Latest AI and machine learning research in infectious disease for healthcare professionals.
BACKGROUND: Tuberculosis (TB) kills approximately 1.6 million people yearly despite the fact anti-TB drugs are generally curative. Therefore, TB-case detection and monitoring of therapy, need a comprehensive approach. Automated radiological analysis, combined with clinical, microbiological, and immunological data, by machine learning (ML), can help achieve it.
Antibiotic resistance is recognized as an imminent and growing global health threat. New antimicrobial drugs are urgently needed due to the decreasing effectiveness of conventional small-molecule antibiotics. Antimicrobial peptides (AMPs), a class of host defense peptides, are emerging as promising candidates to address this need. The potential sequence space of amino acids is combinatorially vast...
The emergence of Large Language Models (LLMs) has significantly impacted the field of Natural Language Processing and has transformed conversational...
Over the last ten years, the US Centers for Disease Control and Prevention (CDC) has organized an annual influenza forecasting challenge with the mo...
Engineering enzyme-substrate binding pockets is the most efficient approach for modifying catalytic activity, but is limited if the substrate binding ...
Bacteriophages are the viruses that infect bacterial cells. They are the most diverse biological entities on earth and play important roles in microbi...
Navigating the complex landscape of high-dimensional omics data with machine learning models presents a significant challenge. The integration of biol...
Target identification is one of the crucial tasks in drug research and development, as it aids in uncovering the action mechanism of herbs/drugs and d...
Therapeutic antibody design has garnered widespread attention, highlighting its interdisciplinary importance. Advancements in technology emphasize the...
Sepsis is the leading cause of in-hospital mortality in the USA. Early sepsis onset prediction and diagnosis could significantly improve the surviva...
As the aging process accelerates, the incidence of chronic diseases in the elderly is rising. As a result, it is crucial to optimize health education ...
A As health technology advances, this study aims to develop an innovative nutritional intake management system that integrates artificial intelligence...
Acute stroke demands prompt diagnosis and treatment to achieve optimal patient outcomes. However, the intricate and irregular nature of clinical dat...
In recent years, healthcare professionals are increasingly emphasizing on personalized and evidence-based patient care through the exploration of pr...
The AIDS epidemic has killed 40 million people and caused serious global problems. The identification of new HIV-inhibiting molecules is of great im...
This integrated study combines bioinformatics, machine learning, and Mendelian randomization (MR) to discover and validate molecular biomarkers for se...
A vaccine passport serves as documentary proof, providing passport holders with greater freedom while roaming around during pandemics. It confirms v...
Gram staining has been one of the most frequently used staining protocols in microbiology for over a century, utilized across various fields, includ...
Large language models (LLMs) have shown remarkable advancements in chemistry and biomedical research, acting as versatile foundation models for vari...