid detection.

OBJECTIVE: To analyze the epidemiological characteristics of human immunodeficiency virus (HIV) infection among voluntary blood donors and provide a f...

Diagnosis of Fibrotic Interstitial Lung Diseases Based on the Combination of Label-Free Quantitative Multiphoton Fiber Histology and Machine Learning.

Interstitial lung disease (ILD), characterized by inflammation and fibrosis, often suffers from low diagnostic accuracy and consistency. Traditional h...

Machine learning-based predictive models for perioperative major adverse cardiovascular events in patients with stable coronary artery disease undergoing noncardiac surgery.

BACKGROUND AND OBJECTIVE: Accurate prediction of perioperative major adverse cardiovascular events (MACEs) is crucial, as it not only aids clinicians ...

Exploratory study of extracellular matrix biomarkers for non-invasive liver fibrosis staging: A machine learning approach with XGBoost and explainable AI.

BACKGROUND: Novel circulating markers for the non-invasive staging of chronic liver disease (CLD) are in high demand. Although underutilized, extracel...

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 di...

Harnessing lactic acid bacteria for nicotinamide mononucleotide biosynthesis: a review of strategies and future directions.

Nicotinamide mononucleotide (NMN), one of the crucial precursors of nicotinamide adenine dinucleotide, has garnered considerable interest for its phar...

The application of machine learning algorithms for predicting length of stay before and during the COVID-19 pandemic: evidence from Wuhan-area hospitals.

OBJECTIVE: The COVID-19 pandemic has placed unprecedented strain on healthcare systems, mainly due to the highly variable and challenging to predict p...

Onset and long-term duration of immunity provided by a single vaccination with recombinant a Marek's disease virus with REV-LTR insertion.

Marek's Disease (MD), caused by Marek's disease virus (MDV), is a highly contagious lymphoproliferative disease in poultry. Despite the fact that MD h...

Antibacterial Activity of Crude , , and Methanolic Extracts on serovar Manilae.

BACKGROUND AND OBJECTIVE: Leptospirosis is a disease caused by pathogenic prevalent in tropical countries like the Philippines. Some studies have sho...

Ensemble learning based on bi-directional gated recurrent unit and convolutional neural network with word embedding module for bioactive peptide prediction.

Bioactive peptides, as small protein fragments, are essential mediators of diverse physiological activities, such as antimicrobial, anti-inflammatory,...