Infectious Disease

Pioneering Klebsiella Pneumoniae Antibiotic Resistance Prediction With Artificial Intelligence-Clinical Decision Support System-Enhanced Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry: Retrospective Study.

BACKGROUND: The rising prevalence and swift spread of multidrug-resistant gram-negative bacteria (MDR-GNB), especially Klebsiella pneumoniae (KP), present a critical global health threat highlighted by the World Health Organization, with mortality rates soaring approximately 50% with inappropriate antimicrobial treatment.

In silico formulation optimization and particle engineering of pharmaceutical products using a generative artificial intelligence structure synthesis method.

Pharmaceutical drug dosage forms are critical for ensuring the effective and safe delivery of active pharmaceutical ingredients to patients. However, traditional formulation development often relies on extensive lab and animal experimentation, which can be time-consuming and costly. This manuscript presents a generative artificial intelligence method that creates digital versions of drug products ...

Prediction of viral oncoproteins through the combination of generative adversarial networks and machine learning techniques.

Viral oncoproteins play crucial roles in transforming normal cells into cancer cells, representing a significant factor in the etiology of various can...

Leveraging large-scale Mycobacterium tuberculosis whole genome sequence data to characterise drug-resistant mutations using machine learning and statistical approaches.

Tuberculosis disease (TB), caused by Mycobacterium tuberculosis (Mtb), is a major global public health problem, resulting in > 1 million deaths each y...

Integrating AI into Breast Reconstruction Surgery: Exploring Opportunities, Applications, and Challenges.

Background: Artificial intelligence (AI) has significantly influenced various sectors, including healthcare, by enhancing machine capabilities in assi...

An Integrated TCN-CrossMHA Model for Predicting circRNA-RBP Binding Sites.

Circular RNA (circRNA) has the capacity to bind with RNA binding protein (RBP), thereby exerting a substantial impact on diseases. Predicting binding ...

The Role of Artificial Intelligence in Accelerating Vaccine Development: Challenges and Opportunities in Pandemic Preparedness.

Artificial intelligence (AI) has been studied and applied to medicines and vaccine development. However, there is still a need to understand the proce...

Pred-AHCP: Robust Feature Selection-Enabled Sequence-Specific Prediction of Anti-Hepatitis C Peptides via Machine Learning.

Every year, an estimated 1.5 million people worldwide contract Hepatitis C, a significant contributor to liver problems. Although many studies have ex...

Interaction-Based Inductive Bias in Graph Neural Networks: Enhancing Protein-Ligand Binding Affinity Predictions From 3D Structures.

Inductive bias in machine learning (ML) is the set of assumptions describing how a model makes predictions. Different ML-based methods for protein-lig...

A lightweight deep-learning model for parasite egg detection in microscopy images.

BACKGROUND: Intestinal parasitic infections are still a serious public health problem in developing countries, and the diagnosis of parasitic infectio...

Predicting synthetic mRNA stability using massively parallel kinetic measurements, biophysical modeling, and machine learning.

mRNA degradation is a central process that affects all gene expression levels, though it remains challenging to predict the stability of a mRNA from i...

Predictive modeling of COVID-19 mortality risk in chronic kidney disease patients using multiple machine learning algorithms.

The coronavirus disease 2019 (COVID-19) has a significant impact on the global population, particularly on individuals with chronic kidney disease (CK...

Rapid bacterial identification through volatile organic compound analysis and deep learning.

BACKGROUND: The increasing antimicrobial resistance caused by the improper use of antibiotics poses a significant challenge to humanity. Rapid and acc...

KnowVID-19: A Knowledge-Based System to Extract Targeted COVID-19 Information from Online Medical Repositories.

We present KnowVID-19, a knowledge-based system that assists medical researchers and scientists in extracting targeted information quickly and efficie...

Generative AI in the Advancement of Viral Therapeutics for Predicting and Targeting Immune-Evasive SARS-CoV-2 Mutations.

The emergence of immune-evasive mutations in the SARS-CoV-2 spike protein is consistently challenging existing vaccines and therapies, making precise ...

Computer vision applications for the detection or analysis of tuberculosis using digitised human lung tissue images - a systematic review.

OBJECTIVE: To conduct a systematic review of the computer vision applications that detect, diagnose, or analyse tuberculosis (TB) pathology or bacilli...

Screening for Potential Antiviral Compounds from Cyanobacterial Secondary Metabolites Using Machine Learning.

The secondary metabolites of seawater and freshwater blue-green algae are a rich natural product pool containing diverse compounds with various functi...

Artificial intelligence-aided colonoscopic differential diagnosis between Crohn's disease and gastrointestinal tuberculosis.

BACKGROUND AND AIM: Differentiating between Crohn's disease (CD) and gastrointestinal tuberculosis (GITB) is challenging. We aimed to evaluate the cli...

Enhancing SARS-CoV-2 Lineage Surveillance through the Integration of a Simple and Direct qPCR-Based Protocol Adaptation with Established Machine Learning Algorithms.

Emerging and evolving Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) lineages, adapted to changing epidemiological conditions, present u...

Balanced Training Sets Improve Deep Learning-Based Prediction of CRISPR sgRNA Activity.

CRISPR-Cas systems have transformed the field of synthetic biology by providing a versatile method for genome editing. The efficiency of CRISPR system...