Infectious Disease

Application of MALDI-TOF MS and machine learning for the detection of SARS-CoV-2 and non-SARS-CoV-2 respiratory infections.

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) could aid the diagnosis of acute respiratory infections (ARIs) owing to its affordability and high-throughput capacity. MALDI-TOF MS has been proposed for use on commonly available respiratory samples, without specialized sample preparation, making this technology especially attractive for implementation in...

Development and Validation of an Interpretable Conformal Predictor to Predict Sepsis Mortality Risk: Retrospective Cohort Study.

BACKGROUND: Early and reliable identification of patients with sepsis who are at high risk of mortality is important to improve clinical outcomes. However, 3 major barriers to artificial intelligence (AI) models, including the lack of interpretability, the difficulty in generalizability, and the risk of automation bias, hinder the widespread adoption of AI models for use in clinical practice.

Addressing the Research and Development Gaps in Modern Phage Therapy.

Antimicrobial resistance is on the rise globally, prompting increased research and development (R&D) of phage therapy as a strategy to address difficu...

Nonionic surfactant Tween 80-facilitated bacterial transport in porous media: A nonmonotonic concentration-dependent performance, mechanism, and machine learning prediction.

The surfactant-enhanced bioremediation (SEBR) of organic-contaminated soil is a promising soil remediation technology, in which surfactants not only m...

Differential Diagnosis of Diabetic Foot Osteomyelitis and Charcot Neuropathic Osteoarthropathy with Deep Learning Methods.

Our study aims to evaluate the potential of a deep learning (DL) algorithm for differentiating the signal intensity of bone marrow between osteomyelit...

Understanding COVID-19 infection among people with intellectual and developmental disabilities using machine learning.

BACKGROUND: People with intellectual and developmental disabilities (IDD) were disproportionately affected by the COVID-19 pandemic. Predicting COVID-...

Assisting the infection preventionist: Use of artificial intelligence for health care-associated infection surveillance.

BACKGROUND: Health care-associated infection (HAI) surveillance is vital for safety in health care settings. It helps identify infection risk factors,...

Enhancing pediatric pneumonia diagnosis through masked autoencoders.

Pneumonia, an inflammatory lung condition primarily triggered by bacteria, viruses, or fungi, presents distinctive challenges in pediatric cases due t...

Deep learning in public health: Comparative predictive models for COVID-19 case forecasting.

The COVID-19 pandemic has had a significant impact on both the United Arab Emirates (UAE) and Malaysia, emphasizing the importance of developing accur...

MIS-Net: A deep learning-based multi-class segmentation model for CT images.

The accuracy of traditional CT image segmentation algorithms is hindered by issues such as low contrast and high noise in the images. While numerous s...

Artificial Intelligence in Plastic Surgery: Analysis of Applications, Perspectives, and Psychological Impact.

Artificial intelligence (AI) is emerging as a promising tool in the field of plastic surgery, offering a wide array of applications that enhance surgi...

Socially Assistive Robots for patients with Alzheimer's Disease: A scoping review.

BACKGROUND: The most common form of dementia, Alzheimer's Disease (AD), is challenging for both those affected as well as for their care providers, an...

Multi-modal deep learning methods for classification of chest diseases using different medical imaging and cough sounds.

Chest disease refers to a wide range of conditions affecting the lungs, such as COVID-19, lung cancer (LC), consolidation lung (COL), and many more. W...

Binding Activity Classification of Anti-SARS-CoV-2 Molecules using Deep Learning Across Multiple Assays.

BACKGROUND: The coronavirus disease-2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2), has urgently nec...

Waste to resource: Mining antimicrobial peptides in sludge from metagenomes using machine learning.

The emergence of antibiotic-resistant bacteria poses a huge threat to the treatment of infections. Antimicrobial peptides are a class of short peptide...

Prognosis of COVID-19 severity using DERGA, a novel machine learning algorithm.

It is important to determine the risk for admission to the intensive care unit (ICU) in patients with COVID-19 presenting at the emergency department....

Parallel prediction of dengue cases with different risks in Mexico using an artificial neural network model considering meteorological data.

In 2022, Mexico registered an increase in dengue cases compared to the previous year. On the other hand, the amount of precipitation reported annually...

Deep model predictive control of gene expression in thousands of single cells.

Gene expression is inherently dynamic, due to complex regulation and stochastic biochemical events. However, the effects of these dynamics on cell phe...

Enhancing parasitic organism detection in microscopy images through deep learning and fine-tuned optimizer.

Parasitic organisms pose a major global health threat, mainly in regions that lack advanced medical facilities. Early and accurate detection of parasi...

Deep-learning assisted zwitterionic magnetic immunochromatographic assays for multiplex diagnosis of biomarkers.

Magnetic nanoparticle (MNP)-based immunochromatographic tests (ICTs) display long-term stability and an enhanced capability for multiplex biomarker de...